HomeMy WebLinkAboutAlaska Affordable Energy Strategy 2017THE ALASKA AFFORDABLE ENERGY STRATEGY
METHODOLOGY, FINDINGS, AND RECOMMENDATIONS
February 2017
www.akenergyauthority.org
This report was made possible through a legislative mandate in SLA 2014 SB 138 requiring Alaska Energy Authority
(AEA) to investigate opportunities for delivering affordable energy infrastructure in non-Railbelt communities.
Principal Investigator: Neil McMahon, Energy Planning Manager, AEA
February 2017 Abstract Page | 3
ABSTRACT
The Alaska Affordable Energy Strategy (AkAES) fulfills the legislative mandate set out as part of Senate Bill
138 (SB138) in May 2014. SB138 required that the Alaska Energy Authority (AEA) develop a “plan and
recommendations to the legislature on infrastructure needed to deliver affordable energy to areas in the
state that do not have direct access to a North Slope natural gas pipeline.”
Not long after beginning the project, it became clear that AEA had two daunting tasks: 1) Deliver more
affordable energy in the study area, and 2) respond to the immediate fiscal crisis so that communities do
not lose critical energy services. Fortunately, research indicated that the state can tackle both tasks
simultaneously.
Research did not discover any “one-size-fits-all” solutions for bringing more affordable energy to
communities: No single fuel, resource, or practice can solve the decades-old dilemma of energy
affordability in Alaska’s communities. With this in mind, the AkAES is a new, but not revolutionary, suite
of recommended changes to incrementally improve the delivery of state energy programs. Through more
efficient and effective resource allocation, the state has the expertise and experience to confront both
the current fiscal challenges and help ensure the affordability of energy.
The following recommendations, grouped into four categories, aim to increase the efficiency of state
funding and increase affordability by maintaining cost-effective projects by bankable entities for their
useful life.
1. Identify most appropriate projects – Data collection and analysis can be improved to address the
unique resources and needs of communities. The state can increase technical assistance to identify,
plan, and finance the most appropriate projects.
2. Finance cost-effective projects – The state should direct funding to address investment barriers in
communities and to address affordability challenges. Expanding the availability and sources of
financing for generation, fuel supply and storage, and residential and non-residential efficiency will
allow communities to more easily pursue cost-effective projects.
3. Establish system of accountability and sustainability – Through technical assistance and
requirements, this system of accountability will help increase communities’ access to financing,
reduce non-fuel costs, increase consumer protection and maximize the economic benefit of
investments. State assistance to meet new standards will be augmented by supporting
regional/statewide entities. Expanded utility requirements can help ensure the financial, managerial,
and technical capacity of utilities. Objective metrics are suggested to foster cost-effective
improvement in utility performance.
4. Fund programs – As required by the enabling legislation, AEA identified possible sustainable funding
sources including potential revenue from the proposed gasline and potential consumer charges.
February 2017 Acknowledgements Page | 4
ACKNOWLEDGEMENTS
This report was funded by the 28th Alaska State Legislature in 2014 as part of Senate Bill 138.
The Alaska Energy Authority is grateful to the assistance provided by the numerous peop le who were
directly and indirectly involved in the research, analysis, compilation, and editing of this report. With more
than 60 State and federal agencies, universities, private companies, utilities, and regional organizations
that provided assistance, it is not possible to thank everyone who was involved.
Without the data provided, expert opinion and guidance, and critique of work products provided by these
individuals and entities, the Alaska Affordable Energy Strategy would have been less successful. AEA is
particularly grateful for the team at the University of Alaska Fairbanks’ Geographic Information Network
of Alaska (GINA) for correcting AEA’s math and logic and coding of the Alaska Affordable Energy Model.
Without their work, much of the quantitative analysis in this report would been impossible.
Any unintended errors remaining in this report are the responsibility of the Alaska Energy Authority.
February 2017 Contents Page | 5
CONTENTS
Abstract ......................................................................................................................................................... 3
Acknowledgements ....................................................................................................................................... 4
Contents ........................................................................................................................................................ 5
Figures ........................................................................................................................................................... 7
Tables .......................................................................................................................................................... 10
Acronyms and Abbreviations ...................................................................................................................... 11
Chapter 1: Overview of the Alaska Affordable Energy Strategy ................................................................. 13
The requirements of the Alaska Affordable Energy Strategy ................................................................. 14
How the AkAES defines the terms in the legislation ............................................................................... 15
How to read the report ........................................................................................................................... 25
Chapter 2: Current conditions of the AkAES study area ............................................................................. 27
Population ............................................................................................................................................... 28
Energy sources, consumption, and costs across the study area ............................................................ 33
Forecasts ................................................................................................................................................. 50
Investment needed to maintain the current level of service in AkAES communities ............................ 56
The ability of communities and regions to pay for energy infrastructure .............................................. 57
Chapter 3: Energy cost drivers .................................................................................................................... 64
Drivers for the delivered cost of diesel ................................................................................................... 65
Drivers of consumer electric rate ........................................................................................................... 73
Retail cost of heating oil ......................................................................................................................... 88
Drivers for heating fuel and electricity consumption ............................................................................. 91
Chapter 4: Risks and barriers to successful energy project implementation ............................................. 99
Documenting and analyzing energy project risks and barriers............................................................. 100
Chapter 5: The impact of programs on energy affordability and state energy policies ........................... 119
Funding levels for state and federal energy programs ......................................................................... 166
How state energy programs help to achieve state energy policies ...................................................... 169
Chapter 6: Infrastructure and non-infrastructure opportunities to reduce community energy costs .... 173
Opportunities investigated for more affordable energy in communities ............................................ 174
Comparison of opportunities ................................................................................................................ 203
Chapter 7: Plan and recommendations .................................................................................................... 207
Plan to address key barriers to affordable energy ................................................................................ 207
Recommendations ................................................................................................................................ 217
References and Resources ........................................................................................................................ 243
Appendix A: Relevant Statutory Language from SB 138 ........................................................................... 252
February 2017 Contents Page | 6
Appendix B: Description of Alaska Affordable Energy Model................................................................... 253
Contents ................................................................................................................................................ 253
Purpose ................................................................................................................................................. 254
Data sources for model ......................................................................................................................... 254
Global model assumptions.................................................................................................................... 256
Forecasts ............................................................................................................................................... 256
AAEM modules ...................................................................................................................................... 258
AAEM distribution, installation, and results ......................................................................................... 266
February 2017 Figures Page | 7
FIGURES
Figure 1: Map of Alaska Affordable Energy Strategy study area ................................................................................. 14
Figure 2: Median household income by Census area .................................................................................................. 18
Figure 3: Total population by AEA energy region ........................................................................................................ 28
Figure 4: Range of community populations by AEA energy region ............................................................................. 29
Figure 5: Regional average yearly population growth rates by AEA energy region .................................................... 31
Figure 6: Outmigration and inmigration by AEA energy regions ................................................................................. 32
Figure 7: End-use energy consumption by AEA energy region .................................................................................... 33
Figure 8: Gallons of diesel and heating oil consumed by AEA energy region .............................................................. 34
Figure 9: Energy source for electricity by AEA energy region ...................................................................................... 35
Figure 10: Primary source of residential heat by AEA energy region .......................................................................... 36
Figure 11: Per capita consumption in MMBtu/year by community size ..................................................................... 37
Figure 12: Per capita energy cost by size of community ............................................................................................. 38
Figure 13: Regional average per capita electricity consumption for residential and non-residential customers ....... 39
Figure 14: Average gallons of heating oil equivalent consumed per household ......................................................... 42
Figure 15: Regional averages for residential and non-residential electricity rates before PCE reimbursement ......... 44
Figure 16: Map of residential electricity prices in AkAES study area ........................................................................... 46
Figure 17: Map of community heating oil price in AkAES study area (2015) .............................................................. 49
Figure 18: Historical yearly average Brent crude oil price and 2016 Energy Information Adminstration forecast ..... 51
Figure 19: Diesel price—Historical and forecast for Bethel ......................................................................................... 52
Figure 20: Heating oil price—Historical and forecast for Bethel ................................................................................. 53
Figure 21: Electricity price—Historical and forecast for Bethel ................................................................................... 54
Figure 22: Electricity consumption—Historical and forecasted for Bethel ................................................................. 55
Figure 23: Per capita tax revenue by AEA energy region ............................................................................................ 58
Figure 24: Communities with a federally recognized tribe by AEA energy region ...................................................... 61
Figure 25: Diagram of the components of consumer energy costs ............................................................................. 64
Figure 26: Relationship between crude oil price and delivered diesel price ............................................................... 65
Figure 27: Components of delivered price of diesel: Crude oil & refining .................................................................. 67
Figure 28: Delivered price of fuel to PCE communities by transportation mode (Assumes $50/bbl crude oil) .......... 68
Figure 29: Components of the delivered price of diesel: Barge transportation .......................................................... 69
Figure 30: Components of the delivered price of diesel: Local storage ...................................................................... 72
Figure 31: Components of electricity price: Fuel cost ................................................................................................. 73
Figure 32: Cost of fuel as a percent of residential rate for PCE-eligible utilities, ......................................................... 74
Figure 33: Impact of generation efficiency on fuel cost in $/kWh .............................................................................. 75
Figure 34: Generation efficiency’s impact on the cost of power ................................................................................. 76
Figure 35: Generation efficiency in PCE-eligible communities .................................................................................... 77
Figure 36: Impact of line loss on the cost of power .................................................................................................... 78
Figure 37: Range of reported, allowable non-fuel utility cost ..................................................................................... 79
Figure 38: Components of electricity price: Utility non-fuel costs .............................................................................. 80
Figure 39: Utility non-fuel costs per kWh vs. kWh generated ..................................................................................... 81
Figure 40: Non-generation expenses vs. annual kWh sales by organization type ....................................................... 82
Figure 41: Distribution of non-generation expenses by organization type ................................................................. 83
Figure 42: Utility rates as a percentage of reported, allowable costs ......................................................................... 84
Figure 43: Components of electricity price: Rates above reported, eligible ............................................................... 86
February 2017 Figures Page | 8
Figure 44: Weighted average cost of capital for PCE utilities ...................................................................................... 88
Figure 45: Average yearly difference between retail heating oil and utility diesel unit cost by AEA energy region ... 89
Figure 46: Components of delivered price of heating oil: Local markup ..................................................................... 90
Figure 47: Heating degree days ................................................................................................................................... 92
Figure 48: Range of average community residential building size .............................................................................. 94
Figure 49: Residential energy costs per AHFC star rating for three communities ....................................................... 95
Figure 50: Range of residential heating consumption (in gallons of heating oil equivalent) ...................................... 96
Figure 51: Fuels consumed for residential heating ..................................................................................................... 97
Figure 52: Distribution of benefit-cost ratios for REF applications ............................................................................ 104
Figure 53: Identified barriers of REF proposals ......................................................................................................... 105
Figure 54: Status of REF projects by project phase ................................................................................................... 106
Figure 55: Status of REF projects by technology type ............................................................................................... 107
Figure 56: Reasons for REF projects not continuing to construction ........................................................................ 108
Figure 57: Reasons for AEA Bulk Fuel Loan applications being declined ................................................................... 110
Figure 58: Percent of Bulk Fuel Loans declined by region ......................................................................................... 110
Figure 59: Cost of equity estimate vs. annual sales for PCE utilities ......................................................................... 112
Figure 60: Reported barriers to REF project performance ........................................................................................ 114
Figure 61: Number of electrical emergency response by type provided by AEA ...................................................... 116
Figure 62: Rural Power System Upgrade Program for AEA and AVEC by funding by year and source ..................... 122
Figure 63: Distribution of Rural Power System Upgrade funding by AEA energy regions (2000-2015) .................... 122
Figure 64: Change in powerhouse efficiency after RPSU project .............................................................................. 124
Figure 65: Bulk Fuel Upgrade funding by source and year ........................................................................................ 128
Figure 66: Bulk Fuel Upgrade funding by AEA energy region .................................................................................... 129
Figure 67: Renewable Energy Fund appropriations and match (2008-2015) ............................................................ 132
Figure 68: Renewable Energy Fund grants by AEA energy region ............................................................................. 132
Figure 69: Fuel displaced by REF projects (2009-2015) ............................................................................................. 133
Figure 70: Percent of total energy savings from REF program by AEA energy region ............................................... 134
Figure 71: Weatherization funding by source (2000-2016) ....................................................................................... 136
Figure 72: Weatherization Program units by AEA energy region .............................................................................. 137
Figure 73: Weatherization program total estimated annual energy cost savings by AEA energy region ................. 137
Figure 74: Annual funding for Home Energy Rebate program (2008-2015) .............................................................. 139
Figure 75: Estimated Home Energy Rebates disbursed per AEA energy region ........................................................ 139
Figure 76: Annual energy cost savings for Home Energy Rebate program ............................................................... 141
Figure 77: Houses accessing New Home Rebate program 2008-2016 ...................................................................... 142
Figure 78: New Home Rebates per AEA energy region ............................................................................................. 143
Figure 79: Village Energy Efficiency Program Funding (2005-2015) .......................................................................... 144
Figure 80: VEEP funding by region (2005-2015) ........................................................................................................ 145
Figure 81: Estimated annual savings from VEEP communities (2005-2015) ............................................................. 146
Figure 82: Annual Power Cost Equalization subsidy (FY2001-2016) ......................................................................... 148
Figure 83: FY2001-2016 Power Cost Equalization subsidy per AEA energy region ................................................... 148
Figure 84: Residential electricity rates in Power Cost Equalization communities ..................................................... 150
Figure 85: Yearly funding for LIHEAP & AKHAP (2000-2015) ..................................................................................... 151
Figure 86: Total LIHEAP and AKHAP funding by AEA energy region (2000-2015) .................................................... 152
Figure 87: Average heating fuel subsidy per participating household for LIHEAP/AKHAP (2000-2015) ................... 152
Figure 88: PPF applications by region ........................................................................................................................ 154
Figure 89: Power Project Loan Fund: principal advanced per year ........................................................................... 155
February 2017 Figures Page | 9
Figure 90: Bulk Fuel Loan program disbursements ................................................................................................... 156
Figure 91: Total value of Bulk Fuel Loan program by AEA energy region (2000-2013) ............................................. 157
Figure 92: Cost of AEA electrical emergency response per year ............................................................................... 161
Figure 93: Electrical Emergency Response cost per region per year ......................................................................... 162
Figure 94: Frequency of communities accessing AEA Electrical Emergency Response (2005-2015) ........................ 162
Figure 95: Number of trainees per AEA course ......................................................................................................... 164
Figure 96: Non-programmatic state direct legislative energy appropriations by AEA energy region ....................... 165
Figure 97: Historical state and federal energy funding ............................................................................................. 168
Figure 98: Components of consumer energy costs ................................................................................................... 175
Figure 99: Non-generation costs per kWh by cost bin and organization type .......................................................... 186
Figure 100: Range of non-generation operating costs by organization type ............................................................ 189
Figure 101: Example of residential savings from weatherization .............................................................................. 201
February 2017 Tables Page | 10
TABLES
Table 1: Contracted deliverables that informed the AkAES ........................................................................................ 25
Table 2: Distribution of population by community size ............................................................................................... 30
Table 3: Mean consumption per residential customer per month in PCE communities ............................................. 40
Table 4: Percentage of non-residential electricity consumption by building type ...................................................... 41
Table 5: Percent of total non-residential heating fuel consumption by community size ............................................ 42
Table 6: Cost conversions for various energy sources ................................................................................................. 43
Table 7: USDA loans for businesses, energy programs, hospitals, water systems, and housing in Alaska (2009-2015)
............................................................................................................................................................................ 63
Table 8: Average non-residential building square footage by building type and community size .............................. 93
Table 9: Non-residential electric consumption per square foot by building type and community population .......... 98
Table 10: Risks and barriers to successful energy projects ....................................................................................... 101
Table 11: Long-term reduction in fuel costs due to efficiency improvement after RPSU project ............................. 125
Table 12: Reduction in generation costs due to RPSU capital grants ........................................................................ 126
Table 13: Value of bulk fuel upgrades in $/gallon ..................................................................................................... 130
Table 14: Emerging Energy Technology Fund appropriations by year and source .................................................... 135
Table 15: Home Energy Rebate program cost-effectiveness..................................................................................... 141
Table 16: PCE generation efficiency and line loss standards ..................................................................................... 149
Table 17: Municipal Energy Assistance Program 2006-2008 ..................................................................................... 153
Table 18: Energy Efficiency Interest Rate Reduction based on efficiency improvement .......................................... 159
Table 19: AEA training program participation by region (1995-2014)....................................................................... 164
Table 20: Per capita direct legislative appropriations by AEA energy region ............................................................ 166
Table 21: Savings from increasing generation efficiency in PCE-eligible communities ............................................. 179
Table 22: Potential savings from reducing line loss to 10% in PCE-eligible utilities .................................................. 180
Table 23: Hydropower opportunity ........................................................................................................................... 183
Table 24: Wind power opportunity ........................................................................................................................... 184
Table 25: Solar PV opportunity .................................................................................................................................. 185
Table 26: Non-residential efficiency opportunity ...................................................................................................... 191
Table 27: Biomass (cordwood) opportunity .............................................................................................................. 193
Table 28: Biomass (pellet) opportunity ..................................................................................................................... 194
Table 29: Non-residential ASHP opportunity ............................................................................................................. 195
Table 30: Residential ASHP opportunity .................................................................................................................... 196
Table 31: Heat recovery opportunity, includes communities with an existing study ............................................... 197
Table 32: Rate of housing construction in AkAES study area .................................................................................... 199
Table 33: Residential energy efficiency opportunity ................................................................................................. 200
Table 34: Water & wastewater efficiency opportunity ............................................................................................. 202
Table 35: Comparison of infrastructure opportunities .............................................................................................. 204
Table 36: Comparison of non-infrastructure opportunities ...................................................................................... 205
Table 37: Recommendation A1—Basic community and utility data to be collected ................................................ 220
Table 38: Recommendation A1—Current community infrastructure data to be collected ...................................... 221
Table 39: Recommendation A1—Utility business management data to be collected .............................................. 222
Table 40: Recommendation A1—State energy program data to be collected .......................................................... 222
February 2017 Acronyms Page | 11
ACRONYMS AND ABBREVIATIONS
AAEM Alaska Affordable Energy Model
ABSN Alaska Science Building Network
ACEP Alaska Center for Energy and Power
(University of Alaska Fairbanks)
ACS American Community Survey
AEA Alaska Energy Authority
AEDG Alaska Energy Data Gateway
AEDI Alaska Energy Data Inventory
AEERLP Alaska Energy Efficiency Revolving Loan
Program
AFN Alaska Federation of Natives
AG Attorney General
AGDC Alaska Gasline Development Corporation
AHFC Alaska Housing Finance Corporation
AIDEA Alaska Industrial Development & Export
Authority
AkAES Alaska Affordable Energy Strategy
AKHAP Alaska Heating Assistance Program
AMI Area median income
ANCSA Alaska Native Claims Settlement Act
ANTHC Alaska Native Tribal Health Consortium
AO 247 Administrative Order 247
APC Alaska Power Company
ARIS Alaska Retrofit Information System
ARRA American Recovery and Reinvestment Act
ARUC Alaska Rural Utility Collaborative
ASHP Air-source heat pump
AVEC Alaska Village Electric Cooperative
AVTEC Alaska Vocational Technical Center
B/C Benefit-cost Ratio
BEES Building Energy Efficiency Standard
BFU Bulk Fuel Upgrade Program
BNEF Bloomberg New Energy Finance
CAPEX Capital expenditures
CCHRC Cold Climate Housing Research Center
CDQ Community development quota
CEFA Community Energy Fund for Alaska
CF Community facilities [USDA program]
CFL Compact fluorescent lamp
CHP Combined Heat & Power
COE Cost of equity
COP Coefficient of performance
COPA Cost of power adjustment
C-PACE Commercial Property Assessed Clean
Energy
CPCN Certificate of public convenience and
necessity
DCCED Alaska Department of Commerce,
Community, and Economic Development
DCRA Alaska Division of Community & Regional
Affairs
DHSS Alaska Department of Health & Social
Services
DOE U.S. Department of Energy
DOL&WD Alaska Department of Labor & Workforce
Development
DOT&PF Alaska Department of Transportation &
Public Facilities
EECBG Energy Efficiency Community Block Grants
EERS Energy Efficiency Resource Standard
EETF Emerging Energy Technology Fund
EIA Energy Information Administration
EM&V Evaluation, measurement, and verification
EPA U.S. Environmental Protection Agency
ESCO Energy service company
EUI Energy Use Intensity
GAO General Accountability Office
GINA Geographic Information Network of Alaska
GIS Geographic Information System
GSHP Ground-source heat pump
HDD Heating degree days
HER Home Energy Rebate Program
HUD US Department of Housing & Urban
Development
IPEC Inside Passage Electric Cooperative
IPP Independent power producer
IRS Internal Revenue Service
ISER Institute of Social and Economic Research
(University of Alaska Anchorage)
kW Kilowatt
kWh Kilowatt-hour
LBNL Lawrence Berkeley National Laboratory
LED Light-emitting diode
LIHEAP Low-income heating assistance program
LNG Liquefied natural gas
MAFA Mark A. Foster & Associates
MCF One thousand cubic feet
February 2017 Acronyms Page | 12
MHI Median household income
MMbtu 1 million British thermal units
MW Megawatt
MWh Megawatt-hour
NASEO National Association of State Energy Offices
NGO Non-governmental organization
NPV Net present value
NREL National Renewable Energy Laboratory
NSB North Slope Borough
NSEDC Norton Sound Economic Development
Corporation
NWAB Northwest Arctic Borough
O&M Operations and maintenance
OPEX Operating expenditures
PCE Power Cost Equalization
PILT Payments in lieu of taxes
PPESCO Public purpose energy service company
PPF Power Project Fund
PV Photovoltaic
R&R Repair and replacement
RCA Regulatory Commission of Alaska
REF Renewable Energy Fund
ROE Return on equity
ROI Return on investment
RPSU Rural Power System Upgrade
RUS Rural utility service
SB 138 Alaska Senate Bill 138-2014
SEIRP Southeast Integrated Resource Plan
SETS Sustainable Energy Transmission & Supply
SWAMC Southeast Alaska Municipal Conference
TCC Tanana Chiefs Conference
UAA University of Alaska, Anchorage
UACED University of Alaska, Center for Economic
Development
UAF University of Alaska, Fairbanks
USACE U.S. Army Corps of Engineers
USDA U.S. Department of Agriculture
VEEP Village Energy Efficiency Program
VEIC Vermont Energy Investment Corporation
VEUEM Village End Use Efficiency Measures
WTI West Texas Intermediate
WVR Whole Village Retrofit
Wx Weatherization Assistance Program
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 13
CHAPTER 1: OVERVIEW OF THE ALASKA AFFORDABLE ENERGY STRATEGY
Due to the critical importance of safe and reliable space heat and electric energy, the Alaska Energy
Authority (AEA) was tasked by the 28th Alaska Legislature to make recommendations for energy policy
consideration. The Alaska Affordable Energy Strategy (AkAES) is the result of AEA’s effort to fulfill that
responsibility.
The “Alaska Affordable Energy Strategy” refers to both the multi-year, multi-stakeholder project
undertaken to meet the legislative mandate, as well as the results of that project. Those results are
summarized in the current report. They include a strategic plan or framework for improving the way the
State identifies, evaluates, develops, and maintains cost-effective energy solutions in non-Railbelt Alaska
communities, followed by recommendations for how the framework can be implemented through policy
levers, regulatory incentives, financing mechanisms, and other administrative tools.
The catalyst for the AkAES project was early planning for the new revenue stream that would result from
a natural gas pipeline (“gasline”), another project initiated by the 28 th Legislature. While that revenue
stream remains at a minimum 10 years away, the AkAES recommendations point to actionable solutions
that would make a positive impact with or without a gasline, including many that could be implemented
immediately.
Access to safe and reliable heat and electricity is essential. The State of Alaska, through AEA and other
State agencies, plays an important role in planning for and investing in energy infrastructure in all parts of
the state, both within and outside the Railbelt. Alaska’s high cost of energy creates a burden for Alaskans
that the State has been working to address for decades. Ensuring the safety and reliability of energy
systems increases the security of Alaskan families. Reducing energy costs leaves money in consumers’
pockets, increasing their standard of living and creating jobs when that savings is spent on other goods
and services.
The AkAES project investigated specific new infrastructure opportunities for delivering more affordable
energy to non-Railbelt communities. It also studied the efficacy of existing energy programs and potential
policy or regulatory changes that could contribute to more affordable, safe, stable, and reliable consumer
energy in non-Railbelt communities. After more than two years of research and analysis, the primary
conclusion is that the State can best improve the affordability of energy in AkAES study area communities
by developing a streamlined, data-driven framework to identify, evaluate, develop, and maintain cost-
effective energy solutions.
To recommend ways to improve the State’s delivery of energy programs, the AkAES analysis drew from
decades of experience working to bring safe, stable, and reliable energy to rural communities, while also
considering current economic conditions. Of critical importance in light of the State’s recent fiscal
challenges, the AkAES provides valuable insights for how to ease the transition from a reliance on grants
for funding energy infrastructure to a new paradigm in which loans and private investment play a larger
role. This transition will require a significant change in the way we think about and do things. The AkAES
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 14
includes recommendations to guide that change which, if implemented, would result in a more
sustainable energy infrastructure in Alaska communities.
THE REQUIREMENTS OF THE ALASKA AFFORDABLE ENERGY STRATEGY
The legislative mandate that became the AkAES was passed in 2014 as part of Senate Bill 138 (SB 138) and
is contained in Section 75, Chapter 14, SLA 2014 [HCS CSSB 138(FIN) am H]. The study area specified in
the legislation includes all areas of the state that would not have direct access to the proposed North
Slope natural gas pipeline. Working with the Alaska Gasline Development Corporation (AGDC), AEA
defined the study area as the entire state excluding communities served by the Railbelt electric grid. This
includes more than 200 communities and a total population of over 165,000.
Under SB 138, AEA was instructed to:
“develop a plan for developing infrastructure to deliver more affordable energy to areas of
the state that are not expected to have direct access to a North Slope natural gas pipeline;”
“identify ownership options, different energy sources… [and] recommend the means for
generating, delivering, receiving, and storing energy in the most cost-efficient manner;”
Figure 1: Map of Alaska Affordable Energy Strategy study area
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 15
“consider the development of regional energy systems that can receive and store bulk fuel;”
“[for] those citizens for whom there is no economically viable infrastructure available,
recommend the means for directly underwriting the energy costs of the citizens to make
their energy costs more affordable;”
“recommend a plan for funding the design, development, and construction of the required
infrastructure” including to “identify a source of rent, royalty, income or tax;” and
“provide the plan and suggested legislation for the design, development, construction, and
financing of the required infrastructure to the legislature before January 1, 2017.”
The full text of the authorizing legislation can be found in Appendix A
AEA was also directed to consider existing State energy policy under AS 44.99.115 and Section 1, Chapter
82, SLA 2010. While the requirements under SB 138 focus on reducing costs to communities, significant
synergy exists between the AkAES and the earlier state energy policy, which set goals that the state:
achieve a 15 percent increase in energy efficiency on a per capita basis between 2010 and
2020;
receive 50 percent of its electric generation from renewable and alternative energy sources
by 2025;
work to ensure a reliable in-state gas supply for residents of the state; and
remain a leader in petroleum and natural gas production and become a leader in renewable
and alternative energy development.
The 2010 legislation also indicated that the power project fund (AS 42.45.010) should serve as the main
source of State assistance for energy projects. The AkAES addresses all these energy policies directly
except for ensuring a reliable in-state gas supply, which is outside AEA’s purview. Other elements of AS
44.99.115 and Section 1, Chapter 82, SLA 2010 are addressed elsewhere in the report.
HOW THE AKAES DEFINES THE TERMS IN THE LEGISLATION
Guided by its understanding of the Legislature’s intent, AEA had to determine how to define many of the
terms used in the authorizing legislation. This section outlines the terms and definitions used by AEA in
implementing the AkAES.
SECTORS
The legislation refers to delivering more affordable energy to “areas” and “citizens .” It does not list specific
sectors of the energy market that should or should not be addressed in the plan. After reviewing existing
state energy policy, AEA included the following sectors in the study:
Residential building heat and electricity
Non-residential building (private and public commercial) heat and electricity
Water and wastewater heat and electricity
Though the AkAES does not address opportunities within Alaska’s industrial and transportation sectors to
make energy more affordable, various recommendations in the study will benefit those sectors—
particularly the investigation of potential improvements in the fuel delivery system.
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 16
INFRASTRUCTURE
SB 138 requires that AEA “develop a plan for developing Infrastructure to deliver more affordable energy.”
AEA has interpreted “infrastructure” expansively to include electric and heat ge neration resources, both
renewable and non-renewable, as well as analysis of energy efficiency improvements to existing and
future residential and non-residential building stock.
COST-EFFICIENT AND ECONOMICALLY VIABLE
The legislation provided two tests for recommended infrastructure: “cost-efficient” and “economically
viable.” Using the common definition of cost-efficient, AEA interpreted it to mean projects whose benefits
outweigh their costs. AEA looks at costs and benefits from a universal perspective: that is, independent of
who pays for the project or receives the benefits. For example, if a project is grant funded, a community
might not include the grant as a cost, but the study would. Likewise, if the cost of electricity is reduced
but results in lower Power Cost Equalization (PCE) payments to the community, the AkAES will still count
the reduced costs as a benefit, even though the community does not receive the full savings benefit
directly.
Economic viability is similar in meaning to cost-efficient, but it places more emphasis on long-term
sustainability given market factors and projected revenues and ignores externalities (costs not paid for by
the producer or consumer and social or environmental benefits not given a monetary value). A project or
activity is predicted to be economically viable if projected revenues equal or exceed projected
expenditures, including financing costs, asset depreciation, and profit. In other words, economic viability
is a measure of profitability: revenues (rather than benefits) exceeding costs. Public policy in the form of
tax credits and subsidies can be used to make a project or technology more economically viable than it
would be otherwise. Selective taxes, tariffs and any regulation that increases development or operational
costs are examples of policies that can reduce a project or technology’s profitability.
AEA evaluates cost-effectiveness by modeling the costs and benefits of a proposed infrastructure project
over its expected economic lifespan using the Alaska Affordable Energy Model (AAEM). A detailed
explanation of the methods and assumptions used in the AAEM is included as Appendix B. The AAEM is
intended to be a living, perpetually updated energy evaluation and planning tool. It is available at
http://www.akenergyinventory.org/energymodel.
The results of the AAEM are included in Chapter 6 for many energy projects proposed throughout the
study area. These are high-level estimates most suited to the reconnaissance stage in project planning. To
refine these estimates for use in feasibility assessments or go/no -go financing or construction decisions
for individual projects will require the development of more site-specific detailed cost inputs based on
accurate resource assessments and technical/design specifications. It will also require revenue forecasts
based on completed business plans as well as knowledge of the particular project financing plans.
DIRECT UNDERWRITING AND CITIZENS
AEA was required to “recommend a means of directly underwriting” the cost of energy for “citizens” who
would not have access to cost-effective infrastructure. AEA interprets direct underwriting to mean directly
subsidizing the cost of energy.
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 17
SOURCES OF RENT, ROYALTY, INCOME OR TAX
The legislation requires that AEA identify a “source of rent, royalty, income, or tax” to help to pay for the
infrastructure. By definition, cost-effective projects will pay for themselves over time; but, by identifying
new revenue streams to help fund energy infrastructure, the State may be able to shorten those payback
periods, make marginal projects more economically viable, and increase the number of energy projects
that can be built. In 2014, the Legislature created the Affordable Energy Fund, which provisionally sets
aside a percentage of the State’s royalty gas revenue from a future North Slope gasline to help fund energy
projects in the AkAES study area. Given the uncertain future of the gasline and of State budgets, AEA
interprets this section of the AkAES authorizing legislation broadly to mean recommendations for
providing the State with near-term revenue as well as for preparing for the possible deployment of
Affordable Energy Fund revenue.
DEFINING “AFFORDABLE” ENERGY
AEA’s mission is to “reduce the cost of energy in Alaska.” The agency and the State are keenly aware of
the need to make energy more affordable, especially in rural areas of the state where the burden of high
energy prices hits hardest. In the course of this study, AEA investigated two different ways to define
“affordable” as a measurable target for assessing competing energy projects or policies, but neither
proved wholly satisfactory.
1. Unit cost parity across Alaska: While bringing energy costs in the AkAES study area down to costs
paid in Southcentral would be ideal, it is not financially or technically feasible to do so. AEA estimates
that the 200+ communities in the AkAES region spend over $630 million for heat and electricity
annually, after State and federal subsidies. That includes approximately $330 million in heating and
$300 million in electric costs. To bring that down to Southcentral levels would require a reduction in
energy costs of $330 million or 52%. To put this in perspective, PCE payments in FY16 were
approximately $31 million, less than 10% of the annual subsidy that would be required to achieve
energy cost parity with Southcentral. That level of subsidy is not achievable with the State’s current
fiscal gap and would not be sustainable in any foreseeable fiscal future.
2. Percent of income: Affordability can be defined in relative terms: the more money a household has,
the higher the energy costs it can afford. Numerous international standards exist for what constitutes
“affordable” energy, generally falling between 10-20% of household income.1 For comparison sake,
the University of Alaska’s Institute of Social and Economic Research (ISER) published a study in 2007
that estimated that energy costs in Anchorage were 3.1% of median household income and 9.9% in
remote communities in 2006.2 The State and federal government consider applicant income in
determining eligibility for a number of energy-related programs including low income Weatherization
1 Compiled in Samuel Fankhauser and Sladjana Tepic. “Can poor consumers pay for energy and water? An affordability analysis
for transition countries.” European Bank for Reconstruction and Development. May 2005.
http://www.ebrd.com/downloads/research/economics/workingpapers/wp0092.pdf
2 Ben Saylor and Sharman Haley. “Effects of Rising Utility Costs on Household Budgets, 2000-2006.” March 2007.
http://www.iser.uaa.alaska.edu/Publications/risingutilitycosts_final.pdf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 18
Assistance Program 3 and the Low Income Heating Assistance Program (LIHEAP).4 Neither program
sets a maximum threshold for the percent of household income spent on energy costs. Eligibility is
determined by household, not by community, through income data provided by the applicant.
Unfortunately, no reliable data source exists that would allow the State to make a similar
determination at a community scale. The international standards referenced above do not take into
account the cost of living in different regions and sub-regions of the state. Median household income
(MHI) is the most likely measure that could be used, in combination with localized energy costs, to
establish a standard for affordable energy that could be applied at the whole community level.
For example, if a community’s MHI were $50,000 and the statewide standard for energy affordability
were set at 15% of household income, then average household energy costs of $7,500 per year or less
would be considered affordable. Maximum rates for electricity and heating fuels could be based on
this value and energy costs above the threshold would make the community eligible for affordable
energy investments or subsidies. However, in Alaska, Census areas are generally the smallest
geographic unit for which the MHI is accurate. The MHI for Alaska Census areas is shown in Figure 2.
Figure 2: Median household income by Census area5
Statewide the median household income is close to $70,000. As can be seen in Figure 2, much the AkAES
study area has an MHI nearly half the statewide average. However, there is a risk of failing to serve high-
need communities due to reliance on this more-accurate, regional-level data which may not reflect the
reality at the community level. The MHI in individual communities can vary greatly from that of the Census
area; there may be communities with low MHIs in regions with high MHIs and vice versa. Also low-income
3 https://www.benefits.gov/benefits/benefit-details/1842
4 https://www.benefits.gov/benefits/benefit-details/1411
5 American Community Survey 2014 5-Year TRACT 02 ALASKA X19: Income Table https://www.census.gov/geo/maps-
data/data/tiger.html
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 19
residents in high MHI communities could be adversely affected if funding decisions were only based on
regional and community-level data. All communities include both high and low-income households.
The unreliability of community-level census data is due to the small populations and sample sizes outside
urban Alaska. The margin of error for MHI is well over 100% in some communities. As one example, the
Census Bureau’s estimate for MHI in Lime Village was $145,313 with a margin of error of plus or minus
$266,070 (183%).6 It would not be prudent to make funding decisions based on data with this level of
uncertainty.
Given the challenges of developing a statewide measure for “affordable” energy that could be applied
fairly and sustainably across communities, AEA decided its resources would be more practically used in
developing a plan for delivering energy services to Alaska’s communities in the most cost-effective
manner. This plan and the accompanying recommendations can have a positive impact on Alaska’s
communities even with the current fiscal challenges.
RESEARCH METHODS
In two years of research, AEA drew on: the expertise of state, national and international entities and
energy stakeholder groups; historical outcomes of State and federal energy programs; policy
recommendations; and previous work from State, federal, and NGO researchers. AEA has learned from
and built on these previous efforts, while coordinating with concurrent local, regional, and federal efforts
in energy planning to minimize the duplication of work.
The AkAES assessed current and past energy programs and policies for effectiveness, identified and filled
in gaps in key areas where data and analysis was lacking, and solicited feedback and critique from a wide
range of stakeholders, including academics, national labs, and other local, regional, and statewide entities.
AEA’s research focused on identifying the most effective policy levers the State could use to help Alaska
communities succeed in their energy programs given current budget realities. To accomplish this,
significant work was done to evaluate potential infrastructure and policy options. The recommendations
that resulted from this research will not alleviate all the challenges of delivering affordable energy to
communities, but will point to definitive actions that can help Alaskan citizens and communities.
STAKEHOLDER INVOLVEMENT
AEA worked with three distinct stakeholder groups throughout the AkAES project:
Technical Advisory Committee: Comprised of the Alaska Center for Energy and Power (ACEP), the
Institute of Social and Economic Research (ISER), and the Alaska Gasline Development Corporation
(AGDC), the technical advisory committee provided guidance on study methodology as well as assessment
and evaluation of technology solutions.
6 US Census Bureau. “American Community Survey 2009-2013 5-Year Estimates.” Accessed from Division of Community and
Regional Affairs Community Database Online.
https://www.commerce.alaska.gov/dcra/DCRAExternal/community/Details/5db73dd9-b52c-486a-acf4-a323b8d8f3cf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 20
Advisory Group: Comprised of eight state and regional organizations, the Advisory Group provided
guidance and review of material developed over the course of the study, including work done by AEA and
its contractors. Advisory Group members included the AGDC, Alaska Federation of Natives (AFN),
Department of Transportation and Public Facilities (DOT&PF), Tanana Chiefs Conference (TCC), Inside
Passage Electric Cooperative (IPEC), Northwest Arctic Borough (NWAB), and Nuvista Light and Electric
Cooperative. The Regulatory Commission of Alaska (RCA) was also a participant in the advisory group, but
withdrew once recommendations were introduced that impacted the RCA, but were not vetted at AkAES
meetings nor discussed with RCA representatives prior to inclusion in the report. The RCA representatives
had concerns that their involvement could be viewed as support for the recommendations.
Alaska Energy Stakeholders: Comprised of other local, regional, state, and federal governments and
NGOs, as well as private companies and utilities, this group contributed data, expertise, and review of
work products.
Participation and input from stakeholders and/or Advisory Group members is not an explicit or implicit
endorsement of the work or recommendations from the AkAES.
PREVIOUS ENERGY RESEARCH IN ALASKA
Before developing a scope of work for the AkAES project, AEA conducted a thorough investigation of
previous research and analysis that could serve as a foundation for the new study. The literature review
process continued throughout the AkAES study. As new problems were identified, new data sources were
discovered, and new ideas proffered.
AEA investigated previous work in three main categories: Best Practice, Best Ideas, and Best Data. Best
Practice investigated federal and NGO guides on how to do energy planning for states, regions and
communities. Best Ideas looked at studies completed previously in Alaska, including infrastructure and
policy studies. Best Data aimed to discover all the energy-related data that could be used to answer the
challenging and important requirements established by the legislation.
BEST PRACTICE—NATIONAL GUIDANCE ON HOW TO DO ENERGY PLANNING
Although the AkAES is not a statewide energy plan, the study area is larger than any other state in the
union. In response to new energy regulations formulated in the federal Clean Power Plan, a number of
new national energy planning and data resources became available over the past few years. Federal
agencies, including the Environmental Protection Agency (EPA)7, have developed comprehensive state
energy planning frameworks. The National Association of State Energy Offices (NASEO) has also published
material that provides guidance for statewide planning. 8 Each of these planning guides provided key
insights into how to develop comprehensive, adaptable and strategic plans.
7 Environmental Protection Agency. “Energy and Environment Guide to Action: State Policies and Best Practices for Advancing
Energy Efficiency, Renewable Energy, and Combined Heat and Power.” 2015 Edition.
https://www.epa.gov/sites/production/files/2015-08/documents/guide_action_full.pdf
8 National Association of State Energy Officials. “State Energy Planning Guidelines: A Guide to Develop a Comprehensive State
Energy Plan Plus Supplemental Policy and Program Options.”
https://www.naseo.org/data/sites/1/documents/publications/NASEO-State-Energy-Planning-Guidelines.pdf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 21
Other federal agencies provide resources for more local-level energy planning. In a study commissioned
by the Department of Energy (DOE)’s Office of Indian Energy, the National Renewable Energy Laboratory
(NREL) developed a valuable community-planning document specifically for Alaska.9
From these and other resources, AEA considered and, where appropriate, incorporated many suggestions
and lessons learned. The AkAES is an amalgamation of the best of these approaches, tailored for Alaska.
BEST IDEAS—INFRASTRUCTURE AND POLICY OPTIONS IDENTIFIED IN PREVIOUS ALASKA-SPECIFIC STUDIES
AEA assessed previous, relevant, Alaska-specific energy policy recommendations as one of the first steps
in its AkAES work. Over the past decade, a number of policy papers have been developed for specific
energy sectors. These provided an excellent foundation for AkAES analysis and recommendations.
Numerous reports have provided recommendations for changes to State energy policy. Policy papers by
the University of Alaska’s ISER 10, Commonwealth North11, the U.S. DOE Office of Indian Energy 12, the
Alaska Arctic Policy Commission13, and the Walker/Mallot Consumer Energy Transition Team14 served as
a baseline in assessing what has been deemed important by others.
Within the past decade, AEA published two studies that looked at infrastructure options across the state:
the 2009 “Alaska Energy: A first step toward energy independence15 and the 2010 “Energy Pathway.”16
These had a different purpose than the AkAES and were developed under a very different fiscal climate.
The two studies aimed to assist communities in identifying projects to access the new source of project
funding and counter the high costs of energy. Neither specifically addressed needed policy change, but
they did provide significant, useful information about Alaska’s energy systems that contributed to the
development of AkAES findings and recommendations.
“Alaska Energy” provides an excellent history of Alaska’s State energy policy, a review that was not
repeated in this document. The “Energy Pathway” provided actions for energy efficiency, renewable
energy, climate change, energy security, economic development, investing in innovation, and education
and workforce development, many of which are included in this document.
9 A. Dane and L Doris. “Alaska Strategic Energy Plan and Planning Handbook.” 2013. National Renewable Energy Laboratory.
https://energy.gov/sites/prod/files/2014/05/f16/AKStrategicPlanningHandbook_v17.pdf
10 Steve Colt, Ginny Fay, Matt Berman, Sohrab Pathan. “Energy Policy Recommendations Draft Final Report.” January 25, 2013.
http://www.iser.uaa.alaska.edu/Publications/2013_01_25-EnergyPolicyRecommendations.pdf
11 Commonwealth North. “Energy for a Sustainable Alaska: The Rural Conundrum.” February 2012.
http://www.commonwealthnorth.org/download/Reports/2012_CWN%20Report%20-
%20Energy%20for%20a%20Sustainable%20Alaska%20-%20The%20Rural%20Conundrum.pdf
12 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
13 Alaska Arctic Policy Commission. “Final Report of the Alaska Arctic Policy Commission.” January 30, 2015.
http://www.akarctic.com/wp-content/uploads/2015/01/AAPC_final_report_lowres.pdf
14 Walker/Mallot Transition Team Conference. “Team Report”. Consumer Energy. November 21-24, 2014.
https://gov.alaska.gov/Walker_media/transition_page/combined-report_final.pdf
15 Alaska Energy Authority. “Alaska Energy: A first step toward energy independence.” January 2009.
http://www.akenergyauthority.org/Content/Publications/AKEnergyJan2009.pdf
16 Alaska Energy Authority. “Alaska Energy Pathway. Toward energy independence.” July 2010.
ftp://ftp.aidea.org/2010AlaskaEnergyPlan/2010%20Alaska%20Energy%20Plan/Narrative/Narrative%202010%20Energy%20Plan
.pdf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 22
Of all the potential ways to reduce the cost of energy in communities, energy efficiency has had the most
extensive review of policy recommendations. Reports commissioned by AEA and AHFC in 200817, 201118,
and 201219 provided an analysis of potential policies for reducing consumer energy costs for both heat
and electricity. An additional study commissioned by Cold Climate Housing Research Center (CCHRC)
focused on policy recommendations focused on electrical efficiency.20
Regional energy plans have recently been completed for all regions of the state. The first regional plan,
completed in 2010, was the Railbelt Integrated Resource Plan. The next regional study was the Southeast
IRP (SEIRP), completed in 2012.21 From 2012 to 2016 the remaining nine energy regions (as defined by
AEA) completed energy planning initiatives.22 Once the AkAES study was underway, data collection and
analysis being performed for regional energy plans were coordinated with work on the AkAES to the
greatest extent possible.
In developing the AkAES recommendations outlined in Chapter 7, AEA did not constrain itself to previously
proposed recommendations but used them as a starting point for further investigation.
BEST DATA—HOW TO EVALUATE POTENTIAL POLICY OPTIONS
To understand the potential benefits and risks of various energy policy options it is necessary to
understand the factors underlying retail energy prices. AEA scoured relevant literature on the components
of energy costs in Alaska. Studies performed by ISER over the past 15 years (especially in 200323, 200824,
200925, 201026) and the attorney general’s 2010 report investigating if the high cost of energy in rural
Alaska was the result of illegal conduct proved valuable.27
AEA tested previous recommendations from energy policy research and analysis (increased renewable
generation, for example) against updated community-level data where possible. This required that AEA
compile a robust set of data to better understand energy consumption, generation, resource availability,
17 Cady Lister, Brian Rogers, and Charles Ermer. “Alaska Energy Efficiency Program and Policy Recommendations.” June 5, 2008.
http://www.cchrc.org/sites/default/files/docs/EE_Final.pdf
18 John Davies, Nathaniel Mohatt, Cady Lister. “Alaska Energy Efficiency Policy and Programs Recommendations: Review and
Update.” June 27, 2011. http://www.cchrc.org/sites/default/files/docs/Interim_EE_Policy_Report.pdf
19 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
20 Information Insights, Inc. “Electric Energy Efficiency, Environmental Scan: Barriers & Opportunities” October 7, 2011.
http://www.cchrc.org/sites/default/files/docs/Electric_EE_Environmental_Scan_Lit_Review.pdf
21 Black and Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
http://www.akenergyauthority.org/Content/Publications/SEIRP/SEIRP-Vol1-ExecSumm.pdf
22 http://www.akenergyauthority.org/Policy/RegionalPlanning
23 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
24 Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. Components of Delivered Fuel Prices in Alaska. June
2008. http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
25 Ginny Fay, Ben Saylor, Nick Szymoniak, Meghan Wilson and Steve Colt. Study of the Components of Delivered Fuel Costs in
Alaska: January 2009 Update. January 2009. http://www.iser.uaa.alaska.edu/Publications/fuelpricedeliveredupdate.pdf
26 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
27 Alaska Attorney General’s Office. “Rural Fuel Pricing in Alaska: A Supplement to the 2008 Attorney General’s Gasoline Price
Investigation.” 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 23
population, costs, and other relevant factors. Hundreds of previous studies, datasets, resource and
technology reports, and program evaluations provided the foundation for this analysis.
Modeling the effectiveness of various energy infrastructure opportunities required the creation of a new
community-scale energy model. The Alaska Affordable Energy Model was built off work from AEA’s energy
models from the 2009 “Alaska Energy – A first step toward energy independence” and the 2010 “Alaska
Energy Pathway,” ISER’s Village End Use Model28, AHFC’s 2014 Housing Assessment29, AEA’s Renewable
Energy Fund (REF) economic model30, and others. AEA maintained most of the assumptions from the REF
model, including the diesel fuel price forecast updated in 2016.
Previous work by AEA, University of Alaska researchers, AHFC, and other state agencies, was used to
populate the AAEM with data. Databases such as the AEA-funded, ISER-maintained Alaska Energy Data
Gateway (AEDG)31 , AHFC’s Alaska Retrofit Information System (ARIS)32 , and the Alaska Energy Data
inventory (AEDI)33 proved invaluable for providing Alaska-specific energy costs, generation and
consumption data.
Federal data sources, such as the American Community Survey (ACS), U.S. Decennial Census and the
Energy Information Administration (EIA), provided data not collected by the State of Alaska. Alaska’s
Department of Labor and Workforce Development was also an excellent source of population estimates
and certain types of housing data.34
Hundreds of studies assessing the merits of individual infrastructure projects have been conducted across
the state, some going back decades. AEA compiled these results from numerous sources, including the
REF, AEA’s 2012 Rural Power House Inventory, 2015 Bulk Fuel Upgrade Inventory, and numerous other
state and federal sources. Preliminary results from over 400 reconnaissance-level hydro studies were
available through a 2014 US Army Corps of Engineers (USACE) compilation of Alaska’s potential hydro
resources.35 Non-project specific resource data was available through AEDI, including the NREL Alaska
wind map and woody biomass data layers, and solar resource estimates were collected through NREL’s
PVWatts online application.36
Numerous state and federal agencies have studied the feasibility of specific technologies in Alaska,
including the parameters needed for optimal performance. Specific reports, too numerous to include here
28 Steve Colt and Tobias Schwoerer. “Alaska Village Energy Model.” 2013. http://www.iser.uaa.alaska.edu/Publications/2013-
07_Village_energy_model_notes.pdf
29 Alaska Housing Finance Corporation. “2014 Alaska Housing Assessment.” https://www.ahfc.us/efficiency/research-
information-center/housing-assessment/
30 http://www.akenergyauthority.org/Programs/RenewableEnergyFund
31 https://akenergygateway.alaska.edu/
32 ARIS is not a publicly available database
33 http://www.akenergyinventory.org/
34 Department of Labor and Workforce Development Research and Analysis. Alaska Local and Regional Information.
http://live.laborstats.alaska.gov/alari/
35 Individual hydroelectric reconnaissance and feasibility reports are accessible through http://www.akenergyinventory.org/
36 National Renewable Energy Laboratory. PVWatts Calculator. http://pvwatts.nrel.gov/
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 24
but accessible through the AAEM, used in the AkAES analysis include work by ACEP, CCHRC, NREL, U.S.
DOE and USACE.
Evaluations of the REF 37, Weatherization 38 and Home Energy Rebate 39 programs were included in the
analysis for AkAES.
Alaska-specific building-level data was obtained from a number of sources. AHFC’s ARIS database includes
data from energy audits of thousands of residential buildings statewide, as well as both modeled and
reported information for over 1,000 non-residential buildings. AEA supplemented the non-residential data
from ARIS with sources that included AEA’s 2012 End Use study40, Alaska Native Tribal Health Consortium
(ANTHC) energy audits, community property tax rolls and regional energy plans.
Water and wastewater data and research for consumption, savings, and utility best practices was
collected from ANTHC41 and the Alaska Rural Utility Collaborative (ARUC).42
AEA gathered additional data from unpublished sources, including working documents from AEA
programs and reports to the Legislature from multiple State agencies.
Money is needed to bring most projects to life. Grants and loans, primarily from State and federal sources,
have been a primary source of financing for energy projects in the AkAES study area. Where it was
possible, AEA collected historical data on funding directly from state and federal agencies.
For financing future projects, the best catalog of Alaska-specific financing opportunities was compiled by
the National Renewable Energy Laboratory in 2013.43
To understand better the finances and non-fuel costs of PCE-eligible utilities, AEA worked with the
Regulatory Commission of Alaska (RCA) to obtain relevant data from utility submittals. Additional data on
community creditworthiness was gathered through AEA’s Bulk Fuel Loan program (2000-2013).
For all data sources that are not proprietary or otherwise confidential, AEA has endeavored to make the
access easier and have developed a tool (the Alaska Affordable Energy Model) to provide integrated
analysis.
37 David Hill, Chris Badger, Leslie Badger, Nikki Clace, and Molly Taylor. “Alaska Energy Authority: Renewable Energy Grant
Recommendation Program Impact Evaluation Report.” 2012. https://www.veic.org/resource-library/alaska-energy-authority-
renewable-energy-grant-recommendation-program-process-and-impact-evaluation-reports
38 Cold Climate Housing Research Center. “Weatherization Assistance Program Outcomes.” August 6, 2012.
http://www.cchrc.org/sites/default/files/docs/WX_final.pdf
39 Kathryn Dodge, Nathan Wiltse, Virginia Valentine. “Home Energy Rebate Program Outcomes.” June 26, 2012.
http://www.cchrc.org/docs/reports/HERP_final.pdf
40 Alaska Energy Authority. “End Use Study: 2012” April 30, 2012.
http://www.akenergyauthority.org/Content/Efficiency/EndUse/Documents/AlaskaEndUseStudy2012.pdf
41 Daniel Reitz, Art Ronimus, Carl Remley, Emily Black. “Energy Use and Costs for Operating Sanitation Facilities in Rural Alaska:
A survey.” October 2011.
42 Alaska Rural Utility Collaborative. “2014 Report on Activities.” https://anthc.org/wp-content/uploads/2015/12/2014-ARUC-
Report-on-Activities-v2_02.09.15_email.pdf
43 K. Ardani, D. Hillman, and S. Busche. National Renewable Energy Laboratory. “Financing Opportunities for Renewable Energy
Development in Alaska.” April 2013. http://www.nrel.gov/docs/fy13osti/57491.pdf
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 25
A complete list of data sources is available in the References section at the end of the report. Individual
data sources are cited as footnotes throughout the report.
NEW RESEARCH PERFORMED
To fill knowledge gaps, AEA contracted with academics, private-sector consultants and federal entities to
answer specific technology, program or policy questions through additional data collection and analysis.
The deliverables from these discreet research and analysis projects were used to inform the final
recommendations and are included in the supplemental material, available through AEA’s website
(http://www.akenergyauthority.org/).
Table 1: Contracted deliverables that informed the AkAES
Report or deliverable title Report Author(s)
Alaska Affordable Energy Model Developed by AEA, coded by UAF Geographic
Information Network of Alaska (GINA)
Energy efficiency program evaluation and
financing needs assessment
Vermont Energy Investment Corporation; Cold
Climate Housing Research Center
LNG feasibility for AkAES communities Northern Economics; Michael Baker International
Rural utility financial analysis UAA Center for Economic Development
Documentation of Alaska-specific technology
development needs in support of the AkAES
UAF Alaska Center for Energy & Power
Barriers and opportunities for private
investment in rural Alaska energy projects
UAF Alaska Center for Energy & Power
Fuel transportation improvement report US Army Corps of Engineers, Alaska District
Demographic modeling UAA Institute of Social & Economic Research
Sustainable utilities study updates, utility
structure analysis, and subsidy program analysis
UAA Institute of Social & Economic Research, Mark
Foster & Associates
Energy costs and rural Alaska out-migration UAA Institute of Social & Economic Research
AEA also tapped its internal knowledge and expertise to perform additional primary and secondary
research in support of the project. The results of numerous research studies performed by AEA staff are
incorporated into this report.
HOW TO READ THE REPORT
The remainder of this report is structured under three broad themes:
Chapters 2 and 3 describe how and why energy is less affordable in some areas of the state.
Chapter 2 describes baseline energy costs and consumption in communities across the AkAES study
area. Socioeconomic characteristics, including population trends and other factors that affect
communities’ ability to pay for infrastructure, are also discussed. Estimates for investment needed to
February 2017 CHAPTER 1: Overview of the Alaska Affordable Energy Strategy Page | 26
maintain the current state of energy systems in communities over next 20 years is provided in this
chapter.
Chapter 3 investigates the factors that drive the cost of energy in communities—for both electricity
and heat. The chapter follows the supply chain from crude oil to consumption to understand which
factors have the most sway over the total cost consumers pay for energy.
Chapters 4, 5 and 6 describe and analyze factors that could help bring affordable energy to Alaska
communities.
Chapter 4 explores the risks and barriers to project development, categorized by technology and
phase. By planning for and mitigating these risks, communities’ and the State’s return on investment
(ROI) can be increased.
Chapter 5 provides an overview and brief analysis of current and historical state energy programs to
understand what has been effective to date in bringing affordable energy to communities.
Chapter 6 expands on the cost drivers in Chapter 3 to delve into infrastructure and non-infrastructure
opportunities for reducing community energy costs.
Chapter 7 builds on the results of all previous chapters to propose a framework for statutory, regulatory
and policy changes to bring more affordable energy to Alaska communities.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 27
CHAPTER 2: CURRENT CONDITIONS OF THE AKAES STUDY AREA
Alaska is an incredibly diverse state culturally, geographically, and economically. Each community and
region has its own unique set of needs and opportunities. This great variability does not allow for a one-
size-fits-all approach to energy solutions in Alaska. Chapter 2 outlines energy and demographic conditions
within the AkAES study area.
To influence energy costs conditions as they currently are, it must first be adequately understood: What
energy sources have people chosen? How much energy do different sectors of the economy consume?
How much does energy cost per unit? Answers to these and other questions provide a baseline of
information that the State and communities can use to test different ways of improving the situation.
In addition to information about energy, it is also important to understand community and regional
demographics within the AkAES study area. Given the sheer number of communities within the study
area, all analysis will be presented on the regional level in this report. Community-level data is available
through the Alaska Affordable Energy Model (AAEM).44
AEA found that community population is generally the most important factor for estimating energy
consumption. It is important, then, to forecast, using best available data and current trends, what
communities might look like in the future.
Economic conditions in AkAES study area communities and regions are also investigated in this chapter.
Outside of the Railbelt, Alaska’s economic data is less reliable, which makes understanding complicated
community issues such as access to non-grant financing difficult.
44 The AAEM is accessible through AEA’s website www.akenergyauthority.org
Key Takeaways
1. The median community size in the AkAES study area is about 300 people.
2. The wide variety of conditions across the state preclude any one-size-fits-all solution to delivery
of affordable energy.
3. Heating buildings is approximately two-thirds of consumers’ energy cost.
4. The cost of doing nothing new – the average annual capital cost of current energy infrastructure
under the existing policy and regulatory framework in communities with populations less than
2,000 – is estimated to be more than $30M per year.
5. There is a wide range of communities’ and utilities’ ability to pay for needed energy projects. The
differences in the tax and economic bases are widely dissimilar across the state.
6. Access to non-grant financing requires proper financial management, excluding some
communities from being able to access project financing.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 28
POPULATION
The AkAES region, home to approximately 165,000 people, encompasses approximately one-quarter of
Alaska’s population. Except for Juneau, all of the 240 communities within the study area have populations
less than 10,000.
Figure 3: Total population by AEA energy region45
The AEA-defined energy regions are similar in population size, except for the Lower Yukon-Kuskokwim
and Southeast regions, as seen in Figure 3. Throughout the report, information will be presented in a
number of ways: in some cases, the data will be normalized by population or some other factor, but in
other cases it will be summarized as totals. It will be important to recognize that the much larger
populations of Southeast and the Lower Yukon-Kuskokwim will inevitably make those two regions more
prominent—Southeast is nearly seven times larger in population and the Lower Yukon-Kuskokwim is
almost three times larger in population than the other regions.
It is important to understand the diversity of community sizes within any given region and tailor energy
affordability assistance to each specific community’s needs.
45 Alaska Dept. of Labor and Workforce Development population. Accessed through Alaska Energy Data Gateway.
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Total population by AEA energy region
Source: Dept. of Labor and Workforce Development (2014)
Juneau
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 29
Figure 4: Range of community populations by AEA energy region46
The median population of communities in almost all regions is less than 300 people, as depicted in Figure
4 (Juneau has been removed from the chart so as not to skew the chart). In each region there is at least
one large town over 1,000 people, the so-called regional hub. Most regional hubs have more than 2,000
people. The relatively small size of the largest community in the Yukon-Koyukuk/Upper Tanana region
might indicate that Fairbanks effectively acts as the regional hub, which is why the maximum community
size in the Yukon-Koyukuk/Upper Tanana is only 1,200 people.
Community size is particularly important when considering the value of economies of scale. While the
majority of people live in communities greater than 1,200, the vast majority of towns ar e less than 300
people. As seen in Table 2, the smallest communities constitute about 60% of the communities in the
AkAES study area but only 10% of the total population, and communities with populations greater than
1,200 make up 8% of the communities but 62% of the total study area population. I t is just as important
for the State to effectively assist the many small communities as it is to assist the fewer larger
communities, and each of these communities has unique needs.
46 AEA analysis of ISER demographic projection (2016)
0 2,500 5,000 7,500 10,000
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Range of community populations by AEA energy region
Source: ISER Demographic Model (2016)
Second quartile Third quartile
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 30
Table 2: Distribution of population by community size47
Range of population
Number of
communities
Percent of
communities
Total
population
Percent of
population
Less than 300 137 60% 16,401 10%
Between 300 & 1,200 83 32% 47,577 28%
Greater than 1,200 20 8% 103,381 62%
AkAES total 240 167,359
There are occasional inconsistencies in the number of communities included throughout this report. This
is generally due to how various government agencies define “community;” some areas that might be
considered “subdivisions” or “suburbs” of a larger town by one agency may or may not be included as a
different place name by other agencies.
POPULATION CHANGE
The amount of population change–both long-term net changes and yearly turnover–can have important
impacts on energy programs. As mentioned before, long-term population trends will greatly influence the
amount of energy consumed in communities. The annual movement of people into and out of
communities may also have important impacts on energy systems . Small changes in the community
population could have major consequences, depending on who moves. If the community energy
champion, who is a key part of any successful community energy project, moves out of the community,
that movement will have an outsized impact on the community.
Except for a few isolated areas where energy-intensive industry exists (e.g. fish processing), population
changes are the main predictor of future community energy load. This is most true in the residential
sector, if we assume that the number of people per household remains constant through changes in
community population.
Over the past 25 years, each energy region has experienced unique population trends. Population growth
in communities and regions has occurred irregularly, with populations growing in some communities
within a region and shrinking in other communities within the same region. Regional changes are not
always good predictors for the population change for communities within that region. Since 1990, as a
whole, Alaska has grown at a rate of 1.1% per year, with most of that growth taking place in the Cook Inlet
region. Among the AkAES study area regions, only the North Slope region has surpassed the statewide
average annual population growth.
47 AEA analysis of ISER demographic projection (2016)
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 31
Figure 5: Regional average yearly population growth rates by AEA energy region48
Gross population changes hide high inmigration and outmigration on a yearly basis. Through Permanent
Fund Dividend applications, the state is able to track how people move around the state. This dataset for
the change between 2013 and 2014, in Figure 6, presents a clearer example of mobility as it removes the
births and deaths from population change. While the migration shown in Figure 6 looks significant, it is
not notably different from national averages. For example, between 2014-15, the U.S. Census estimated
that 12% of Americans moved both within and between counties.49
Intraregional differences in population change are also hidden by the regional averages. Some
communities have had rapid population growth and others have shrunk and disappeared.
48 AEA analysis of U.S. Census and Alaska Department of Labor and Workforce Development data
49 U.S. Census. Table 1. General mobility, by race and Hispanic origin, region, sex, age, relationship to householder, educational
attainment, marital status, nativity, tenure, and poverty status: 2014 to 2015.
http://www.census.gov/data/tables/2015/demo/geographic-mobility/cps-2015.html
-1.0%-0.5%0.0%0.5%1.0%1.5%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Regional average yearly population growth rates by AEA energy region
Sources: US Census and ADOL&WD 1990-2014
Average
Statewide
Growth: 1.1%
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 32
Figure 6: Outmigration and inmigration by AEA energy regions50
Between 2013 and 2014, only the Bering Straits region had more people move into it than moved out.
The Lower Yukon-Kuskokwim was the least mobile region, both inbound and outbound, whereas the
Aleutians saw the most movement into and out of the region.
It has been suggested that high-energy costs are a primary motivating factor for people moving from
Alaska’s rural communities. Research has not been able to confirm this suggestion. Worldwide there is a
trend of people moving to urban areas. In Alaska, researchers have found that people are most likely t o
move from small communities to hub communities and then from hub communities to urban
communities.51 Two different studies performed by ISER over the past decade, using very different
methods, did not find a strong relationship between the cost of energy and migration patterns. 52,53 Other
considerations, such job opportunities, education, and safety, appear to be more important factors. It is
unlikely that delivering more affordable energy to communities will change the migration trends, as
complex factors influence individual decisions on where they live.
There is a perception that personnel turnover at rural utilities is high due to outmigration, but there are
unfortunately few data sources to confirm this perception. The list of participants in AEA’s training
programs suggests that is true with some exceptions. Of the approximately 1,000 participants, most had
only attended one course, but 52 had taken courses over at least a 5-year period, and 17 over a 10-year
50 AEA analysis of “Change in Borough or Census Area of Residence for Alaska Permanent Fund Dividend Applicants, 2013 to
2014” from Alaska Department of Labor and Workforce Development, Research and Analysis Section (2014).
http://live.laborstats.alaska.gov/pop/migration/PFDMigrationBCA.xls
51 E Lance Howe, Lee Huskey, and Matthew Berman. “Migration in Arctic Alaska: Empirical evidence of the stepping stones
hypothesis.” Migrat Stud (2014) 2 (1): 97-123.doi: 10.1093/migration/mnt017
52 Stephanie Martin, Mary Killorin, and Steve Colt, “Fuel Costs, Migration, and Community Viability”, May 2008.
http://www.iser.uaa.alaska.edu/Publications/Fuelcost_viability_final.pdf
53 Matt Berman and Eddie Hunsinger, “Energy Cost and Rural Alaska Out-migration.” 2016.
0%3%6%9%12%15%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Railbelt
Southeast
Yukon-Koyukuk/Upper Tanana
Outmigration and inmigration by AEA energy regions (2013-14)
Source: Alaska Dept. of Labor & Workforce Development
Inmigration Outmigration
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 33
period. AEA’s 2015 bulk fuel assessment, an evaluation of 56 communities that had been pre-identified
as being in the most need, showed that the 130 bulk fuel operators in those communities had an average
of 10 years of experience, but there was no indication of the length of tenure.54 It is likely that personnel
turnover is highly variable by community and utility.
ENERGY SOURCES, CONSUMPTION, AND COSTS ACROSS THE STUDY AREA
Before the cost of energy in communities can be influenced, it is important to understand the baseline.
What types of energy are consumed? How much is consumed? How much does it cost?
Since the information presented in this section is at the regional level, some of the variations within
regions will be muted. Some regions are composed of similar types of communities with very similar
conditions, while other regions have significant variability. Community-level data is not shown in this
report; instead, the community-level data has been aggregated on the regional level.
ENERGY SOURCES CONSUMED ACROSS THE AKAES STUDY AREA
The two primary uses of energy in communities, are for electricity and heat. Within regions there can be
significant differences in the ratio between end-use heat and electricity consumption, as a number of
factors can impact energy consumption. Figure 7 shows the end-use consumption of energy for residential
and non-residential buildings in the AkAES study area. In cases where communities also use electricity for
heat, it is included in the “electricity” column. This chart represents “site energy,” that is energy consumed
on site, instead of “source energy,” which also includes the fuel needed to produce the energy—as in the
case of electricity produced by diesel-fired generators.
Figure 7: End-use energy consumption by AEA energy region55
54 Unpublished AEA data
55 AEA analysis of Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000
Kodiak
Aleutians
Northwest Arctic
Bristol Bay
Bering Straits
Yukon-Koyukuk/Upper Tanana
Copper River/Chugach
Lower Yukon-Kuskokwim
North Slope
Southeast
MMBtu consumed per region
End-use energy consumption by AEA energy region
Source: Alaska Affordable Energy Model
Electricity (MMBtu)Heat (MMBtu)
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 34
The Southeast region consumes significantly more energy for electricity and heat than any other region,
primarily due to that region’s much larger population. In all regions within the AkAES study area, heat is
the main end-use energy need in terms of units of energy. As a percentage of end-use consumption,
electricity ranges from about 10% in the North Slope to over 20% in the Southeast and Kodiak regions. It
should be noted that the energy needed to produce electricity is not factored into Figure 7.
AKAES STUDY AREA DIESEL CONSUMPTION
Based on estimates from the Alaska Affordable Energy Model, approximately 120 million gallons of
diesel and heating oil are consumed within all AkAES regions together. Figure 8 illustrates how these
gallons are consumed by the different regions. This figure includes the “source energy” for diesel-fired
generation.
Figure 8: Gallons of diesel and heating oil consumed by AEA energy region56
With the exception of Kodiak, the Southeast region consumes the least amount of diesel for electric
generation despite its large population and higher per capita electricity consumption; both Kodiak and
Southeast have large, mature hydro projects that provide the majority of power in the more populated
communities Diesel consumption in the North Slope region is unexpectedly small because of access to
locally supplied natural gas in Barrow and Nuiqsut. In general, diesel for electricity is about one-third of
the diesel and/or heating oil consumed in any given community. All regions rely heavily on heating oil for
both residential and non-residential heat.
ELECTRICITY IN THE AKAES STUDY AREA
Of all the energy data available in Alaska, electricity is the most reliable. Almost all communities have a
certificated utility, and the utilities are required to report generation and sales figures to AEA, the
56 AEA analysis of Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
0 10,000,000 20,000,000 30,000,000 40,000,000
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak Region
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Gallons of diesel/heating oil consumed per year
Gallons of diesel and heating oil consumed by AEA energy region
Source: Alaska Affordable Energy Model
Utility diesel Residential heating oil Non-residential heating oil
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 35
Regulatory Commission of Alaska (RCA), and/or the federal Energy Information Authority (EIA). Electricity
is charged by the unit, and sales are easily measured for billing purposes.
Figure 9 shows the large regional and intra-regional differences for how electricity is generated.
Figure 9: Energy source for electricity by AEA energy region57
Energy sources for electricity generation within the AkAES study area vary considerably. Outside the
Railbelt region, natural gas is used to generate electricity in only two communities – North Slope’s Barrow
and Nuiqsut. Regional electricity production totals hide variation at the local level — Southeast in
particular shows nearly 100% hydropower, which is true in Juneau, Ketchikan, Metlakatla, Wrangell, Sitka,
and Petersburg. However, some of the other smaller, isolated communities rely solely on diesel. Southeast
and Kodiak generate more than 90% of their electricity through renewable energy sources, whereas the
Aleutians, Bering Straits, Bristol Bay, Lower Yukon-Kuskokwim, and Yukon-Koyukuk/Upper Tanana regions
are almost entirely reliant on diesel for power generation.
A relatively small but increasing amount of wind power is generated in the Bering Straits, Lower Yukon -
Kuskokwim, and Northwest Arctic regions. Bristol Bay and Aleutians regions have developed some hydro
resources. As we will see in Chapter 6, there are still a number of cost-effective renewable energy options
that can be capitalized on using available technology. Future changes in technology costs and/or
performance may increase the range of where renewable resources are economically viable.
The amount of hydro and wind generation is expected to increase as more projects funded through the
Renewable Energy Fund (REF) come online.
57 AEA analysis of Alaska Energy Statistics (2012). Accessible from: http://www.akenergyauthority.org/Publications
0%25%50%75%100%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Energy source for electricity by AEA energy region
Source: Alaska Energy Statistics (2013)
Oil Natural gas Hydro Wind Other
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 36
HEAT SOURCES IN AKAES STUDY AREA
Mostly due to Alaska’s cold climate, heating accounts for the largest percentage of energy consumption
for consumers across all AkAES study area regions. Except for two natural gas utilities on the North Slope,
Barrow and Nuiqsut, heating fuels are supplied by an unregulated local heating oil company. Because of
this, the volumes and types of heating fuels consumed are not known with the sa me precision as is
electricity consumption. The most reliable and widespread data source for residential heating information
was through the American Community Survey (ACS), a product of the U.S. Census that is updated on a
rolling five-year schedule. Figure 10 compiles the data from the ACS by AEA energy region and shows the
diverse range of sources used to heat homes in Alaska. Throughout the following figures, the Railbelt is
included as a means of comparison.
Figure 10: Primary source of residential heat by AEA energy region58
The first thing to note is the apparent statistical aberrations: utility gas (natural gas) is not available outside
of the Railbelt and the North Slope, but we have not removed this data. A number of the other categories
less than 2% were aggregated as “other”, including coal, solar, and other.
In the regions that have access to natural gas, nearly all customers who have access choose to connect to
the utility. In the other regions there is a mix of fuel used. In areas with forests—Yukon-Kuskokwim/Upper
Tanana and Copper River, in particular—there is a significant amount of firewood used to heat homes.
Except for the relatively high penetration of electric heat (almost 20%) in Southeast, the vast majority o f
residential heat throughout the AkAES study area is supplied by fuel oil. Without a significant reason to
change these choices, AEA assumes that this regional residential heat profile will remain the same into
the future.
58 United States Census Bureau. “B25040: House Heating Fuel [10]”. 2008-13 U.S. Census Bureau’s American Community Survey
Office, 2013. January 2015 <http://ftp2.census.gov/>.
0%25%50%75%100%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Railbelt
Southeast
Yukon-Koyukuk/Upper Tanana
Primary source of residential heat by AEA energy region
Source: American Community Survey (2013)
Utility gas Propane Electricity Fuel oil Wood Other
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 37
Fuel oil is also the fuel of choice for non-residential buildings. Of the nearly 6,000 non-residential buildings
identified in the AkAES study area (out of approximately 10,000 total assumed buildings), very few use an
alternative to fuel oil for heat. An unknown but potentially sizable number of non-residential buildings in
Southeast communities with low-cost hydropower use electric resistance heating.59 Sixty non-residential
buildings and five water and wastewater systems currently use biomass as heat. Sixty-one buildings have
been identified as utilizing heat recovered from diesel generators. A small number of buildings use heat
from excess electricity generated by wind or hydro as secondary loads.
HOW COMMUNITIES CONSUME ENERGY
This section offers more detailed information on how energy is consumed in the regions.
PER CAPITA DIFFERENCES IN CONSUMPTION BASED ON THE SIZE OF COMMUNITY
While regional differences in how energy is consumed exist, there are also strong differences in energy
consumption and costs based on the size of the community. In general, smaller communities have fewer
types and smaller buildings than larger communities. Based on the available data, almost all communities
have a core set of buildings—a school, clinic, warehouse, store, municipal or tribal facility, community
hall—and these buildings do not necessarily get smaller at the same rate as the population. These factors
lead to greater per capita non-residential energy consumption in the smallest communities.
Figure 11: Per capita consumption in MMBtu/year by community size60
The largest communities, defined here as those with populations of more than 1,200, have the highest
per capita consumption of energy. The largest communities had the highest per capita consumption in all
categories, except for water/wastewater heat and electricity. The largest communities generally serve as
59 Black & Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
http://www.akenergyauthority.org/Content/Publications/SEIRP/SEIRP-Vol1-ExecSumm.pdf
60 AEA analysis of results from Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
-
40
80
120
160
<300 >300,<1200 >1200MMBtu consumed per capita per yearPopulation of community
Per capita energy consumption by community size
Source: Affordable Energy Model
Water/wastewater electricity
Water/wastewater heat
Non-residential electricity
Non-residential heat
Residential electricity
Residential heat
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 38
hubs for the medium-sized and smallest communities within their region, with the additional services and
facilities that this would require. It is surprising that the medium-size communities, defined as having a
population between 300 and 1,200, have the lowest per capita consumption, but this may be due to a
limited amount of economy of scale relative to the smallest communities. These communities have more
people to stretch the basic services seen in almost all communities—schools, public safety, public
assembly etc.—but not so much of an expanded economy as to have the ancillary businesses and services
of the larger communities.
Figure 12: Per capita energy cost by size of community61
Figure 12 shows a strikingly different picture from Figure 11. Displaying energy costs per person by
community size illustrates a distinct upwards trend as communities decrease in size—the total per-capita
cost in the smallest communities are nearly twice as much as the largest category of communities in the
AkAES study area. Figure 12 does not include subsidies, such as Power Cost Equalization (PCE) or the
federal Low-income Heating Assistance Program (LIHEAP) or the State Alaska Heating Assistance Program
(AKHAP).
Water/wastewater energy use becomes a larger share of the consumption and cost as a community
decreases in size. A baseline amount of energy is needed to run these systems regardless of the number
of customers, and the incremental increase for each additional person is relatively small.
The per capita cost of electricity—residential, non-residential, and water/wastewater—has the largest
difference across the community sizes. Small communities generally have a minimum number and size of
buildings — public safety, education, store, etc. — that get spread out over fewer people in smaller
communities.
61 AEA analysis of results from Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
$-
$2,000
$4,000
$6,000
$8,000
<300 >300,<1200 >1200Per capita energy costCommunity population
Per capita energy cost by size of community
Source: Affordable Energy Model
Water/wastewater electricity
Water/wastewater heat
Non-residential electricity
Non-residential heat
Residential electricity
Residential heat
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 39
CONSUMPTION OF ELECTRICITY
As mentioned before, electricity generation and sales are reported to state and federal agencies. The data
aggregated and analyzed in this report generally maintain a distinction between the residential and non-
residential sectors. Depending on the community, the non-residential sector can include a number of
subsectors, e.g., industry, government, public facilities, and commercial, but such granular detail is not
always available for all communities. Figure 13 shows the average annual per capita consumption by
region in megawatt-hours (MWhs); each MWh is equal to 1,000 kilowatt-hours (kWh).
Figure 13: Regional average per capita electricity consumption for residential and non-residential customers62
There is a huge difference in average per capita electricity consumption between regions. Annual use in
the residential sector ranges from just over one MWh per capita, as in the Aleutians, to more than five
MWh per capita, as in Kodiak. The residential sector in some regions, such as Kodiak, Southeast, and the
Railbelt, consumes more or nearly as much as all sectors combined in other regions, such as Lower Yukon-
Kuskokwim and Northwest Arctic. Factors likely contributing to these regional differences include the
number of people per household, the economic prosperity of the region, and the price of electricity.
Although there are likely a number of contributing factors, including, but not limited to the uni t price of
electricity, there is a clear trend, Table 3 shows that residential customers consume less electricity when
the unit price is higher.
62 Alaska Energy Statistics, 2013. Accessible from: http://www.akenergyauthority.org/Publications
0 5 10 15 20 25
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Railbelt
Southeast
Yukon-Koyukuk/Upper Tanana
MWh per person per year
Regional average per capita electricity consumption for residential and non-
residential customers
Source: Alaska Energy Statistics (2013)
Per capita residential sales Per capita non-residential sales
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 40
Table 3: Mean consumption per residential customer per month in PCE communities63
Effective rate
kWh per customer
per month
Average cost per
month
Less than $0.19 453 $ 86.07
$0.20-0.29 395 $98.75
$0.30-0.39 304 $106.40
$0.40-0.49 304 $136.80
$0.5-0.59 178 $97.90
More than $0.60 212 $137.80
Table 3 also shows that the effective rate consumers pay, after including PCE payments, is closely
correlated with the amount of electricity consumed. The average amount spent per month is relatively
consistent across each of the rate groups, at approximately $110/month, plus or minus about $20. This
value does not include the seasonality of consumption, as in winter PCE covers 65% to 83% of residential
consumption (this figure is 70% to 94% in summer).64 Other factors, such as the size of housing and the
economic condition of the community, also contribute to this trend. If all communities charge cost-based
rates and are able to provide documentation for utility costs, the effective rate in all communities would
be nearly equal and near the PCE base rate. Thus, the higher effective rate might be indicative of other
community attributes that could also affect consumption. Table 3 could indicate that a reduction in a
community’s electric rate might increase consumption, an effect referred to as rebound.65
The amount of non-residential consumption is an indicator of the amount and type of industries in a
region. More energy-intensive industries, at least on a per capita basis, such as fish processing in the
Aleutians, Copper River/Chugach, and Kodiak or the oil transportation industry in the Copper
River/Chugach region, have much more non-residential energy consumption than less developed areas.
The data in Figure 13 actually underestimates the consumption in some regions, particularly the Aleutians,
since a number of industries, such as fish processors, self-generate. The high cost of running an electric
utility makes it relatively less expensive for some consumers to generate their own power, which is termed
bypass risk.66 Additionally, in some communities the local schools also self-generate.
The differences in regional and community industrial activity are a factor that influences the consumption
of electricity in communities. The community population is another factor that influences electricity
63 Alaska Energy Statistics, 2013. Accessible from: http://www.akenergyauthority.org/Publications
64 Alaska Energy Statistics, 2013. Accessible from: http://www.akenergyauthority.org/Publications
65 Jesse Jenkins, Ted Nordhaus, and Michael Shellenberger. “Energy Emergence: Rebound & Backfire as Emergent Phenomena.”
February 2011. http://thebreakthrough.org/blog/Energy_Emergence.pdf
66 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 41
consumption. As seen in Table 4, the average contribution of each building type changes with the size of
the community, but is most noticeable in the education sector.
Table 4: Percentage of non-residential electricity consumption by building type67
Building Type <300
Between
300 & 1200 >1200
Education 25% 26% 10%
Office 8% 5% 5%
Public Assembly 5% 4% 5%
Accommodation Services 5% 3% 1%
Warehousing 5% 4% 1%
Health Care - Hospitals 4% 2% 4%
All other 49% 55% 76%
The education sector is the largest known consumer of electricity in study-area communities; however,
the contribution decreases in the largest communities as a more diverse economy increases the
contribution from other sectors. Offices, public assembly, accommodation services, clinic/hospitals, and
warehouses are responsible for the second tier of known consumer electricity consumption in the AkAES
study area. Data such as this will help communities and the State target particular sectors that will most
benefit from efficiency.
HEAT CONSUMPTION
As mentioned before, outside of the natural gas service areas, information about the amount of energy
consumed to heat the built environment is not collected by any state or federal agencies, so the data for
heating fuels has been modeled. The description of the method used to develop modeled estimates in
this section is explained in depth in the supplemental material.68 Chapter 3 will explore the factors
influencing consumption in greater depth.
RESIDENTIAL HEATING
While it might not always be the largest sector for heating fuels consumption in a community, residential
heating is what impacts individual Alaskans most directly. Numerous studies have shown that heating is
the largest energy cost for most households, and this is also indicated in the AAEM. Outside of the
communities with natural gas, which can be easily measured for sales, the consumption of most heating
fuels is not directly measured.
67 AEA analysis of results from Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
68 http://www.akenergyauthority.org/Policy-Planning/AlaskaAffordableEnergyStrategy
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 42
Figure 14: Average gallons of heating oil equivalent consumed per household69
In order to have a common unit to discuss the thermal load of residences, Figure 14 shows all energy
sources (wood, natural gas, etc.) in the equivalent number of gallons of heating oil. For example, even
though the Yukon-Koyukuk/Upper Tanana region has a high percentage of wood consumption, the energy
in wood is shown here as an equivalent gallons of heating oil. The values presented above are based on
AHFC data from over 17,000 audits of houses in the AkAES region. It may be surprising that some of the
colder parts of the state, such as the Lower Yukon-Kuskokwim and Bering Straits, are in the lower end of
heat energy consumption. As we will see in Chapter 3, multiple factors influence consumption, and the
climate is just one of the drivers.
NON-RESIDENTIAL HEATING
Just like electricity consumption, the impact of non-residential heat consumption is not generally felt
directly by residences. Instead it is indirectly paid for in more expensive goods and services, reduced
government services, constrained choices, and higher water and sewer rates.
Table 5: Percent of total non-residential heating fuel consumption by community size70
Building Type <300
Between
300 & 1200 >1200
Education 28% 33% 13%
Office 8% 5% 6%
Public Assembly 7% 5% 3%
Accommodation Services 3% 2% 1%
Warehousing 6% 5% 2%
Health Care - Hospitals 3% 2% 2%
All other 45% 48% 73%
69 AEA data analysis based on records in Alaska Retrofit Information System (2015)
70 AEA analysis of results from Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
- 500 1,000 1,500 2,000
Lower Yukon-Kuskokwim
Aleutians
Bristol Bay
Kodiak
Bering Straits
Southeast
Northwest Arctic
North Slope
Yukon-Koyukuk/Upper Tanana
Copper River/Chugach
Railbelt
Gallons of heating oil equivalent
Average gallons heating oil equivalent consumed per household
Source: AEA analysis of AHFC HERP, Weatherization, and BEES
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 43
As a whole, the results shown in Table 5 are similar to those seen in Table 4. Education is the largest
identified consumer of thermal energy, up to one-third of all non-residential heating oil consumption in
some communities.
RATES FOR ELECTRICITY AND HEAT
The total amount that people pay for energy is determined by the combination of the amount consumed
and the rates utilities charge. Knowing the rates is obviously an important part of evaluating the
opportunity for bringing more affordable energy to communities; Chapter 3 will delve into understanding
why the rates are what they are.
Rates undoubtedly influence how people consume energy, but we have little hard evidence to definitively
show or test this, particularly for heating fuels. There is likely less elasticity of demand for heating fuels
than for electricity, especially as heat load is controlled more by the quality of building design and
construction than personal choice, though some factor of demand will always be based on consumer
choices such as building size, interior temperature set points, leaving doors and windows open, etc.
Table 6 provides the most common units and their abbreviations, detailing how each will be used in this
report to represent regional energy sources. A common option for trying to reduce costs is to evaluate if
switching fuels will be effective. Since it can be difficult to understand how the value of a certain number
of kilowatt-hours (kWh) compares to gallons of heating oil, Table 6 provides a common reference between
each energy type and the equivalent unit price of heating oil. The table does not include the dif ferent
potential conversion efficiencies of each fuel type.
Table 6: Cost conversions for various energy sources
Fuel type
Heating
oil ($/gal)
Electricity
($/kWh)
Natural gas
($/Mcf)
Firewood
($/cord)
Pellets
($/ton)
Propane
($/gal)
Assumed
energy
density
0.138
MMBtu/
gal
0.003412
MMBtu/ kWh
1.028
MMBtu/Mcf
16 MMBtu/
cord
17.6
MMBtu/ton
0.0915 MMBtu/
gal
Equivalent
unit prices
$ 1.00 $ 0.02 $ 7.45 $ 116 $ 105 $ 0.66
$ 2.00 $ 0.05 $ 14.90 $ 232 $ 211 $ 1.33
$ 3.00 $ 0.07 $ 22.35 $ 348 $ 316 $ 1.99
$ 4.00 $ 0.10 $ 29.80 $ 464 $ 422 $ 2.65
$ 5.00 $ 0.12 $ 37.25 $ 580 $ 527 $ 3.32
$ 6.00 $ 0.15 $ 44.70 $ 696 $ 633 $ 3.98
$ 7.00 $ 0.17 $ 52.14 $ 812 $ 738 $ 4.64
$ 8.00 $ 0.20 $ 59.59 $ 928 $ 844 $ 5.30
$ 9.00 $ 0.22 $ 67.04 $ 1,043 $ 948 $ 5.97
$ 10.00 $ 0.25 $ 74.49 $ 1,159 $ 1,054 $ 6.63
Table 6 can be most readily understood by following any given price of heating oil horizontally to find the
equivalent unit cost for each of the other fuels. For example, for propane to be cost competitive with
heating oil when heating oil is $4.00 per gallon, propane must be less than $2.65 per gallon.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 44
ELECTRIC RATES
Electricity is the highest quality and most useful form of energy available —its versatility allows it to be
used for a wider array of uses than other energy sources. Because of its flexibility, electricity has become
a requirement for a modern American lifestyle and achieving operational efficiency for businesses.
To put the rates shown in Figure 15 in perspective, the average U.S. electricity rate is $0.12/kWh.71 While
especially high electricity rates may impede economic growth, reduce profits, and/or complicate
household financial choices, other highly industrialized countries have significantly higher rates than the
U.S. For example, the average electricity rate in Germany is $0.29/kWh72, and Germany has been able to
maintain one of the strongest manufacturing sectors in the world. This indicates that a complex
relationship between energy costs and economic development exists. The Railbelt is included for sake of
comparison.
Figure 15: Regional averages for residential and non-residential electricity rates before PCE reimbursement73
The similarities between the non-residential and residential rates show a combination of a lack of
discernable differentiation in pricing structures and lack of data. In particular, smaller utilities are less
likely to have separate rates for different sectors or to have tiered rates.74 On average, the rural regions
have electric rates four times higher than the Railbelt or larger communities in Southeast. Factors
71 Jess Jiang, “The Price of Electricity in Your State.” National Public Radio. October 28, 2011.
http://www.npr.org/sections/money/2011/10/27/141766341/the-price-of-electricity-in-your-state
72 Ellen Thalman, “What German households pay for power.” November 2, 2016.
https://www.cleanenergywire.org/factsheets/what-german-households-pay-power
73 Alaska Energy Statistics, 2013. Accessible from: http://www.akenergyauthority.org/Publications
74 Unpublished AEA analysis of PCE filings to RCA (2000-2014)
$- $0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70
North Slope
Railbelt
Southeast
Kodiak
Copper River/Chugach
Bering Straits
Aleutians
Northwest Arctic
Bristol Bay
Lower Yukon-Kuskokwim
Yukon-Koyukuk/Upper Tanana
Average residential rate Average non-residential rate
Regional averages for residential and non-residential electricity rates before PCE
Source: 2013 Alaska Energy Statistics
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 45
contributing to these price differences, explored in more detail in Chapter 3, include higher fuel costs, due
to more expensive diesel fuel, lower generation efficiency, and higher line losses, as well as non-fuel costs,
such as labor and materials. The regional weighted averages used in Figure 15 hide large differences within
the regions, as can be seen in the map Figure 16.
Data on non-residential electricity rates are not collected systematically by any agency. Likewise, if there
are multiple residential rates or tiered rates, these are not included in publically available databases. The
lack of access to data can cause some limitations on understanding the impact of policies and projects on
all consumers, especially if there are different price structures for different types of users.
It is important to recognize that the rates paid by consumers do not necessarily reflect the true cost of
delivering power. Due to a subsidy across the borough, the North Slope has an anomalously low electricity
rate. The subsidies for residential customers can be greater than $0.70/kWh in some communities. In
many other communities, if the capital costs for generation plants, much of which was paid for through
state and federal grants, were included, the retail rates would be significantly higher. This will be detailed
in Chapter 3.
Figure 16 shows residential rates across the state, and it is easy to see that there are large differences
across regions. The North Slope is subsidized by the borough. Southeast has significant variety, both some
of the lowest and some of highest cost utilities in the state.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 46
Figure 16: Map of residential electricity prices in AkAES study area
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 47
HEATING FUEL RATES
Outside of the Railbelt, heating oil is the main source of heat for residential and non -residential facilities
due to convenience as well as safety of use and ease of transport. It is because heating oil is commonly
used that all other fuels are compared to heating oil in this report, and this section focuses on the
consumer rates of heating oil.
While heating oil constitutes the majority of all thermal loads outside of the Railbelt, other energy sources,
such as electricity, biomass (cordwood and pellets), propane and natural gas, contribute a locally and/or
regionally important role in maintaining safe and healthy temperatures in buildings.
Electricity is generally only used for heat in the Southeast region, where some utilities have special rates
and metering for electric heat.
Firewood—otherwise referred to as cordwood—requires attention of a person to start and stoke the fire
and, as such, is much more labor intensive than the other heating fuels in this section. In addition,
firewood can be “free” if it is collected by a household. Even though there is not a dollar amount ascribed
to it, there is still a cost to collecting firewood. We do not know how to calculate the opportunity costs
accrued by those collecting firewood themselves, nor do we know how many people participate in this
activity instead of purchasing firewood. AEA has used the reported prices in communities and re gions as
the rate for firewood, even if people have collected their own firewood. The amount of energy in a cord
of wood varies by species of wood, regionally defined parameters, as well as water content of the wood,
which must be considered because of boilers that do not capture the heat used to boil off the water in
the wood.
Pellets are a relatively recent product on the market. With uniform size, shape, moisture and energy
content, pellets allow for a mechanization and control of temperature output, unlike cordwood, and they
also provide a convenience more similar to oil- or natural gas-fired heating appliances than cordwood.
The American Community Survey (ACS) includes propane as a minor thermal energy source, which, given
the margin of error, is likely overstated in many regions. Based on its pricing, propane is a viable substitute
for some electrical uses that require thermal input, such as cooking, heating water, or drying clothes,
rather than for space heating. In many cases, propane is a less expensive alternative to electricity and may
reduce the loads on diesel generators.75 Propane is less energy dense than heating oil, and a gallon of
propane only has 67% of the heating content of a gallon of heating oil. So, a building that might require
1,000 gallons of heating oil would require nearly 1,500 gallons of propane. Propane is also a less viable
source because it is a pressurized fuel, meaning that it requires a heavy tank for transportation and
storage. The two factors of lower energy density and the heavy pressure vessel increases the delivered
cost of propane relative to diesel.
Natural gas is currently available in two communities outside of the Railbelt: Barrow and Nuiqsut, both of
which happen to be very close to natural gas deposits. Actual costs of natural gas are unknown in these
75 Dave Pelunis Messier, personal communication, 4/4/2016
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 48
communities, as neither community pays market prices for the gas or associated infrastructure and
operation.
The cost of heating oil by location is similar to electricity cost by location (see Figure 17). In places where
electricity costs are higher, the heating oil costs are also generally higher. While it might not be readily
apparent, there is a greater difference between the highest and lowest cost communities for el ectricity
than for heating oil. There are also greater differences between communities that are relatively close to
each other. Some communities might be selling at a loss while others may be selling at profit.76, 77 This
may indicate that additional local-level data, such as timing of deliveries, what was left over from previous
year, etc., could help to disentangle the issue.
Road accessible communities have some of the lowest rates, even lower than many areas in Southeast,
which are closest to refineries in Washington.
76 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
77 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 49
Figure 17: Map of community heating oil price in AkAES study area (2015)
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 50
FORECASTS
Much of the research referenced in this report is meant to help understand how to predict future costs,
benefits, consumption, generation, and performance. While it is impossible to know what will happen in
the future, making educated choices based on lessons learned and a study of past action can lessen the
risk of stranded investments and assist in preparing for investment to meet growth.
For the purpose of the AkAES research and analysis , AEA assumed that the choices and preferences
revealed by consumers’ historical actions will be continued in the future. If there has been a downward
trend in per capita consumption of electricity then, which is true in many parts of the state, AEA assumed
that this trend will continue into the future in addition to any population trends that might also exist.
Everyone can relate to the experience of planning a
weekend based on the promise of sunny weather just to
have it ruined by an unexpected rainstorm. All forecasts
risk being inaccurate, but that does not mean that they
are not useful. Forecasts allow us to use what we know
today to make informed decisions and plan for
possible/probable scenarios.
The assumptions used in this report represent one view of a potential future–what AEA thinks is the most
likely outcome based on current conditions. Forecasts must be actively, continuously evaluated and
adjusted based on new information and updated data. To make this process most relevant, it must be an
iterative process.
In order to do an adequate analysis of the cost-effectiveness of potential infrastructure projects,
assumptions must be made about the future in order to compare potential project against the status quo.
Two types of forecasts are required to do this analysis; forecasts for energy prices and consumption. The
methods used to develop these forecasts are described in in the following pages.
ENERGY PRICE FORECASTS
Since energy infrastructure projects can last for 20 years or more (more than 100 years for hydro projects
in some cases), economic analysis is based on educated guesses regarding the future price of energy.
What follows is a description of how the forecasts for diesel, heating oil, and electricity were developed
for each community and/or intertie in the AkAES study area.
DIESEL PRICE FORECAST
AEA has relied on forecasts by the EIA, the federal agency that develops the most widely followed
forecasts on energy futures. In particular, the Brent crude price has been chosen over other indices, as
historically the crude inputs for Alaska’s diesel has better tracked Brent than other domestic indices, such
as West Texas Intermediate (WTI) crude prices.
Crude oil is priced on the international market. The market cannot be predicted because there are many
volatile elements that impact cost. Figure 18 shows the historical yearly averages of Brent crude and the
2016 forecast produced by the EIA.
Forecasts allow us to use what we know
today to make informed decisions and
plan for possible/probable scenarios.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 51
Figure 18: Historical yearly average Brent crude oil price78 and 2016 Energy Information Adminstration forecast79
The historical yearly averages are in nominal dollars for U.S. dollars per barrel of crude oil. The volatility
between 2003 and 2016 shows how difficult it can be to forecast future prices as large price increases can
be followed by crashes. The dashed line starting in 2017, which is used for the base case economic
analysis, is likely to be incorrect on a year-to-year basis, but it is expected to be reasonable over the long-
term.
The forecast shown in Figure 18 is then used to develop the forecasts for diesel prices through a method
developed by the Alaska Center for Energy and Power (ACEP). ACEP personnel went through the laborious
task of recording individual fuel invoices submitted to the RCA for PCE reimbursement. Marking these
invoices against the crude oil price at the date of purchase from the refinery (the lift date), ACEP
developed equations to predict the local utility price for diesel based on Brent crude price (Brent was
chosen by AEA because there are forecasts produced by EIA).80 While there are local discrepancies and
uncertainties exist, the work by ACEP improved the quality of estimates that goes into AEA’s economic
analysis.
Figure 19 demonstrates an example of how the EIA crude oil forecast is applied to an individual
community, in this case Bethel.
78 Europe Brent Spot Price FOB (Dollars per Barrel), 3/2/2016.
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RBRTE&f=A
79 Real Petroleum Prices Crude Oil Brent Spot (Case Reference case),
http://www.eia.gov/forecasts/aeo/data/browser/#/?id=12-AEO2015
80 Dominique Pride, Matthew Snodgrass, Antony Scott. “Correlating Community Specific Rural Diesel Fuel Prices with Published
Indices of Crude Oil Prices, and Potential Price Projection Applications” June 2015.
http://www.akenergyauthority.org/Content/Programs/RenewableEnergyFund/Documents/Round%209/RuralFuelModelReport
FinalDraft.pdf
$0
$20
$40
$60
$80
$100
$120
$140
2000 2005 2010 2015 2020 2025 2030 2035 2040Price Per BarrelHistorical and forecasted yearly average Brent crude oil price
Source: 2016 Energy Information Administration
Europe Brent Spot Price (Dollars per barrel)Brent Forecast (Dollars per barrel)
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 52
Figure 19: Diesel price—Historical and forecast for Bethel81
The actual price per gallon, shown in Figure 19, paid between 2003 and 2015 mirrors changes in the
average annual Brent costs for the same timeframe. The actual values are less volatile than the crude oil
prices. For instance, from 2008 to 2009 there was a nearly 40% drop in the average yearly price in crude
oil but only a 2% drop in the local diesel price. The drop was not felt entirely until the next year and then
only as a 14% reduction.
HEATING OIL PRICE FORECAST
A number of entities, including AEA and ISER, have unsuccessfully investigated the mechanisms that lead
to the differences in heating oil costs between communities, as explained in depth in Chapter 3. Lacking
this site-specific information, AEA used regional averages of the difference between the retail price of
heating oil (both #1 and #2) and the diesel price reported to PCE to forecast the heating oil prices for the
AkAES project. AEA created a workable proxy for heating costs in communities using ACEP’s wo rk
predicting the price of diesel based on the EIA Brent crude oil price and the regional average for the local
markup. This creates additional uncertainty for the community-level evaluation of projects that either
deliver or save thermal energy, but it is expected to be generally correct at the regional level.
As in the previous figure, Figure 20 applies this method to Bethel.
81 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
$0.00
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
2000 2005 2010 2015 2020 2025 2030 2035 2040Diesel price ($/gallon)Diesel price—Historical and forecast for Bethel
Source: PCE and Alaska Affordable Energy Model
Historical diesel price Forecasted diesel price
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 53
Figure 20: Heating oil price—Historical and forecast for Bethel82
Figure 20 shows just how difficult it can be to use external factors to forecast the price of heating oil in a
community. While there are some similarities between the shape of the curve of the commodity cost of
oil, shown in Figure 18, and the retail price of heating oil, there is no evident correlation. The rise in costs
after 2010 are not commensurate with the rise in the commodity cost. This may be due to a number of
factors that will be discussed in Chapter 3.
ELECTRICITY PRICE FORECAST
Electricity prices are another necessary but difficult element to forecast. The first source of uncertainty is
that many communities rely on diesel to produce electricity and the future price of diesel is uncertain. As
with heating oil, AEA has limited this uncertainty by using ACEP’s work and the EIA pro jection for Brent
crude oil to forecast diesel at the local level. Converting the diesel price to a dollar per kilowatt-hour
($/kWh) price for electricity requires further knowledge and assumptions about the utility. To forecast the
price, AEA has assumed that the generation efficiency and line loss remain consistent into the future and
that the nonfuel costs—defined as the difference between fuel cost and residential rate —remains
constant over time.
82 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
$0.00
$2.00
$4.00
$6.00
$8.00
$10.00
2000 2005 2010 2015 2020 2025 2030 2035 2040Heating oil price ($/gallon)Heating oil price—Historical and forecast for Bethel
Source: AEDG and Alaska Affordable Energy Model
Hisorical heating oil price Forecasted heating oil price
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 54
Figure 21: Electricity price—Historical and forecast for Bethel83
Compared to heating oil, the electricity price is less sensitive to the commodity cost. For instance, the 40%
reduction in the average yearly oil price between 2008 to 2009 was not felt in the data until 2009 and
2010, and then only as a 13% reduction in electricity cost. Because there are a number of other factors
that influence the cost of electricity, which will be investigated in Chapter 3, this muted response is not a
surprise. As a note, the Bethel utility was purchased by Alaska Village Electric Cooperative (AVEC) in 2014,
and because new data has not been available for the model, the forecast may not take into account any
potentially significant cost reductions that have been possible through AVEC’s purchase of the utility.84
POPULATION FORECAST
Since population is a major driver of community consumption and load, and hence cost, estimating how
the population may change is very important. No government agency currently does community-level
population projections because of the uncertainty involved in doing so for small communities.
Understanding the potential difficulties, but needing the data, AEA commissioned community-level
population forecasts from the Institute of Social and Economic Research (ISER) at the University of Alaska
Anchorage. ISER applied the common method of population forecasting by employing the historical birth,
death, and migration rates to individual communities.
83 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
84 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
$0.00
$0.10
$0.20
$0.30
$0.40
$0.50
$0.60
$0.70
$0.80
2000 2005 2010 2015 2020 2025 2030 2035 2040Electricity price ($/kWh)Electricity price—Historical and forecast for Bethel
Source: AEDG and Alaska Affordable Energy Model
Historical electricity price ($/kwh)Forecasted electricity price
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 55
ELECTRICITY CONSUMPTION/GENERATION FORECAST
In order to forecast future demand and ensure that sufficient generation capacity will be available for a
community, previous studies have generally used a 1% or higher annual growth rate. This growth rate is
not consistent with the empirical change in communities. Contrary to this assumption, for many utilities,
the per customer and total demand have both declined. The electric consumption and generation
forecasts improve on this baseline assumption by doing an analysis of the consumption trends, based on
population, for each community and/or utility.
Figure 22: Electricity consumption—Historical and forecasted for Bethel85
The example shown in Figure 22 is somewhat atypical for AkAES communities. Aside from the very high
level of consumption, the level of consumption has been particularly steady over the past decade, with
residential consumption at about 10 million kWhs per year and non-residential at about 40 million kWhs
per year. At 80% of the total consumption, the non-residential consumption is also a higher proportion of
the total consumption than in many communities. The slight uptick in consumption, primarily from the
residential sector, is based on the forecast of steady population growth in the community until 2040.
Although Bethel is one of the larger communities in the AkAES st udy area, and as a regional hub has a
larger-than-average, non-residential sector, each community has its own unique characteristics. The
residential sector can be anywhere from 8% to 70% of the total electrical load in a community, with the
majority of communities between 30% and 50%.86 The split between the residential and non-residential
85 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
86 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
2003 2008 2013 2018 2023 2028 2033 2038Electricity consumed per year (kWh)Electricity consumption—Historical and forecasted for Bethel
Source: AEDG and Alaska Affordable Energy Model
Residential kWh Non-residential kWh
Beginning of forecast
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 56
sector is important for a number of reasons, including indicating how much PCE assists in covering the
total utility costs and how reactive the demand will be to population changes.
INVESTMENT NEEDED TO MAINTAIN THE CURRENT LEVEL OF SERVICE IN AKAES
COMMUNITIES
Even without trying to bring more affordable energy to communities, there will still be a need for
continued investment in communities to maintain the current level of service. Assuming proper
maintenance, energy infrastructure has a standard design life, after which the infrastructure is expected
to be replaced. Given that the primary function of an electric utility is to maintain safe, stable, and reliable
energy, it is critical that the State’s current fiscal uncertainty does not lead to underinvestment in
community energy infrastructure that imperils the utilities’ ability to perform their required functions now
or in the future.
UTILITY PERFORMANCE IN DELIVERING STABLE, RELIABLE ENERGY
Utilities provide a service that does not lend itself to competition, especially in small markets, and thus
utilities are granted a local monopoly in exchange for fulfilling its obligations to its customers. Even if a
utility is not economically regulated, in order to be granted a certificate of public convenience and
necessity (CPCN) from the Regulatory Commission of Alaska (RCA), a utility must be fit, willing, and able
to provide the applicable services,87 which is defined as exhibiting adequate financial, managerial, and
technical fitness.88
It is difficult to know how well utilities perform as a whole in delivering the required services to customers
because no State agency collects the data needed to make this determination. The RCA collects some of
this data for economically regulated utilities, but it is not available for most of the utilities in the AkAES
study area, and many regulated utilities do not report.89
Outages and frequency/voltage stability remain key concerns for residential and business consumers.
Outages can cause a wide range of issues, including general consumer dissatisfaction; loss of stored food,
which can be a particular concern in rural areas; or even loss of life, should an outage occur at a medical
clinic, for example. Episodes of low voltage can cause electric motors to fail. Unstable frequency can also
cause issues such as clocks not keeping time properly, which may appear unimportant at first but can lead
to serious issues with electromechanical devices.90
87 AS 42.05.241
88 Regulatory Commission of Alaska. Order U-15-012(2) “Order Denying Request for Expedited Consideration; Approving
Application for Certificate of Public Convenience and Necessity; Approving Service Area Description, Tariff Sheets, and Power
Sales Agreement; Requiring Filing; and Closing Docket.” http://rca.alaska.gov/RCAWeb/ViewFile.aspx?id=69f102f0-4fdb-4475-
bfd8-471318c96bff
89 James Layne. ”Electric Utility Outage Reporting 2003 to 2013.” Presentation. Regulatory Commission of Alaska. April 22,
2015.
90 Lisa Demer, “Time warp in Bethel? It’s improving thanks to changes in the electrical system.” Alaska Dispatch News.
8/27/2016. http://www.adn.com/alaska-news/rural-alaska/2016/08/27/time-warp-in-bethel-muted-with-improved-electrical-
system/
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 57
ANNUAL INVESTMENT NEEDED TO MAINTAIN THE CURRENT LEVEL OF SERVICE
POWER PLANTS
To estimate the annual investment needed in power plant replacement in order to maintain the current
level of service, AEA chose to make a conservative estimate based on experience from the Rural Power
System Upgrade program (RPSU). The 194 communities eligible for the RPSU meet the four following
criteria:
have a population of at least 20 but less than 2,000;
are not predominantly a military or industrial site;
have a central community power system; and
are not connected to the Railbelt electrical grid (Homer-Seward-Anchorage-Fairbanks), Four
Dam Pool (Glennallen-Valdez, Wrangell-Petersburg, Ketchikan, Kodiak), or Juneau power
distribution systems.
Restricting the analysis to communities meeting these
criteria, and assuming a 30-year design life and cost of
$3.5 million per powerhouse, a yearly average
investment in physical infrastructure of over $20
million is needed to maintain the same level of service
in Alaska’s small, rural communities if no other
changes are made.
BULK FUEL FACILITIES
To estimate the annual investment needed to maintain the current level of bulk fuel storage in
communities, key for keeping buildings warm and providing fuel for electricity, AEA used its experie nce
from the Bulk Fuel Upgrade (BFU) program to provide a conservative estimate. The communities included
within the estimate had populations between 20 and 2,000, per the BFU regulations. Based on the
population and average fuel capacity per capita from the
2015 Bulk Fuel Assessment, AEA estimates that there are
approximately 29 million gallons of storage combined in
communities eligible for the BFU program. Assuming that a
bulk fuel tank farm life is 30 years on average and using the
median cost of tank farm projects between 2005 and 2016
($18/gallon in 2017 dollars) over $17 million per year of
investment in physical infrastructure is needed to maintain
the current standard of bulk fuel storage in Alaska’s small,
rural communities if no other changes are made.
THE ABILITY OF COMMUNITIES AND REGIONS TO PAY FOR ENERGY INFRASTRUCTURE
In the near term, at a minimum, it is likely that the amount of State grants for energy infrastructure will
decrease, and there will be a subsequent need for communities to pay a larger share than has been
historically required. It must be assumed that the need for the replacement infrastructure outlined above
… a yearly average investment in physical
infrastructure of over $20 million is
needed to maintain the same level of
service in Alaska’s small, rural
communities if no other changes are
made.
…over $17 million per year of
investment in physical infrastructure
is needed to maintain the current
standard of bulk fuel storage in
Alaska’s small, rural communities if
no other changes are made.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 58
will not magically disappear with the reduction in State funding, and it seems unlikely that federal funds
will increase to make up the difference. Therefore, the State must prepare to assist communities in
accessing loan financing.
Assessing a community’s or region’s ability to pay for energy infrastructure is challenging. Especially
considering conflicting needs within a community or region, it is very difficult to know how much a
community or utility might be able or willing to pay.
With reduced or no access to State grant funds there are three main ways in which energy infrastructure
could be paid for by communities, regions, or utilities:
1. The energy infrastructure could be paid for outright by using tax or other local/regional revenue
sources.
2. The community could finance the infrastructure through state, federal, or private loans.
3. Non-state grant programs, particularly through the federal government, could be accessed.
PAY OUTRIGHT FOR PROJECTS AND SUBSIDIES
Probably the easiest way for energy infrastructure to be paid for, from an administrative perspective, is
by using local or regional revenue sources, such as taxes. Some communities and boroughs already use
this strategy to build new infrastructure or, even more commonly, subsidize the cost of energy.
As seen in Figure 23, the availability of tax revenue is not equally distributed across the state.
Figure 23: Per capita tax revenue by AEA energy region91
91 Alaska Department of Commerce, Community, and Economic Development, Division of Community and Regional Affairs.
Alaska Taxable Database. Accessed September 2014.
https://www.commerce.alaska.gov/dcra/DCRARepoExt/Pages/AlaskaTaxableDatabase.aspx
$0 $15,000 $30,000 $45,000
Yukon-Koyukuk/Upper Tanana
Lower Yukon-Kuskokwim
Northwest Arctic
Bering Straits
Kodiak
Southeast
Railbelt
Aleutians
Bristol Bay
Copper River/Chugach
North Slope
Tax dollars per person per year
Per capita tax revenue by AEA energy region
Source: 2013 Combined City & Borough taxes, Alaska Dept. of Revenue
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 59
Figure 23 shows the combined local and borough tax revenue per capita by region. A little over 100
communities showed some local tax revenue. Since borough tax revenue was more common than local
tax revenue, intra-regional differences were generally low. There are huge differences, nearly three orders
of magnitude, between the per capita tax revenue in the North Slope and the bottom four regions. Figure
23 shows the unequal distribution of tax revenue.
Some communities and regions, such as the North Slope and Valdez92, choose to use tax revenue to affect
energy costs through direct subsidies. In addition to direct subsidies, it may be possible to use tax revenue
as a form of collateral for energy projects. Regional organizations and Community Development Quota
(CDQ) groups, such as Norton Sound Economic Development Corporation (NSEDC), also contribute to local
subsidies amounting to $1.32 million to electric customers in member communities in 2014.93
There are other potential local and regional revenue sources that could be used to pay for energy
infrastructure. CDQ revenues, payments in lieu of taxes (PILT), 7(i), and 7(j) payments are all other
potential revenue sources. 7(i) and 7(j) payments are requirements under the Alaska Native Claims
Settlement Act (ANCSA) that distributes various forms of revenue between the 12 regional native
corporations and between the regional native corporations and the village corporations. As noted earlier,
communities have many needs for revenue and energy infrastructure might not be the highest priority
need identified by the community. In those cases, the community will need to be able to access other
sources of funding.
ABILITY TO ACCESS FINANCING
Although it has not been the case since its passage in 2010, State energy policy directs that the power
project fund (PPF), an AEA loan program, instead of grants will be the main source of assistance for energy
projects.94 In light of reduced State grant funding for energy projects, entities will need to have greater
access to both State and non-State loans.
There is uncertainty surrounding the issue of utility creditworthiness. AEA was not able to find a
comprehensive resource for credit scores, bond ratings, or other commonly used financial measures. This
requires that lending agents perform credit checks on a one-off basis.
In a study commissioned for the AkAES, the Alaska Center for Energy and Power identified characteristics
that lenders looked for in their loan applicants. Those characteristics included the ability of the applicant
to repay the debt, a reasonable payback time for the loan, collateral to secure the loan, sufficient
administrative capacity to manage the project and loan, and an equity contribution.95
In a report commissioned for the AkAES, the University of Alaska Center for Economic Development,
(UACED) investigated the finances of 32 utilities, covering over 90 communities, through public reporting
92 Lee Revis, “Free energy credit: coming to a utility bill near you.” Valdez Star, 11/9/2016.
http://www.valdezstar.net/story/2016/11/09/main-news/free-energy-credit-coming-to-a-utility-bill-near-you/1423.html
93 http://www.nsedc.com/wp-content/uploads/267304-NSEDC-AR-proof.pdf
94 AS 44.99.115
95 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 60
to the State or Internal Revenue Service (IRS). UACED found a wide range of ability to adequately report
financial data. Many of the financial statements did not include all known sources of income (such as PCE
payments), were internally inconsistent, or were inconsistent with other reporting, including to the RCA.96
UACED found that the majority of communities assessed had especially low debt loads; generally, only
larger communities had debt loads.97 This is likely because of the utilities’ success in accessing grant funds,
and that larger communities are ineligible for State and federal programs such as the Rural Power System
Upgrade and Bulk Fuel Upgrade programs, which are limited to populations under 2,000. With regards to
liquidity metrics, most of the utilities had a strong balance between the near-term cash-producing assets
and near-term liabilities. The net revenue of many of the utilities was highly volatile from year to year.
This work indicates that many utilities have some financial attributes, such as low debt loads and strong
liquidity measures, that could make them potentially attractive to lenders, but that there are many other
factors, including inadequate financial reporting and volatile net revenue and cash flow, that will be a
hindrance to debt financing energy projects.98
Other factors that affect bankability were not included in this study, which was focused solely on what
could be gleaned from available financial reports. Probably the most important is the lack of collateral in
many communities. Even for a short-term State loan program such as the Bulk Fuel Loan program, which
acts significantly less risk averse than private financers, lack of collateral has been a common reason fo r
rejecting loan applications. For long-term infrastructure projects, where the infrastructure is not likely
going to be seen as a means to secure the loan, the lack of collateral can be an even larger barrier.
Additional analysis of the barriers to applicants to the Bulk Fuel Loan program and Power Project Fund
are contained in Chapter 5.
ABILITY TO ACCESS NON-STATE FINANCING
All of the communities in the AkAES study area are eligible for many federal programs focused on rural
and high-energy cost regions, including through the Denali Commission and the U.S. Department of
Agriculture (USDA) High Energy Cost and Rural Utility Service (RUS) grant programs. These two federal
entities have been major contributors to rural Alaska infrastructure, with the Denali Commission
contributing $811 million in grants since 2001 and the USDA $61 million in grants since 2009.
In addition to the important role that many tribes play in the governance and sustainability of
communities, tribal membership brings access to a number of federal programs. The U.S. Department of
Energy, U.S. Department of Housing and Urban Development; USDA; and other federal programs
specifically focus on tribal land and organizations in grant and loan solicitations. The number and
percentage of communities within a region with federally recognized tribes are far from uniform across
96 University of Alaska Center for Economic Development. “Utility Financial Analysis and Benchmarking Study Draft.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/Utilityfinancialanalysisandbenchmarkingstudy.
pdf
97 UACED 2016
98 UACED 2016
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 61
the state, as shown in Figure 24. Almost all communities in the Northwest Arctic, North Slope, Lower
Yukon-Kuskokwim, and Bering Straits have a federally recognized tribe.
Figure 24: Communities with a federally recognized tribe by AEA energy region99
A number of regional non-governmental organizations also provide support for energy projects in Alaska.
One example is the Norton Sound Economic Development Corporation’s Community Energy Fund (CEF),
which allocated $1 million for each of its 15 communities with a sunset in 2021. CEF program funding may
be for a number of construction-ready, community-wide generation and distribution projects, including
renewable and alternative energy, and efficiency upgrades. This program will not fund feasibility studies
for energy upgrades or construction projects. The program funds facilitate the actual implementation of
projects that are past the feasibility, licensing, and final design phases (“shovel-ready”).100 Not all regions
of the state have similar energy programs.
99 Alaska Department of Commerce, Community, and Economic Development, Division of Community and Regional Affairs.
Alaska Community Database Online. Accessed September 2015. https://www.commerce.alaska.gov/dcra/DCRAExternal
100 http://www.nsedc.com/programs/community-benefits/community-energy-fund/
0%33%67%100%
0 20 40 60
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Percent of Communities with Federally Recognized Tribe
Number of Communities with Federally Recognized Tribe
Communities with a federally recognized tribe by AEA energy region
Source: Division of Community and Regional Affairs (DCRA) Community Database
Online
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 62
FEDERAL AND PRIVATE DEBT FINANCING
The AkAES study area has significant variability in terms of
ability to access private capital to develop projects. For
power generation, larger utilities, utilities operating in
larger hub communities and small cities, and those that are
members of larger cooperatives often have the ability to
access traditional debt financing to develop projects. Access
to traditional debt financing is available when borrowers
have attractive balance sheets, stable revenue streams,
traditional collateral to secure loans, and staff who are able
to manage and meet the requirements of complex financing
tools.
For many small, stand-alone utilities, accessing private financing is more challenging. Potential borrowers
may lack the financial health to be able to secure traditional loans. Additionally, typical private commercial
lending terms are not well matched for large utility projects that may require longer repayment terms to
avoid causing cash flow problems.
USDA Rural Development has a wide variety of programs that fund different types of community
development projects in rural communities. The programs that are most relevant to this study are the
Rural Utilities Service (RUS) electric grant and loan programs, the Community Facilities (CF) grant and loan
programs, and the Rural Energy for America Program (REAP) grants and loan guarantees. Some of these
grant programs have been used extensively in the study area, but use of the loan programs has been much
more limited for a variety of reasons.
All of the loan programs have extensive paperwork involved, and they may require applicants to have first
applied to commercial lenders. RUS loans have extensive requirements for applicants to demonstrate
their creditworthiness and the feasibility of the loan, as well as environmental review and regulatory
approval requirements that can involve a substantial amount of work for a small utility. CF loans are direct
loans from USDA to the applicant, and typically applicants have to have applied for commercial credit and
been denied to be eligible. REAP does not do direct loans but has loan guarantees, as do RUS and CF, and
in these cases applicants first need to secure commercial financing before applying to USDA. At least
partially due to these requirements, use of USDA loan programs in the study area has been very limited
despite the large amount of money potentially available.
The only USDA loan originated between 2009 and 2015 for electric projects in the study area was a $10.6
million guaranteed loan to Kodiak Electric and a $2.9 million guaranteed loan to the Kotzebue Electric
Association. Several other utilities in the study area appear to have USDA loans, either direct or
guaranteed, from before 2009. All other USDA loans for electric utilities ($432 million) between 2009 and
2015 went to Railbelt utilities.
Access to traditional debt financing
is available when borrowers have
attractive balance sheets, stable
revenue streams, traditional
collateral to secure loans, and staff
who are able to manage and meet
the requirements of complex
financing tools.
February 2017 CHAPTER 2: Current Conditions of the AkAES Study Area Page | 63
Table 7: USDA loans for businesses, energy programs, hospitals, water systems, and housing in Alaska (2009-2015)101
AEA Energy Region
USDA Energy-
specific loans
USDA total loans
in region
Percent of USDA
loans in Alaska
Railbelt $418,500,000 $963,864,551 66%
Lower Yukon-Kuskokwim $0 $214,584,940 15%
Southeast $0 $146,605,366 10%
Kodiak $10,600,000 $58,890,859 4%
Copper River/Chugach $0 $31,123,446 2%
Bering Straits $0 $22,751,676 2%
Bristol Bay $0 $13,275,938 1%
Northwest Arctic $2,900,000 $8,063,265 1%
Aleutians $0 $6,927,650 0%
Yukon-Koyukuk/Upper Tanana $0 $1,634,650 0%
North Slope $0 $725,912 0%
Entities in the study area have accessed USDA loan products. Although the majority of USDA loans have
been within the Railbelt, the USDA provided nearly $500 million in direct and guaranteed loans in the
AkAES study area for water/wastewater, telecommunications, and health care projects. The total loan
amounts vary widely by region, and the value of individual loans range from less than $2,000 for individual
homeowners to $165 million for the remodel of the Yukon-Kuskokwim Health Corporation’s Bethel
hospital.
101 AEA compilation of USDA loan data 2009-2015.
February 2017 CHAPTER 3: Energy Cost Drivers Page | 64
CHAPTER 3: ENERGY COST DRIVERS
Only by understanding the factors driving the total cost consumers pay for energy is it possible to
understand what costs can and cannot be changed. This chapter pulls together the best research and data
AEA has been able to compile to understand the complex mechanisms that lead to a customer’s energy
bill. Chapters 6 continues this work to evaluate opportunities.
Figure 25: Diagram of the components of consumer energy costs
Figure 25 will be used as a reference for the analysis of what contributes to the total consumer energy
cost. The total cost is the sum of the electricity and heating fuel costs. As seen in Chapter 2, in most cases,
the heating costs outweigh the electricity costs. Costs for electricity and heating fuel are each a
combination of the rate paid per unit (such as cents per kilowatt-hour or dollars per gallon) and the
Consumer
Electric Rate
Consumer
Electricity
Consumption
Consumer
Heating Fuel
Rate
Consumer
Heating Fuel
Consumption
Consumer
Electricity Cost
Consumer
Heating Fuel Cost
Total Consumer
Energy Cost
Key Takeaways
1. Most study area communities are dependent on imported diesel fuel, the price of which is largely
determined by world markets
2. The large distances between communities cause high costs for delivering fuel and supplies
3. Non-fuel costs are important factors for the cost of electricity
4. Most communities have insufficient energy consumption to create an economy of scale
5. Local decisions by unregulated utilities and fuel suppliers play a very important role in
determining energy costs
Management decisions and technical capacity impact how infrastructure is maintained and
thus its usable life and generation efficiency
Retail electricity and heating oil prices are largely unregulated and there is a wide range of
pricing decisions made at the community level
February 2017 CHAPTER 3: Energy Cost Drivers Page | 65
number of units consumed. The following sections will provide data and analysis to understand the
factors that lead to both the rates for electricity and heating fuels as well as the consumption of electricity
and heating fuels.
DRIVERS FOR THE DELIVERED COST OF DIESEL
As shown in Chapter 2, diesel is the primary fuel for electricity generation and heat for most of the
communities in the AkAES study area. This section will outline factors that drive the cost of liquid fuels in
communities. Later sections will then explore drivers for consumer electricity and heating fuel prices. For
simplicity’s sake, this section will use “diesel” to refer to diesel for electricity, heating oil for heat, and
gasoline/aviation fuels for transportation.
For much of Alaska, bringing more affordable energy to communities involves either reducing the cost or
reducing the amount of diesel consumed. These are the primary factors for determining economic
benefits of projects.
Before going into a description of the individual drivers of the delivered cost of diesel, we will begin by
looking at the way that AEA translates crude oil prices to diesel prices at the co mmunity level. As stated
in Chapter 2, ACEP recorded individual fuel invoices submitted to the RCA for PCE reimbursement.
Marking these against the crude oil price at the date of purchase from the refinery (the lift date), ACEP
developed equations to predict the local utility price for diesel based on Brent crude price.102
Figure 26: Relationship between crude oil price and delivered diesel price103
Figure 26 summarizes the range of delivered diesel prices that are expected across the AkAES region based
on the international price per barrel of Brent crude. Although it may be counterintuitive, the community
price for fuel does not increase at a one-to-one rate with the price of crude oil. Per the model, doubling
102 Dominique Pride, Matthew Snodgrass, Antony Scott. “Correlating Community Specific Rural Diesel Fuel Prices with Published
Indices of Crude Oil Prices, and Potential Price Projection Applications” June 2015.
http://www.akenergyauthority.org/Content/Programs/RenewableEnergyFund/Documents/Round%209/RuralFuelModelReport
FinalDraft.pdf
103 AEA analysis of ACEP 2015 fuel price model
$0.00
$2.00
$4.00
$6.00
$8.00
$30 $60 $90Diesel price ($/gallon)Brent crude oil price ($/barrel)
Relationship between crude oil prices ($/bbl) and delivered diesel prices
Source: AEA analysis of ACEP price model (2015)
Third quartile
Second quartile
February 2017 CHAPTER 3: Energy Cost Drivers Page | 66
the price of crude oil does not double the delivered cost—not even tripling the price of crude oil results
in a doubling of cost. For example, the highest cost community shown in Figure 26 goes from
approximately $4.50 at $30/bbl to $6 at $60/bbl and $7.20 at $90/bbl, a 60% increase in diesel price
resulting from a tripling of the crude oil price.104
In addition to input commodity, there are other cost drivers. Even if crude were free, it would still incur a
cost to deliver the fuel. Some of those costs increase with the increase in crude price (such as cost of fuel
to power the barges), but some costs are less elastic, such as labor costs, capital recovery, etc. Refining
costs are not always related to cost of feedstock. The unit price of diesel for a utility includes the
international price of crude oil, the cost of refining the crude oil to a consuma ble product, the
transportation of the diesel to the community, any financing charges, and the cost of storing the fuel on
site.
The spread of diesel prices from one community to another increases with the crude oil price, but the per-
gallon cost for diesel in lower cost communities does not increase at the same rate as in higher cost
communities. As seen in Figure 26, the spread between the minimum and maximum prices increases from
$30/bbl to $90/bbl from about $3.50/gal to over $5/gal.
INTERNATIONAL MARKET AND COMMODITY COST
The price of crude oil, which is determined by international markets, is a primary driver of diesel costs.
While forecasting the price of crude oil is fraught with uncertainty, doing so provides a useful baseline for
understanding what might happen and allows for the comparison of potential projects. Chapter 2 Figure
18 on page 51 shows the historical yearly averages of Brent crude and the 2017-2040 forecast produced
by the EIA.
Relying on three ISER studies performed between 2008 and 2011 exploring the components of fuel costs,
the chart in Figure 27 will be filled in over the next several sections to illustrate components making up
the cost of delivered fuel.105,106 ,107 In this first iteration, only the costs of the crude oil and its refining are
included in the figure. Figure 27 is a general depiction of what leads to the cost of diesel in a community;
it will not be completely accurate for any given community and specifically assumes that the fuel will be
delivered by barge, which is true for the majority of communities in the AkAES region but not all of them.
104 The nonlinear increase that is seen here may be as much an artifact of the equation type chosen to model the data as an
indication of the real response of local prices to external factors.
105 Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. “Components of Delivered Fuel Prices in Alaska.”
June 2008. http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
106 Ginny Fay, Ben Saylor, Nick Szymoniak, Meghan Wilson and Steve Colt. “Study of the Components of Delivered Fuel Costs in
Alaska: January 2009 Update.” January 2009. http://www.iser.uaa.alaska.edu/Publications/fuelpricedeliveredupdate.pdf
107 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
February 2017 CHAPTER 3: Energy Cost Drivers Page | 67
Figure 27: Components of delivered price of diesel: Crude oil & refining108
*Assumes $40/barrel crude oil
For this generalized case, it can be seen that commodity cost of diesel, depicted as the sum of the crude
oil and refining, is nearly 40% of the delivered price. The rest of the delivered price is from the
transportation and local storage of the fuel.
COST DRIVERS OF DIESEL FUEL DELIVERY
Fuel is delivered by three main modes throughout Alaska: by airplanes, road, and barges to communities
on the coast or river system. Researchers have further distinguished barge deliveries to communities that
are ice-free year round (such as Southeast, Kodiak, and the Aleutians) and those that are ice-bound during
the winter months (communities north of the Alaska Peninsula and on Interior rivers). Each of these
modes of delivery has a unique price structure. Figure 28 illustrates the range of per gallon prices by
transportation mode and assumes $50 per barrel of oil.
108 AEA adaptation from 2008-2011 ISER work on components of delivered fuel costs
0%
20%
40%
60%
80%
100%
Linehaul Lightering
Crude oil &
refining
Tranportation Local storage TotalPercent of total delivered priceComponents of the delivered price of diesel: crude oil & refining*
Source: AEA adapted from 2008-2011 ISER work
Oil: Refining & other
Oil: Crude oil
February 2017 CHAPTER 3: Energy Cost Drivers Page | 68
Figure 28: Delivered price of fuel to PCE communities by transportation mode (Assumes $50/bbl crude oil)109
There is less difference between ice-free and ice-bound deliveries than might be expected, especially
given the large distances needed to supply fuel for northern and Interior regions.
Air has the greatest cost spread of any mode of delivery—in some cases it appears to be cheaper to fly
fuel into communities than to deliver it by barge. The higher cost of air delivery is not always due to the
costs of flying the fuel. The highest cost areas are impacted by the fact that their fuel is bought from an
intermediary who plays a large role in determining price. For example, for some of the communities in
the Kotzebue area, fuel is flown in from Kotzebue, paid for at the local retail rate in Kotzebue.110, 111 The
final delivered cost to the communities includes the price of the air delivery but also the cost of delivering
the fuel to Kotzebue and the local markup.
Delivering fuel by Alaska’s highways is very inexpensive, merely pennies per gallon. With frequent
deliveries, often weekly, costs via road delivery parallel the crude price more closely. The price paid by
the community changes to match the rise and fall of price on international markets. Generally, product
being delivered by road does not need more than a couple of weeks of storage, which creates efficiencies
while also making it unlikely to experience fuel emergencies due to low stocks.
Given the paucity of data and lack of access to proprietary information from fuel deliverers, it is difficult
to know exactly what causes the price in any given community, but there are a number of potential drivers
for the differences in community diesel prices.
One major cost factor is distance. Distance increases the hours of labor and fuel needed for
transportation, and reduces the number of gallons of product to recover the cost of capital (the barge,
truck, or airplane has to be paid for). The distance traveled also increases the unit cost for all of these
components. For instance, to get to Nome, fuel coming from the Port of Anchorage has to travel
109 AEA analysis of ACEP fuel price model (2015)
110 Ingemar Matthiesen, personal communication, 4/4/2016
111 Trevor Crowder, Fuel operations manager at Everts Air Fuel. Personal communication 4/25/2016.
$0.00
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
Barge (Ice-Free)Barge (Ice-bound)Air Road
Delivered price of fuel to PCE communities by transportation mode
Source: AEA analysis of 2014 ACEP model
Third quartile
Second quartile
February 2017 CHAPTER 3: Energy Cost Drivers Page | 69
approximately 700 miles to Unimak Pass (the first pass to western Alaska), then another 640 miles from
Unimak Pass to Nome.
BARGE DELIVERY
The ice-free portions of the state (particularly Southeast) generally have eas y access because they are
close to large markets like Washington state. Furthermore, the amount of storage needed is lower than
in the ice-bound region. Some areas may receive monthly deliveries, while smaller, more remote
communities may only receive a couple of deliveries per year even though the community may be
accessible year round.
For a number of reasons, the ice-bound areas of western Alaska and Interior rivers have the highest
delivered cost of fuel in the state (and potentially anywhere in the U.S.).112 The time constraints from the
short open-water period, the subsequent low utilization of capital, the large distances, and relatively
shallow rivers all exacerbate the costs people end up paying. Figure 29 summarizes the main drivers for
the cost of delivering fuel into a small, remote community along the coast or on an Interior river. Each of
the sections (linehaul, lightering, and other) is discussed in more depth in the following pages.
Figure 29: Components of the delivered price of diesel: Barge transportation113
*Assumes $40/barrel crude oil
Linehaul barges are relatively large, ocean-going barges that carry 2-3 million gallons in a trip from
Southcentral Alaska or Washington state. The linehaul barges generally require 18 -20’ of draft, which is
deeper than most of the ports in Western Alaska (Naknek and Nome are two of the few, even Bethel does
112 Ginny Fay, Ben Saylor, Nick Szymoniak, Meghan Wilson and Steve Colt. “Study of the Components of Delivered Fuel Costs in
Alaska January 2009 Update.” Prepared for: Alaska State Legislature, Senate Finance Committee. January 2009.
http://www.iser.uaa.alaska.edu/Publications/fuelpricedeliveredupdate.pdf
113 AEA adaptation from 2008-2011 ISER work on components of delivered fuel costs
0%
20%
40%
60%
80%
100%
Linehaul Lightering
Crude oil &
refining
Tranportation Local storage TotalPercent of total delivered priceComponents of the delivered price of diesel: Barge transportation*
Source: AEA adapted from 2008-2011 ISER work
Transportation: Admin
Transportation--Working Capital
Lightering: Local challenges
Lightering: CAPEX & other
Lightering: Fuel
Lightering: Personnel
Linehaul: CAPEX & other
Linehaul: Fuel
Linehaul: Personnel
Oil: Refining & other
Oil: Crude oil
February 2017 CHAPTER 3: Energy Cost Drivers Page | 70
not have sufficient draft for an ocean-going barge). In the areas where the linehaul barges are not able
to deliver to a port, the fuel is transferred to smaller barges, lightering barges, in protected waters off the
coast.
Due to a grounding near Nunivak Island reported by the Alaska Dispatch News in June 2016 114 , AEA
became aware that fuel is delivered into Southwest Alaska by large tankers in addition to linehaul barges.
It is unlikely the tanker would be able to dock any ports at to unload its fuel, since the draft of a tanker is
greater than any port north of the Aleutians.115
Based on work by ISER, the cost of paying for the barge (CAPEX) constitutes the single largest cost for a
barge company, comprising about 45% of the expenses that need to be recovered in delivering fuel. The
operational expenses (OPEX) are broken out between the fuel to run the barge, the labor to operate the
barge, and other expenses. Fuel is not as significant of an operational expense as might be expected—at
$2.50/gallon, fuel accounts for less than 10% of the total cost of the linehaul delivery. Each dollar change
in fuel price for the barge only changes this component by about a percentage point. Labor accounts for
about 30% of the total cost of delivery, which is three times the cost of the fuel to operate the barge.
Other operational expenses, such as insurance, make up the remainder.116
To get the fuel to the smaller communities, the fuel must be transferred to the lightering barges,
sometimes directly and sometimes by first being transferred into a shore-side storage facility. Each of
these touchpoints incurs time and costs. Wharfage fees for loading and unloading fuel can be up to $0.04
per gallon, and the labor needed to staff the unloading and loading of the barges can be up to $0.06 per
gallon.117
While the lightering barges are smaller than the linehaul barges, they are more expensive to operate per
unit than linehaul, primarily because they are utilized less and deliver fewer gallons over a season. The
barges are frequently made specifically for Alaska’s riverine and coastal environments and do not get used
outside of the four- to five-month ice-free window. The capital and operational expenses have a very
similar breakdown as the linehaul barges.118
The conditions in any given community can also incur greater costs. Issues such as the lack of moorage,
multiple (or missing) marine headers to unload the fuel, and dangerous river conditions can all increase
the time and risk of delivering fuel. These costs are generally passed along to the community.119
114 Jeannette Lee Falsey. “Coast Guard: No spill in grounding of tanker carrying fuel to Southwest Alaska villages.” Alaska
Dispatch News. 6/25/2016. http://www.adn.com/alaska-news/2016/06/25/coast-guard-no-spill-in-grounding-of-tanker-
carrying-fuel-to-southwest-alaska-villages/
115 U.S. Army Corps of Engineers, Alaska District. “Fuel Transportation Improvement Report.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AEAfueltransportationreport101416.pdf
116 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
117 Szymoniak et al, 2010
118 Szymoniak et al, 2010
119 Szymoniak et al, 2010
February 2017 CHAPTER 3: Energy Cost Drivers Page | 71
The delivery companies have two other main costs that must be covered. The fuel that is being delivered
to communities must be paid for; and, depending on the terms of the agreement, payment may not be
made until delivery. If this is the case, the delivery company may be holding onto millions of dollars of
product that must be carried with the risk of non-payment. This working capital is expected to cost about
$0.02 per gallon. Other administrative services–billing customers, purchasing diesel from refiners,
coordinating schedules between barges and communities, etc.–are expected to cost another $0.05-$0.10
per gallon.
All of these various expenses add more than a dollar to the wholesale cost of diesel from the refinery, as
shown in the Figure 29.
OTHER FACTORS IN DELIVERED FUEL PRICE
As with any other private enterprise, it would be expected that the fuel deliverers would earn a profit.
Investigation by both the Alaska attorney general (AG) office and ISER did not find “excess profits” from
fuel distributors.120,121 In 2009, as part of the AO 247 Rural Fuel Price Investigation, the AG’s office found
that the “average rate of return on capital was unremarkable”.122
Anecdotally, credit risk and financing terms are another factor that leads to the final price that consumers
pay. Since most communities will have access to the Bulk Fuel Loan, administered by the Division of
Community and Regional Affairs (DCRA), it would seem that credit risk should now be minimal for most
fuel deliverers as the risk of repayment has been transferred to the State. Conversations with fuel
distributors have highlighted this benefit to fuel distributors.123
LOCAL STORAGE
The cost of storing fuel in the community can be a significant driver for local fuel costs, though whether
or not that cost is always priced into fuel used for electricity generation or consumer heating oil is
unknown. Figure 30 shows the added cost that local storage contributes to the total cost of diesel through
the capital costs, operational costs, and working capital.
120 Szymoniak et al, 2010
121 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
122 Alaska Attorney General, 2010.
123 Trevor Crowder, Fuel operations manager at Everts Air Fuel. Personal communication 4/25/2016.
February 2017 CHAPTER 3: Energy Cost Drivers Page | 72
Figure 30: Components of the delivered price of diesel: Local storage124
*Assumes $40/barrel crude oil
Since many communities have been recipients of a bulk fuel tank farm from the State and/or federal
government, the capital expenses (CAPEX) are generally not included in the retail price of the fuel.125 The
CAPEX component included in Figure 30 is from an AEA analysis of the Denali Commission bulk fuel
database for the per-gallon costs of bulk fuel storage in communities. More details on this are included in
Chapter 5 under the section on the Bulk Fuel Upgrade program.
Operational expenses (OPEX) include both regulatory compliance and the maintenance and labor for the
tank farm. AEA does not have access to the actual operational expenses for the facilities, as they are not
economically regulated. The RCA reports that some utilities use the Denali Commission/AEA business
plans to account for bulk fuel operational expenses for PCE reimbursement.126
The working capital is the amount of money that is needed to cover the cost of holding a large amount of
fuel for many months before the product can be sold to consumer s. This working capital is equivalent to
the amount of interest that would be paid over the winter for holding onto the fuel before selling it. Many
communities invest hundreds of thousands to millions of dollars in bulk fuel purchasing; those funds will
remain tied up, not available for other investments, until the fuel is sold.
124 AEA adaptation from 2008-2011 ISER work on components of delivered fuel costs
125 Per Denali Commission grant agreements, communities are supposed to have a business plan that charges customers for the
eventual replacement of the bulk fuel facility.
http://denali.gov/images/documents/Other_Commission_Reports/RR_Report_FINAL_6-12-13.pdf
126 Julie Vogler, Regulatory Commission of Alaska, personal communication, June 2016.
0%
20%
40%
60%
80%
100%
Linehaul Lightering
Crude oil &
refining
Tranportation Local storage TotalPercent of total delivered priceComponents of the delivered price of diesel: Local storage*
Source: AEA adapted from 2008-2011 ISER work
Storage: CAPEX
Storage: Working capital
Storage: OPEX
Transportation: Admin
Transportation--Working capital
Lightering: Local challenges
Lightering: CAPEX & other
Lightering: Fuel
Lightering: Personnel
Linehaul: CAPEX & other
Linehaul: Fuel
February 2017 CHAPTER 3: Energy Cost Drivers Page | 73
In cases where a community that used a Bulk Fuel Loan to purchase fuel ends up selling less fuel over the
term of the loan than was purchased with the loan, the community has to find other funds to pay off the
loan without the revenue from the fuel sales, which places a burden on the community.127
DRIVERS OF CONSUMER ELECTRIC RATE
The residential and/or commercial rate that people pay for electricity is determined by a number of
complex interrelated supply chains and utility decision-making processes. While the price of fuel is seen
as the primary driver of the consumer rate, fuel costs, generation and distribution efficiency, and the non-
fuel utility management needs and decisions all contribute to the final rate customers pay. As seen later
in this section, ratemaking decisions, an infrequently addressed part of the process, has a significant
impact on residential rates as well as the total cost of electricity in communities. The Power Cost
Equalization program blunts some of these rates to certain consumers, shifting them instead to the State.
UTILITY COST OF DIESEL FUEL
As seen in Chapter 2, the majority of utilities in the AkAES study area rely exclusively on diesel fuel for
electricity generation. Fuel costs are a major component of the residential electricity rate for the majority
of communities in the AkAES study area.
Figure 31: Components of electricity price: Fuel cost128
*Note: Assumes $3.50/gallon of diesel and 12 kwh/gallon
Figure 31 shows the percentage of 2013 residential rates that were based on the cost of diesel for those
communities that participated in PCE. The other two categories, currently showing no data, will be
127 Jane Sullivan, Division of Community and Regional Affairs, personal communication 11/14/2016.
128 AEA analysis and calculations based on utility filings to the RCA for the PCE program and AEA PCE program data, 2000-2014.
0%
25%
50%
75%
100%
Fuel cost Utility non-fuel
cost
Rate above
reported,
eligible
TotalPercent of Retail RateComponents of electricity price: Fuel cost*
Source: AEA analysis of utility PCE filings to the Regulatory Commission of Alaska
Fuel
February 2017 CHAPTER 3: Energy Cost Drivers Page | 74
addressed later in this chapter. Figure 31 assumes that fuel costs $3.50/gallon and that power generation
efficiency is 12 kWh/gallon. Given these assumption, which is roughly average for PCE communities, fuel
costs constitute approximately half of the residential electricity rate. This is obviously not the case for all
communities, as is illustrated in Figure 32.
Figure 32: Cost of fuel as a percent of residential rate for PCE-eligible utilities129,130
One noteworthy anomaly illustrated by Figure 32 is that in some cases the residential rate does not cover
even the fuel cost for the utilities—this is the case for all values above 100%. In some regions there is also
a wide spectrum of variability in the degree to which fuel costs influence the residential rate. In some
communities using hydropower, for instance, it is nearly 0%.
GENERATION AND DISTRIBUTION EFFICIENCY
Diesel costs are not fixed for a community. The unit price that a utility pays for diesel changes from year
to year. The values in Figure 32 have likely changed with the reduction in oil prices, for instance, but 2013
is the most recent year for which AEA has cleaned data for this analysis. The consumption of diesel is also
not fixed. Aside from changes in the consumption of electricity, the generation and distribution efficiency
of the power plant also has a profound impact on a utility’s fuel costs.
A utility’s generation efficiency (generally measured in terms of kWh of electricity produced per gallon of
diesel), the distribution efficiency (generally referred to as line loss and measured in the percent of
129 AEA analysis of PCE data, accessed from Alaska Energy Data Gateway (https://akenergygateway.alaska.edu/)
130 Figure does not include North Slope and non-PCE communities
0%25%50%75%100%125%150%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Fuel cost as percent of residential rate
Cost of fuel as a percent of residential rate for PCE-eligible utilities
Source: 2013 PCE data
Second quartile Third quartile
Weighted average: 63%
Median: 55%
February 2017 CHAPTER 3: Energy Cost Drivers Page | 75
generation not purchased by consumers), and the price of fuel (measured in dollars per gallon) all
contribute to the cost of power. Generation efficiency, in particular, as shown in Figure 33, has a primary
role in determining the cost of power.
Figure 33: Impact of generation efficiency on fuel cost in $/kWh131
Differences in generation efficiency have less of an impact at lower prices. For example, the difference in
the cost of power between the highest and lowest efficiency is $0.12/kWh at $2/gal, but $0.44/kWh at
$7/gallon. Generation efficiency directly affects the cost consumers pay. Generation efficiency is lim ited
by the type of gensets, and also a number of other factors including how well the genset is sized to the
community’s load (gensets run less efficiently at low loads), the age of the genset, and the maintenance
performed on the machinery.
The cost of power is more volatile when generation efficiency is lower, as seen in Figure 34. Yearly
averages for Brent crude prices are used to estimate the differences in $/kWh for the cost of power in a
hypothetical community in Figure 34. Brent crude prices are converted to community diesel prices, using
Bethel for the case study.
131 AEA calculations
$0.25
$0.50
$0.75
$0.88
$0.17
$0.33
$0.50
$0.58
$0.13
$0.25
$0.38
$0.44
$-
$0.20
$0.40
$0.60
$0.80
$1.00
$2.00 $3.00 $4.00 $5.00 $6.00 $7.00Fuel cost as $/kWhPrice per gallon of diesel
Impact of generation efficiency on fuel cost in $/kWh
Source: AEA calculations
8 kWh/gal
12 kWh/gal
16 kWh/gal
February 2017 CHAPTER 3: Energy Cost Drivers Page | 76
Figure 34: Generation efficiency’s impact on the cost of power132
Figure 34 shows how the fuel cost, in terms of $/kWh, would have changed from 2000 through 2016 based
on two different fuel efficiencies. The upper line is the efficiency at 10 kWh/gallon and the bottom line is
for 14 kWh/gallon. It should be evident that the cost of power changes significantly over the years, and
the two efficiencies respond very differently to the changes in the cost of diesel. The cost difference
between the two efficiencies is only $0.06/kWh at the lowest crude oil price, but goes to $0.15/kWh at
the highest oil price in 2011.
Price volatility is also greater when efficiency is lower. For example, between 2010 and 2011, the change
in crude oil price translated to a $0.11/kWh increase for the lower efficiency scenario but only $0.08/kWh
at the higher efficiency scenario. Translating this difference into total costs, if the utility sold an average
of one million kWh per year, this $0.03 difference would mean a difference of $30,000 in cost to the
community. Generation efficiency helps protect the utility and community from commodity volatility.
132 AEA analysis based on ACEP fuel price model
$-
$0.15
$0.30
$0.45
$0.60
2000 2002 2004 2006 2008 2010 2012 2014 2016$/kWhGeneration efficiency's impact on the cost of power
Sources: AEA analysis
Cost of power--10 kWh/Gal Cost of power--14 kWh/Gal
February 2017 CHAPTER 3: Energy Cost Drivers Page | 77
Figure 35: Generation efficiency in PCE-eligible communities133
The reported generation efficiency in PCE-eligible communities, as shown in Figure 35, does not show a
strong correlation between community size and generation efficiency, particularly below 5 million
kWh/year. While smaller communities do tend to have lower efficiency, some smaller communities have
reported efficiencies close to large communities. The two efficiencies above 16 kWh/gallon and below 15
million kWh generated are likely due to reporting errors.
The cost effect of line loss works in a similar manner to generation efficiency. As electricity is distributed
to consumers, there is an unavoidable loss of power through the power lines, at transformers, and other
parts of the distribution system. Per RPSU design specifications, a local distribution should lose no more
than about 8% of its power through these necessary components. A distribution system that has unknown
faults, unseen bridging, or grounding may be losing energy–energy that must still be produced by burning
diesel but that does not provide any benefit to the community. Not insignificantly, these losses may also
be a safety hazard. Line losses drive up the costs to the consumers, as seen in Figure 36.
133 2013 PCE data, accessed from the Alaska Energy Data Gateway.
6
8
10
12
14
16
18
0 15,000,000 30,000,000 45,000,000Generation efficiency (kWh/gallon)kWh generated per year
Generation efficiency in PCE-eligible communities
Source: 2013 PCE data
February 2017 CHAPTER 3: Energy Cost Drivers Page | 78
Figure 36: Impact of line loss on the cost of power134
Figure 36 uses a constant efficiency, 12 kWh/gallon, while looking at the trajectory of different line losses.
At higher fuel prices, line losses become more expensive. At the low end of the fuel price spectrum, the
difference between 5% and 25% line loss is only $0.04/kWh, but at $6/gallon the difference equates to
$0.17/kWh. Some utilities have reported line losses greater than 30%, which contribute s to unnecessary
costs to consumers.
When diesel is cheap, inefficiency is much less expensive. The price of crude, currently low, is but one
factor that leads to the utility’s price for diesel. If anything, the other factors that lead to the delivered
price of fuel, such as labor and capital costs, would be expected to increase in the future.
UTILITY NON-FUEL COSTS
While fuel costs make up, on average, 63% of residential electricity rates across all PCE communities, non-
fuel costs are also substantial. For this analysis, AEA used unpublished data supplied by the RCA on non-
economically-regulated utilities that participated in PCE from 2007 to 2014. In order to be reimbursed by
the PCE program, the RCA evaluates all reported expenses to ensure that they are allowable under RCA
regulations. Utilities can only be reimbursed for expenses that are reported to the RCA, which creates a
strong incentive for utilities to report any and all expenses. Some of the data would indicate that not all
utilities report all expenses, but without auditing every utility, it is impossible to be certain.
What follows are those that the RCA determined to be allowable expenses. There may be expenses that
are actual utility expenses that were deemed to be ineligible by the RCA for various reasons—anecdotally,
old fuel debt is a commonly disallowed expense.
134 AEA calculations
$0.18
$0.35
$0.53
$0.61
$0.22
$0.44
$0.67
$0.78
$-
$0.20
$0.40
$0.60
$0.80
$2.00 $3.00 $4.00 $5.00 $6.00 $7.00$/kWh$/gallon
Impact of line loss on the cost of power
Source: AEA calculations
5%25%
February 2017 CHAPTER 3: Energy Cost Drivers Page | 79
Figure 37: Range of reported, allowable non-fuel utility cost135
Total reported utility non-fuel costs, seen on the bottom of Figure 37, range from approximately
$0.10/kWh to more than $0.90/kWh.
Median cost of utility personnel across the dataset is approximately $0.12/kWh, which is more than the
total cost per kWh in some Alaska communities, including several in the study area. Outlying personnel
expenses range up to $0.50/kWh. Most utilities did not separate out the personnel expenses for the
operators versus the office personnel or utility clerks versus management. It is difficult to know from the
available data which of these positions is the primary driver of personnel costs.
Total utility operating expenses are almost entirely personnel costs. Maintenance activities, at least those
not captured in the personnel expenses, represent a minimal sum to utilities. Given the importance of
maintenance in reducing the need for early replacement of gensets, which are capital costs that have
historically not been typically born by the utilities, it would be useful to know how these costs fit with
expectations for these utilities. Current data availability does not allow for that analysis, however.
Bad debt is an expense from uncollected bills that are being written off by the utility. Anecdotally, bad
debt has been identified as a major strain on utilities. Although this may be an issue of utilities
underreporting an allowable expense to the RCA, the available data does not indicate that bad debt is a
major issue across the PCE utilities. Looking at the ledgers of a small sample of utilities showed that
customer payments were not made regularly but that accounts were settled over time, so the real issue
may instead be one of cash flow rather than one of having to write off customer debts. The issues caused
135 AEA analysis of utility filings to the RCA for the PCE program and AEA PCE program data, 2000-2014.
$(0.20) $- $0.20 $0.40 $0.60 $0.80 $1.00
Total personnel
Total operating expenses…
Insurance
Bad debt
Total G&A costs
Depreciation & amortization
Interest expense (income)
Other misc. income
Total reported cost
$/kWh
Range of reported, allowable utility non-fuel costs
Source: AEA analysis of RCA non-regulated PCE ilings (2007-2014)
Second quartile Third quartile
February 2017 CHAPTER 3: Energy Cost Drivers Page | 80
by volatile cash flow have been one of the reasons why pre-paid meters have become more widespread
across rural Alaska.
The category Total G&A costs includes other general and administration expenses including building rent,
telecommunications, insurance, and other such expenses.
Almost all utilities in this analysis had some sort of depreciation and/or amortization, but few had anything
sizeable. The vast majority of the infrastructure assessed was paid for by grants from the State and/or
federal government. Other miscellaneous income came mainly from heat sales and pole rental for
telecommunications. It is possible that utilities are not fully exploiting other revenue sources that could
reduce the cost to consumers.
Figure 38: Components of electricity price: Utility non-fuel costs136
*Note: Assumes $3.50/gallon of diesel and 12 kwh/gallon
Figure 38 shows how utility non-fuel costs, which were displayed in Figure 37, add to the total costs of the
utility. It should be apparent that the non-fuel costs are an important contributor to the overall cost that
consumers pay. Operational expenses, primarily personnel costs, contribute about a quarter of all costs.
These costs are why electricity prices are much less sensitive to changes of crude oil prices than are diesel
prices.
It is uncertain if the reported non-fuel costs are sufficient to cover the utilities’ needs. There are
indications of deferred and or neglected maintenance in many communities. At least some of the
operational costs are subsidized by State programs, including the Electrical Emergency Assistance and
136 AEA analysis and calculations based on utility filings to the RCA for the PCE program and AEA PCE program data, 2000-2014.
0%
25%
50%
75%
100%
Fuel cost Utility non-
fuel cost
Rate above
reported,
eligible
TotalPercent of Retail RateComponents of electricity price: Utiility non-fuel costs*
Source: AEA analysis of utility filings to the Regulatory Commission of Alaska
Other: Income
Other: Interest
Other: Deprecriation
General & Admin: Other
General & Admin: Bad debts
General & Admin: Insurance
Operating Expenses (Personnel, O&M,
R&R)
Fuel
February 2017 CHAPTER 3: Energy Cost Drivers Page | 81
Circuit Rider programs.137 The rates in many communities would likely need to be raised to cover the
actual expenses to maintain the infrastructure for its expected economic life.
THE IMPACT OF ORGANIZATIONAL STRUCTURE ON NON-FUEL UTILITY COSTS
The non-fuel costs generalized in Figure 38 are far from uniform across utilities. It would be assumed that
rural utilities should experience some economies of scale, since as the utility increases in size in terms of
sales, the costs to run the utility will be spread out over more kWh of sales. Figure 39 shows the
relationship between the non-fuel cost per kWh and the kWh sold for the PCE communities, including
some that are economically regulated.
Figure 39: Utility non-fuel costs per kWh vs. kWh generated138
As is evident in Figure 39, the spread in booked, non-fuel costs among the smaller utilities, particularly
those with sales under 10,000,000 kWhs, is very large. The reported, allowable non-fuel expenses go from
under $0.05/kWh to over $0.80/kWh. It may be that some of the smaller utilities do not have the
resources or bookkeeping to accurately report the actual expenses at the utility. Some communities may
provide internal subsidies, where the community clerk or manager may also perform work for the utility
137 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
138 Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in Rural Alaska.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElectricityFuel102616.pdf?ver=
2016-10-27-083402-423
$0.00
$0.15
$0.30
$0.45
$0.60
$0.75
$0.90
0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000$ per kWhkWh sold (FY14)
Booked non-fuel costs per kWh vs FY14 kWh sold
Source: ISER analysis of RCA data
All communities AVEC Communities
Cordova
Bethel
Unalaska
February 2017 CHAPTER 3: Energy Cost Drivers Page | 82
but not be on the utility’s books. If these anecdotes are correct, communities are missing out on potential
State funds that might be available to the community through PCE reimbursement.
Above 10 million kWhs of sales, there is a factor of four difference between the lower bound ($0.07/kWh)
and the upper bound ($0.33/kWh). In this analysis, the largest utility, the Alaska Village Electric
Cooperative (AVEC) has very average non-fuel costs.
It should also be remembered that most of these utilities do not have significant capital expenses due to
the historical abundance of state and federal grants for utility infrastructure. If these costs were included,
non-fuel costs for almost all utilities would be significantly higher, as is shown in Chapter 5.
Figure 40: Non-generation expenses vs. annual kWh sales by organization type139
Figure 40 slices the data in a slightly different way in order to understand the organizational efficiency of
utilities. In this chart, the costs associated with generation have been removed, which creates a fair
comparison between utilities. For example, Alaska Power Company (APC) has significant hydro generation
while AVEC is almost exclusively reliant on diesel. Even without including the cost of fuel, diesel power
requires more operations and maintenance (O&M) than hydropower. In this analysis, as opposed to Figure
39, AVEC shows significant economies of scale. Except for the most extreme outliers, this is up to
$0.30/kWh less expensive than some of the other utilities.
139 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
$-
$0.20
$0.40
$0.60
$0.80
$1.00
0 10,000,000 20,000,000 30,000,000 40,000,000$/kWh Customer Svcs + G&A ExpenseskWh per year by community served and organization type
Customer + G&A expenses per kWh vs. annual kWh
across Alaska PCE communities by organization type
Source: MAFA analysis of RCA data (2012-2016)
City / Borough Village Local Coop Regional Coop Local IOU Regional IOU
AVEC
APC
February 2017 CHAPTER 3: Energy Cost Drivers Page | 83
A large spread of costs is seen for the utilities, with some pronounced differences by the type of utility. In
this analysis, larger utility structures, including regional co-ops and regional investor owned utilities
(IOUs), see significant economies of scale. Other types of organizational structures including local co-ops,
municipal/borough run utilities, village utilities (defined as municipal run utilities with sales less than 1
million kWhs/year), and local IOUs, are generally more expensive.
Figure 41: Distribution of non-generation expenses by organization type140
NOTE: “n” is the number of communities within the utility type
Figure 41 shows the range of non-fuel costs by the type of utility organization. Large regional utilities, both
co-ops (such as AVEC) and IOUs (such as APC), have the lowest median costs at $0.065/kWh and $0.077,
respectively. Local Community Co-ops, which tend to serve larger communities (12 million kWh/year
average), are marginally more expensive at a mean cost of $0.083/kWh.
The last three organizational structures deliver higher median costs to serve rural communities – ranging
from $0.11/kWh for city/boroughs to the $0.16-$0.18/kWh range for stand-alone villages and local IOUs.
The overall range of costs is wide, even for the middle 50% of utilities. For example, the city/borough
group, the middle 50% of utilities, range from $0.07/kWh to $0.23/kWh.
140 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
$- $0.10 $0.20 $0.30 $0.40 $0.50 $0.60 $0.70 $0.80 $0.90 $1.00
Regional Coop
Regional IOU
Local Coop
City / Borough
Village
Local IOU
$/kWh [Customer Svc + G&A Expenses per kWh]
Distribution of non-generation expenses by organization type
(Distribution + Customer Service + G&A Expenses per kWh)
Source: MAFA analysis of RCA data (2012-2016)
2nd Quartile 3rd Quartile Median
n=59
n=31
n=7
n=23
n=42
n=7
February 2017 CHAPTER 3: Energy Cost Drivers Page | 84
Larger regional utilities, both co-ops and IOUs, tend to be more efficient than other organizational
structures. The most efficient large regional co-op, AVEC, includes a large regional hub and dozens of
smaller villages.141
UTILITY RATES
For those utilities that are economically regulated by the RCA, the utility’s profit is based on the approved
return on equity. For all other utilities, which constitute the majority of PCE eligible utilities, the utility is
able to charge whatever rate they deem appropriate.
In addition to customer charges, fees (such as connection fees), and other revenue (such as heat sales or
pole rental), non-fuel rates should cover fixed and variable utility costs. Fixed customer charges are
generally minimal ($5/month in almost all communities with applicable data). Since the quantity of
electricity sold in any given year cannot be predicted and small changes in consumption or the loss or gain
of a limited number of customers can have a large effect on sales, small utilities can be put in a difficult
financial position purely due to a change in sales.142
In Figure 42 the rates reported to the RCA by each utility are compared to the utility’s reported, allowable
expenses (in terms of $/kWh). There is only one entry per utility—so even if one utility covers multiple
communities, it will only be counted once. It is important to recognize that this does not include non-
booked costs, in particular the grant-funded capital costs for infrastructure. The consumers’ rates would
be significantly higher if the State and federal governments had not paid significant amounts of the
infrastructure costs.
Figure 42: Utility rates as a percentage of reported, allowable costs143
141 Foster and Townsend, 2017.
142 University of Alaska Center for Economic Development. “Utility Financial Analysis and Benchmarking Study.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/Utilityfinancialanalysisandbenchmarkingstudy.
pdf
143 AEA analysis and calculations based on utility filings to the RCA for the PCE program and AEA PCE program data, 2000-2014.
0
4
8
12
16
Number of UtilitiesActual rate as percent of reported expenses/kWh
Utility rates as a percentage of reported, allowable costs for non-
economically regulated PCE utilities
Source: AEA analysis of RCA and AEA data
Rates do not cover
reported,allowable
expenses
Rates are greater
than reported,
allowable
expenses
North Slope
Borough
February 2017 CHAPTER 3: Energy Cost Drivers Page | 85
PCE will not reimburse an amount over the rate set by the utility. For example, if the rep orted allowable
expenses are $0.80/kWh but the customer rate is only $0.15/kWh (as is the case in many North Slope
Borough communities), PCE will only reimburse based on the $0.15/kWh rate and not the full reported,
allowable rate. PCE will also not reimburse for rates above the reported, allowable expenses. Thus, if the
reported, allowable expenses, including fuel, equal $0.30/kWh but the rate is $0.45/kWh, PCE will only
reimburse on the basis of the $0.30/kWh reported, allowable expenses and utility customers will pay the
difference. This is why the effective rate in most communities is not at the PCE minimum. Residential
electricity rates are higher than is needed to cover the reported, allowable expenses in 57 of the 78 non-
economically regulated utilities.
Figure 42 includes the cost of power adjustment (COPA)—essentially the fuel cost—for the most recent
year available, generally FY2014. Thirteen utilities did not have rates that covered all reported, allowable
expenses; six of those utilities are located in the North Slope Borough (NSB). The NSB provides a $0.50-
$0.75/kwh subsidy to the communities, effectively negating potential reimbursements from the PCE
program. Several other communities and utilities also provide subsidies to their customers, presumably
from local resource taxes.
The majority of the 45 non-economically regulated utilities have rates that are between 110% and 140%
of the reported, allowable expenses. It appears that anecdotes about small, rural utilities undercharging
their customers are not supported by the data.
There are specific instances where legitimate expenses are not allowed and which must be paid for by
customers. Because of this, some argue that all reported costs should be used instead of the allowable
costs as these may be more reflective of actual utility expenses.144 In some cases, utilities have past fuel
debt that must be repaid, but these expenses are not allowed und er current PCE regulations. This may
explain the extreme outliers of rates that are set nearly twice as high as the reported, allowable expenses
submitted to the RCA. As shown in Figure 43, the weighted average of the component of the non-fuel rate
that is above the reported, eligible expenses is about 7% of the residential electricity rate. An inspection
of Figure 42 may make one expect that this value would be larger, but since Figure 42 does not break it
out by individual community, and the largest utilities have rates closest to the reported, eligible expenses,
the average across all non-economically regulated utilities is much less than might be expected.
144 Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in Rural Alaska.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElectricityFuel102616.pdf?ver=
2016-10-27-083402-423
February 2017 CHAPTER 3: Energy Cost Drivers Page | 86
Figure 43: Components of electricity price: Rates above reported, eligible145
*Note: Assumes $3.50/gallon of diesel and 12 kwh/gallon
A reserve fund for renewable and replacement (R&R) is another common potential expense that is not
allowed. In order to prepare for major repair and replacement of infrastructure in the future, many believe
that utilities should save money in a reserve account, perhaps because these accounts were required per
the Denali Commission grant agreements that built many of the utilities’ powerhouses. The reserve
accounts were meant to allow for sustainable operation of the facilities and not create a future liability
for the state or federal government. In 2012, the Denali Commission’s Inspector General was unable to
determine if these accounts were set up and being funded through ratepayers. 146 It seems unlikely that
the rates that are significantly above the reported, allowable expenses are being used to fill these
accounts.
From the utility’s perspective, there is likely no advantage for having a reserve account sp ecifically for
replacing the infrastructure as opposed to taking out a loan at the time of plant replacement. In fact,
charging current customers for future investments runs directly contrary to fundamental principles of
utility regulation, which is why the deposits into R&R accounts are not eligible expenses. The used and
useful principle, which underlies utility regulation, requires that physical assets are both used by and
145 AEA analysis and calculations based on utility filings to the RCA for the PCE program and AEA PCE program data, 2000-2014.
146 Office of Inspector General, Denali Commission. Analysis of R&R Accounts as Highlighted in the FY2012 Second Half Semi-
Annual Report to Congress. June 12, 2013. http://oig.denali.gov/wp-content/uploads/2015/01/SAR-2012-09.pdf
0%
25%
50%
75%
100%
Fuel cost Utility non-fuel
costs
Rate above
reported,
eligible
TotalPercent of Retail RateComponents of electricity price: Rates above reported, eligible*
Source: AEA analysis of utility filings to the Regulatory Commission of Alaska
Rate above reported and eligible
Other: Income
Other: Interest
Other: Deprecriation
General & Admin: Other
General & Admin: Bad debts
General & Admin: Insurance
Operating Expenses (Personnel, O&M,
R&R)
Fuel
February 2017 CHAPTER 3: Energy Cost Drivers Page | 87
useful to current ratepayers to reduce costs or ensure the quality of service before they can be required
to pay for the assets.147,148
Of the factors shown in Figure 43, approximately half of them respond slowly to changes in demand—the
utility non-fuel costs and the rate above reported, eligible—and half of them are variable—the fuel cost.
As the price of fuel and the efficiency of the generation and distribution system changes, the relative
weights of all of these factors change. Since the non-fuel costs respond slowly to changes in demand, it
would indicate that more of these fixed costs should be recovered in a customer charge instead of in rates.
This would reduce some of the difficulties of setting a rate based on uncertain sales to cover the fixed cost
of operating the utility.
COST OF CAPITAL FOR ELECTRIC UTILITIES
The cost of capital was not included in the previous analysis, due to insufficient data. Cost of capital
includes both the cost of debt, the interest paid, and the cost of equity, which is the profit on the capital
investments made by the utility. Economically regulated utilities in Alaska are only allowed to earn a profit
from their equity, otherwise their rates are limited by the RCA to the reported, allowable costs. The
utilities that are not economically regulated are able to charge whatever rate they choose.
In most markets, utilities have a combination of debt and equity on their books. In most of the
communities in the AkAES study area, utilities have both limited debt and lim ited equity because either
the State or federal government granted the infrastructure to the community or utility.149 The grant-
funded infrastructure does not count as equity for the utility and they are not allowed, if it is an
economically regulated utility, to earn a return on the government’s investment.
The cost of equity increases with the amount of risk experienced by the utility. Smaller utilities, because
of uncertainty associated with the volatility of consumption and potential cash flow issues, will have a
higher cost of equity than larger utilities. The weighted cost of capital is the combination of the cos t of
debt (the interest rate paid to finance the infrastructure) and the cost of equity (the expected return on
the investment). Figure 44 provides an illustration of the weighted cost of capital for the range of utility
sizes for PCE-eligible utilities.
147 Wikipedia. “Used and Useful Principle.” https://en.wikipedia.org/wiki/Used_and_Useful_Principle
148 Jim Lazar. “Electricity Regulation in the US: A Guide.” Second Edition. The Regulatory Assistance Project. 2016.
http://www.raponline.org/wp-content/uploads/2016/07/rap-lazar-electricity-regulation-US-june-2016.pdf
149 Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in Rural Alaska.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElectricityFuel102616.pdf?ver=
2016-10-27-083402-423
February 2017 CHAPTER 3: Energy Cost Drivers Page | 88
Figure 44: Weighted average cost of capital for PCE utilities150
Most PCE eligible utilities do not have sizeable debt or equity, due to State and federal grant-funding of
infrastructure. In addition to grants, consumers’ costs are also lower because of the reduced cost of
capital.151 Per the above analysis, a private utility or independent power producer (IPP) in the PCE region
that does not have grant-funded infrastructure would likely require a return on equity (ROE) between 16%
and 22%. If the entity is an IPP investing in small communities, in order to reduce consumer costs and still
earn a return on investment, the IPP would have to be significantly more cost-efficient than the status
quo. For reference, large utilities’ ROE in the Lower 48 are generally close to 10%.152
RETAIL COST OF HEATING OIL
Although the factors that lead to the delivered cost of fuel, including heating oil, is relatively we ll
understood, finding a way to correlate the delivered and retail costs has been problematic because of the
variety of local pricing decisions. In 2010, ISER found that the majority of fuel price variability resulted
from pricing decisions by the local fuel retailer.153
In 2010, the State of Alaska attorney general investigated causes of the high fuel costs in rural Alaska
communities. The AG’s office had access to proprietary data that AEA and other researchers have not had
access to. After determining that fuel deliverers were not extracting unusual profits, the AG’s report
looked into local decisions that led to the sometimes large retail differences in a geographically close area.
The AG report found a range of local mark-ups: from just a few percent to 100% mark-up. The factors that
the AG noted for why these differences exist included: the fuel had previously been sold at a loss, a lack
150 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
151 Foster and Townsend, 2017.
152 Castalia Strategic advisors. Estimating WACC for Regulated Utilities in the United States. April 2014. http://www.castalia-
advisors.com/files/updated_2014/TP_WACC_Sub_Attachment_B_Castalia_Estimating_WACC.pdf
153 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
0%
5%
10%
15%
20%
25%
Village-scale
utility
Small rural
utility
Medium
rural co-op
utility
Large local
co-op
Large rural
muni utility
Large
regional IOU
Large
regional co-
op
Weighted average cost of capital -rural utilities
Source: Adapted from MAFA (2016)
Weighted cost of equity Weighted cost of debt
Small village scale
utilities estimated
cost of capital is
reduced by 1,290
basis points when
they join large
February 2017 CHAPTER 3: Energy Cost Drivers Page | 89
of local competition, as a source of revenue to pay for public projects or other community needs, and no
apparent justification for the different retail prices. The AG was unable to determine the amount of profit
by the local fuel distributors.154 ISER also found anecdotal evidence of communities marking up the fuel
cost to raise revenue for other local services, acting as a de facto tax.155
Given the challenges noted in previous work, AEA did not attempt to gather additional data on local
markups. Instead AEA tried multiple ways to come up with a mathematical relationship between utility
diesel and retail heating oil prices. Likely due to the inconsistency in local pricing strategies, no statistically
significant method was found that worked for the majority of communities.
AEA ended up generalizing the local mark-ups on a regional basis by comparing the reported utility diesel
cost, as reported to PCE, to the retail heating oil prices in communities. Diesel and heating oil are similar
fuels, sometimes the same fuel, delivered by similar or same means. While other factors, as noted earlier,
may lead to different prices for different purchasers in the same community, this method allows for some
interesting analysis, as shown in Figure 45. Two regions are highlighted to show the change in this
difference over time.
Figure 45: Average yearly difference between retail heating oil and utility diesel unit cost by AEA energy region156
154 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
155 Szymoniak, et al 2010.
156 AEA analysis of PCE and Alaska Housing Finance Corporation and Division of Community and Regional Affairs fuel price
surveys. Accessed through Alaska Energy Data Gateway (https://akenergygateway.alaska.edu/).
$(3.00)
$(2.00)
$(1.00)
$-
$1.00
$2.00
$3.00
$4.00
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Difference between retail heating oil and utility dieselAverage yearly regional difference between retail heating oil and utility
diesel costs
Sources: AHFC fuel survey and PCE by fiscal year
Aleutians
Bristol Bay
Northwest
Arctic
Lower Y-K
Bering Straits
Copper
River/Chugach
Kodiak
Y-K/Tanana
Southeast
Railbelt
North Slope
February 2017 CHAPTER 3: Energy Cost Drivers Page | 90
AEA compared reported utility diesel cost to the retail heating oil prices in study area communities, using
an average across all communities in the AEA energy region. The expectation of this analysis was that the
difference between the utility price of diesel and the retail price of heating oil would provide an indication
of the price to operate the bulk fuel storage facility and small margin for profit. AEA had expected to find
little difference between the regions over time, as it was assumed that a comm unity would have similar
expenses to cover, independent of where it was located. AEA found that there were large regional
differences in the costs of heating oil versus utility diesel cost and that those differences changed over
time.
To help illustrate how the difference between costs of heating oil and costs of diesel for power generation
has changed over time, two regions, the North Slope and Northwest Arctic, are highlighted in Figure 45.
The Northwest Arctic region, highlighted in blue, had a relatively steady markup over time: approximately
$1/gallon from 2004 through 2008. This change is consistent with analysis on what it should cost to
operate a bulk fuel facility.157 Then, after 2008, the difference between the utility diesel and retail heating
oil price diverged significantly to more than $3/gallon. Other regions experienced similar divergences.
The North Slope region illustrates a contrary example. The steep decline for the North Slope shows the
impact of the subsidy for residential customers provided by the North Slope Borough.
Figure 46 includes an average local markup to complete the illustration of all costs contributing to the
retail cost of heating oil in study area communities. The cost of the fuel is only one of many factors making
up the high energy costs paid by many Alaska communities.
Figure 46: Components of delivered price of heating oil: Local markup158
157 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
158 AEA adaptation from 2008-2011 ISER work on components of delivered fuel costs
0%
25%
50%
75%
100%
Crude oil &
refining
Linehaul Lightering
Tranportation Local
storage
Local
heating oil
markup
TotalPercent of Retail Heating Oil PriceComponents of the delivered price of heating oil: Local markup*
Source: AEA analysis of various sources Local heating oil markup
Storage: CAPEX
Storage: Working capital
Storage: OPEX
Transportation: Admin
Lightering: Local challenges
Lightering: CAPEX & other
Lightering: Fuel
Lightering: Personnel
Linehaul: CAPEX & other
Linehaul: Fuel
Linehaul: Personnel
Oil: Refining & other
Oil: Crude oil
February 2017 CHAPTER 3: Energy Cost Drivers Page | 91
*Note: Assumes $3.50/gallon of diesel and 12 kwh/gallon
One additional factor was not included in Figure 46: taxes. In FY16, the State of Alaska enacted a
$0.01/gallon heating oil tax, which is less than the $0.08/gallon State tax on motor fuels. At well under 1%
of the retail cost of fuel, the penny-per-gallon tax would not show up on the chart. The tax is not collected
in a way that allows for knowledge of heating oil consumption at the local level.
Though some communities in the AkAES study area have a local sales tax up to 8%, more commonly local
tax is less than 5%. However, these local taxes are still relatively uncommon, and as a small percentage of
the total cost, they were also left off of Figure 46.
All of the factors summarized in Figure 46 illustrate why heating oil is only moderately sensitive to changes
in the price of crude oil, as was shown in Chapter 2’s Figure 18 on page 51.
DRIVERS FOR HEATING FUEL AND ELECTRICITY CONSUMPTION
In almost all AkAES study area communities, the primary factor contributing to consumer energy cost is
population. In addition to the basic relationship (more people will consume more energy), a community’s
population will change how energy is consumed. Generally speaking, larger communities have more and
larger buildings that consume energy, particularly electricity, differently than smaller communities.
This last section of Chapter 3 will investigate the factors, including population, that impact energy
consumption, specifically the heating and electricity consumption for residential and non-residential
buildings. This section provides an analysis that allows for a general understanding of the factors that lead
to differences in energy consumption. The Alaska Affordable Energy Model (AAEM) presents a more
detailed set of data to develop consumption estimates for all communities in the AkAES study area.159
Chapter 6 will look at changes that can be made to reduce energy consumption; this chapter aims to
describe factors that currently impact energy consumption.
COMMUNITY THERMAL LOADS
To be comfortable for the building users, buildings must be heated for much of the year in Alaska. A
number of factors, including the local climate, size of building, type of use, as well as the building efficiency
(insulation, heating efficiency, and building tightness) affect the consumption of heating fuels.
159 The Alaska Affordable Energy Model will be available through AEA’s website
February 2017 CHAPTER 3: Energy Cost Drivers Page | 92
CLIMATE
Figure 47: Heating degree days160
Heating degree days (HDD) is a useful way to quantify how cold an area is over the entire year and is
calculated by taking the difference between 65 degrees Fahrenheit and the outdoor temperature. For
example, if the average outside temperature in a community is 20 degrees for a given day, there would
be 45 heating degree days for that particular calendar day. By adding these across the entire year and
averaging it over multiple years, the total HDD for a year can be estimated. The HDD is also a convenient
way to estimate relative thermal requirements. For a given structure, a doubling of HDD roughly
corresponds to a doubling in the amount of heating oil (or other fuel) needed to maintain the same interior
temperature. Locations with colder average temperatures throughout the year require more energy to
maintain the same interior temperature.
Southeast Alaska has the most temperate climate in Alaska, with less than 7,500 HDD, and the North Slope
with more than twice that, with over 18,000 HDD. While many other physical factors can go into actual
heating needs–including the amount of sun, the speed and direction of wind, the use of the building, the
number of people occupying the buildings, etc. –when all else is equal, a building in Ketchikan would
consume about half of the heating oil than if that same building were in Barrow.
NUMBER OF BUILDINGS PER COMMUNITY
The number of buildings in a community, both residential and non-residential, is strongly influenced by
the community’s population. Other factors, such as the economic vitality of the community, also influence
160 AEA mapping of Cold Climate Housing Research Center (CCHRC) analysis of 1980-2010 climate data
February 2017 CHAPTER 3: Energy Cost Drivers Page | 93
the number of buildings. Although information associated with community-level income is not always
statistically significant, it appears that wealthier communities have more residential and non -residential
buildings.
The number of buildings in communities, which is a dataset in the AAEM, was collected from a number of
sources including the Alaska Native Tribal Health Consortium (ANTHC), local property taxes, and various
State, federal, and NGO personnel who traveled to communities.
BUILDING SIZE
In addition to having more non-residential buildings, larger communities also generally have larger non-
residential buildings. The data collected in Table 8 comes from an AEA analysis of more than 1,000 non-
residential buildings in the AkAES study area. The table represents a sub-set of the data used by the AAEM
to estimate non-residential energy consumption.
Table 8: Average non-residential building square footage by building type and community size161
Population
less than
300
Population
between
300 and
1,200
Population
greater
than 1,200
Education 10,921 20,463 62,095
Health care - hospitals 2,157 3,802 6,779
Public assembly 2,842 3,296 9,257
Public safety 2,463 2,302 12,602
Warehousing 1,883 2,869 3,950
Average—not including education 2,304 3,649 7,706
Building square footage influences both the heating and electricity consumed. As can be seen in Table 8,
the average square footage of the building type increases with the community size. Most notably,
education buildings double in size between communities with a population of less than 300 to
communities with up to 1,200 people, and then triple in size for the communities with the largest
populations.
RESIDENTIAL SIZES
In general, larger residences require more heating fuel to keep them at the same interior temperature.
While house sizes vary within a community, the average sizes vary more significantly from community to
community. By using this average community size, AEA was able to develop an estimate for the total
heating fuel consumption in a community.
Figure 48 aggregates data from the Alaska Retrofit Information System (ARIS), AHFC’s database, which
houses all of the data from the residential audits performed for the Weatherization, Home Energy Rebate
161 AEA analysis of multiple sources
February 2017 CHAPTER 3: Energy Cost Drivers Page | 94
(HER), and New Home Rebate programs. The amount of data available in ARIS by community extends from
0% to nearly 100% of the residential buildings in the community.
Figure 48: Range of average community residential building size162
The majority of study area communities have residences with an average size under 1,500 square feet,
with many under 1,000 square feet. For instance, both the Lower Yukon-Kuskokwim and Northwest Arctic
median average size is less than 1,000 square feet. Some communities typically have much larger houses;
both the Southeast and the Aleutians regions include communities that averaged more than 2,000 square
feet per household. Good data was not available for all communities to adequately assess the range of
average home size.
BUILDING QUALITY
After the climate and building size, the building quality, specifically with regards to its thermal efficiency,
has a profound effect on how much energy is consumed.
Figure 49 provides a comparison of how building quality, climate, and local energy rates affects the total
energy costs for a residential consumer. In the figure, the same 1,400-square-foot residential building was
modeled using AHFC’s residential energy modeling software, AkWarm, to three levels of energy efficiency:
One Star, Three Star, and Five Star. A One Star has little insulation in the walls and attic, single pane
windows, and is very drafty. A Three Star house is moderately insulated in the walls and attic, has double-
pane windows, and is somewhat drafty. A Five Star house is well insulated in the walls, attic and floor; has
162 AEA analysis data from Alaska Retrofit Information System, accessed Fall 2014.
0 500 1,000 1,500 2,000 2,500
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Average residential square footage
Range of average community residential building size
Source: AEA analysis of AHFC HER, Weatherization, BEES data
Second quartile Third quartile
February 2017 CHAPTER 3: Energy Cost Drivers Page | 95
high efficiency windows and heating system; and few air leaks. This house was evaluated in two
communities with different climates: Bethel (12,542 HDD) and Unalaska (8,899 HDD).
Figure 49: Residential energy costs per AHFC star rating for three communities163
It is evident that there are large differences in consumer costs between locations and the building’s
efficiency. Improving the efficiency of the housing can lead to large cost reductions, nearly $15,000 per
year in heating costs could be offset by improving a One Star house to Five Stars (based on 2014 energy
prices). The figure also shows that energy cost savings will not be the same between locations, as the local
energy rates and climate affects the costs. The modeled cost for heat and domestic hot water in Bethel
for a Five Star rated house is roughly equivalent to a Three Star house in Unalaska.
BUILDING USE
Building occupant behavior and energy use is another primary factor leading to total energy consumption.
Data regarding energy consumption is non-random and may therefore include systematic biases that may
over- or under-estimate the consumption. The AkAES used the best data available.
Non-residential consumption
Across the study area’s approximately 1,000 non-residential buildings for which AEA was able to find
reported annual heating fuel consumption, the average was about one gallon, plus or minus a half a gallon,
per square foot across all building types. Although some individual buildings consumed significantly more
heating fuel than others, likely due to occupant behavior and or poor building quality, there were not
huge differences between buildings types.164
163 AEA analysis of AkWarm modeling (2014)
164 Richard Armstrong. “A White Paper on Energy Use in Alaska’s Public Facilities.” 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
$- $2,500 $5,000 $7,500 $10,000 $12,500 $15,000 $17,500 $20,000
One Star
Three Star
Five Star
One Star
Three Star
Five StarBethelUnalaska
Annual household energy cost
Residential energy costs by AHFC star rating
Source: AEA analysis of AkWarm modeling (2014)
Heat Domestic Hot Water
February 2017 CHAPTER 3: Energy Cost Drivers Page | 96
Based on data compiled by AEA, more than 90% of non-residential thermal energy is supplied by heating
oil. In Southeast, a higher percentage of non-residential buildings use electric resistance heating where
low-cost hydropower is available.165 Biomass and heat recovery both supply a small percentage, and each
has greater potential. Southeast has a handful of non-residential (air- and ground source-) heat pumps,
and Barrow and Nuiqsut have locally available natural gas.
Residential consumption
Unlike non-residential buildings, residential consumption is based on estimates from the AkWarm
residential energy model and not from reported consumption by building occupants. The results in this
section are based on approximately 17,000 pre- and post-retrofit energy audits using the AkWarm model.
So as to provide a common unit of measure, the energy consumption values included in Figure 50 have
been converted into gallons of heating oil equivalent.
Figure 50: Range of residential heating consumption (in gallons of heating oil equivalent)166
Based on the results of the analysis, the majority of households in the study area consume between 500
and 2,000 gallons of heating oil equivalent. Regional differences are apparent—the Aleutians, Bristol Bay,
and Lower Yukon-Kuskokwim average between 500 and 1,000 gallons of heating oil equivalent. A
comparison of Figure 48 to Figure 50 shows interplays between local climate and building size and end-
use efficiency. It is apparent that climate can play a big role in consumption. Surprisingly, the community
with the largest average consumption is in the Southeast, as is the community with lowest average
consumption.
165 Black & Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
http://www.akenergyauthority.org/Content/Publications/SEIRP/SEIRP-Vol1-ExecSumm.pdf
166 AEA analysis of ARIS data
0 500 1,000 1,500 2,000 2,500 3,000
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Average Gallons of Heating Oil Equivalent per Year
Range of yearly residential heating consumption in AEA regions
Source: AEA analysis of AHFC HERP, Weatherization, BEES data
Second quartile Third quartile
February 2017 CHAPTER 3: Energy Cost Drivers Page | 97
As stated earlier, Figure 50 converts all fuels into an equivalent number of gallons of heating oil. In some
areas wood is a common fuel, and in others, primarily the Southeast, electricity is also used as a primary
source of heat.
Figure 51: Fuels consumed for residential heating167
Unlike in non-residential buildings, there appears to be more diversity in the fuel sources for residential
buildings. Based on work done by the U.S. Census, as found in the American Community Survey, Figure 51
shows the estimated use of various fuel types. The data is not perfect, as can be seen in the utility gas
column; the only communities in the AkAES study area that have access to natural gas are Barrow and
Nuiqsut. Figure 51 provides a more qualitative snapshot of residential heating fuel type, but it also shows
that residences in some regions, particularly the Yukon-Koyukuk/Upper Tanana region, may be less
affected by heating oil prices as occupants have chosen to burn wood instead of heating oil.
ELECTRIC CONSUMPTION
As was shown in Chapter 2, there are regional and community differences in residential electric
consumption. No data is available for what leads to the differences, although socioeconomic differences,
appliance efficiency, the number and kind of consumer goods, and different levels of energy conservation
practiced by occupants all likely play a role in the level of residential electricity consumption.
Residential customers respond to seasons by consuming more electricity in winter than summer,
approximately one-third more in January than in June.
167 United States Census Bureau. “B25040: House Heating Fuel [10]”. 2008-13 U.S. Census Bureau’s American Community
Survey Office, 2013. Web. January 2015 <http://ftp2.census.gov/>.
0%25%50%75%100%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
North Slope
Railbelt
Southeast
Yukon-Koyukuk/Upper Tanana
Primary source of residential heat by AEA energy region
Source: American Community Survey (2013)
Utility gas Propane Electricity Fuel oil Wood Other
February 2017 CHAPTER 3: Energy Cost Drivers Page | 98
More data is available for non-residential electricity consumption; AEA was able to find electric
consumption data for about 1,000 buildings in the study area. A portion of these results, categorized
under the same three community sizes as Table 8, is included in Table 9.
Table 9: Non-residential electric consumption per square foot by building type and community population168
Population
less than
300
Population
between
300 and
1,200
Population
greater
than 1,200
Education - K - 12 6 7 9
Office 9 6 9
Public assembly 4 5 20
Public safety 10 8 12
Retail - other 21 24 22
Average (not including education) 8 10 12
Although there are not huge differences between community size and heating oil consumption,
differences are evident in electricity consumption. Non-residential buildings in larger communities appear
to consume more electricity per square foot than in small communities. The difference in consumption by
building size may be due to factors such as different ways in which the building is used (such as the number
of hours and type of services), the cost of electricity, or some other unknown factor.
Based on the average of all PCE communities, the non-residential electric consumption pattern is different
from the residential electric consumption. The extremes are not as pronounced as for residential.
Seasonal consumption patterns are not currently included in the modeling.
168 AEA analysis of multiple sources
February 2017 CHAPTER 4: Project Risks and Barriers Page | 99
CHAPTER 4: RISKS AND BARRIERS TO SUCCESSFUL ENERGY PROJECT
IMPLEMENTATION
Successful energy projects require a clear understanding of potential risks. For the purposes of the AkAES,
project success is defined as the development of a project that reduces the cost of energy in communities
by meeting project performance and economic life expectations. Any project development activity
contains risks, identifying these risks as early as possible improves the potential for success. When a
project fails to move forward because it is determined to be too risky or not economically viable the
developers can face criticism for money that was spent in the evaluation process. However, projects that
do not continue to construction can still provide useful information to communities and the State; halting
development avoids unnecessary additional expenditures.
Understanding energy project risk will help maximize project benefit for communities, consumers, and
the State. Unmitigated project risks can compromise the cost-effectiveness of a project by increasing its
cost and/or reducing its benefits. This can happen through reduced performance, a shorter economic life
or selection of a less-than-optimal project that stall before completion. Since the State’s limited energy
funding could be spent on many alternative projects, it is important to use the money as wisel y as possible,
especially as those funds shrink.
Key takeaways
Mitigating risks at each phase of project development will maximize potential project benefits.
1. General risks include lack of resources including skilled labor in villages and limited pool of
specialized contractors in Alaska; lack of leadership or stakeholder buy in; immature or
inappropriate technology; challenging economics and financing; poor project management or
maintenance; and weather or climate-related events.
2. Risks, including future operational and financing risks, should be thoroughly addressed in project
selection criteria. Many communities have pursued projects that are not likely to be cost-effective.
3. Project funding should be committed to projects that have community support and have examined
other potential technologies.
4. Programs should use standardized criteria to approve projects at each stage of development
before the decision is made to move forward.
5. All projects should have clear financing and business plans, from conception through operation.
6. The risk of project performance or economic life not meeting expectations applies to all project
and technology types, but can be mitigated through proper maintenance and training. Inadequate
maintenance is the chief barrier to performance.
7. Climate change is expected to increase the need for infrastructure funding in many parts of the
state.
February 2017 CHAPTER 4: Project Risks and Barriers Page | 100
Understanding and mitigating project risk becomes even more important in moving toward more loan-
based financing where energy projects must pay for themselves within their economic life. Without a clear
financing plan from conception through operation, projects are at much greater risk of being stalled or
cancelled. Energy projects will be unable to access financing unless risks are nearly completely mitigated
or the developer is pledging significant assets. Being able to pay back a long-term loan will require that
projects achieve the performance and economic life consistent with the expectations of the loan.
Note that reducing costs is not the sole motivation for community energy project developers. Projects
may be pursued for a number of reasons, not all of which will save consumers money. Some communities
may be willing to invest in a project to reduce their reliance on imported diesel fuel, typically increasing
price stability in the process, or they may want to create more jobs in the community. In each of these
cases, residents may be willing to pay more for energy if these other values are met. The tools developed
through the AkAES project will assist communities in achieving their energy goals, whateve r they are, at
the least cost.
DOCUMENTING AND ANALYZING ENERGY PROJECT RISKS AND BARRIERS
Risks and barriers to community energy projects in Alaska have not been formally documented for most
of Alaska’s energy programs. Although a number of best practice checklists have been developed, lessons
learned have generally been captured through an informal process.169 Moving forward, a more formal and
consistent method of program evaluation would help to solidify best practices and ensure more parties
beyond funders and project managers are involved in their development. Good examples of focused
learning through doing and sharing lessons learned exist within AEA’s biomass program and the Alaska
Wood Energy Development Task Group, which has organized many statewide meetings and tours to
demonstrate different biomass solutions and share successes and failures. Including requirements for
evaluation, measurement and verification (EM&V) at the program level would contribute to the body of
knowledge; however, there is a cost to EM&V programs that should be recognized and planned for.
Analysis of energy project risks and barriers in this chapter is primarily based on data from Alaska’s
Renewable Energy Fund (REF). No other state-funded Alaska energy program has as high a level of data
available from all phases of the project life cycle: from reconnaissance and feasibility through design,
development, construction, and operation. Additional datasets used in the AkAES risks and barriers
analysis include AEA’s Rural Power Systems Upgrade (RPSU) program, Emergency Assistance and
Preventative Maintenance program, and AEA’s former Bulk Fuel Loan program (now at the Division of
Community and Regional Affairs). These programs have captured some of the operational and financial
risks associated with existing diesel-based energy systems.
AEA examined REF projects throughout their project development life cycles starting with its initial
analysis of the project during the grant program’s competitive scoring process. The rest of this chapter
explores risks and barriers to energy project success through project selection, implementation, financing,
and operations. Additional insights are included from non-REF project analyses.
169 http://www.akenergyauthority.org/Programs/RenewableEnergyFund
February 2017 CHAPTER 4: Project Risks and Barriers Page | 101
One caveat is that no information is available about how or why projects were selected by REF applicants.
Lacking this, the risks and barriers analysis provides a retrospective look at the projects proposed for REF
funding, without comparison with projects that were not proposed. To more fully understand how to
reduce risks across the entire energy project lifecycle, considering initial project choice is critical, since
project selection limits the pursuit of other options.
CATALOGING THE MOST COMMON RISKS
Table 10 catalogs the most prevalent risks to successful energy project development and operation, based
on an analysis of state energy programs and other sources. While it may appear that risks increase with
each phase, the actual risk decreases since the risk at any given phase includes the risks associated with
all subsequent phases. The following risks, which are developed from data in the rest of this chapter, are
not presented in any particular order.
Table 10: Risks and barriers to successful energy projects
Development Risks Financial Risks Operational Risks
Sub-optimal project selection Funding availability Resource availability
Resource availability Cost overruns Integration with current system
Site control Risk of no return Fuel costs & availability
Project development skills Economic analysis Load changes
Community conflicts Future fuel costs Staff skills
Permitting & regulatory Power sales agreement Availability of parts
Not optimizing design Future load Business management
Skilled workforce Financial management Failure of machinery
Weather delays Lack of collateral Actual life of infrastructure
Supply chain & logistics Availability of infrastructure
Geotechnical issues Staff turnover
Transportation Planning for and performing maintenance
Competing projects Weather events
Transmission constraints Planning for repair and replacement
Competing projects
Technology maturity
LEAST COST PLANNING FOR COMMUNITIES
Unlike many states, Alaska does not currently have any requirements for utilities to perform long -term
resource planning that considers all generation and efficiency resources at least-cost service to customers
and consistency with State policy goals. Current rules allow economically regulated utilities to submit to
a prudency review after a project has been built, and unregulated utilities do not require any approval
from the Regulatory Commission of Alaska (RCA).
February 2017 CHAPTER 4: Project Risks and Barriers Page | 102
Through required procedures such as integrated resource and integrated distribution-system planning,
many other states provide a mechanism for utilities to identify, analyze, and pursue optimal projects to
ensure least-cost service to consumers. Integrating the supply- and demand-side resources available in a
community reduces costs to consumers, ensures a fair rate of return to the utility, and assists the State in
reaching policy objectives.170
Many states have a pre-approval process, generally referred to as “siting authority”, and a post-
construction approval process, a prudency review, to ensure that infrastructure is used, useful, and
prudent. “Useful” means that without the infrastructure either the service will be diminished or the costs
will be higher; “used” requires that the infrastructure provides service to customers, and “prudent” that
it was constructed properly, within a reasonable budget, and sized properly for the customer base. Since
utilities are natural monopolies and consumers do not have access to a perfect substitute or perfect
information, regulation provides a layer of consumer protection.171
Alaska’s ex-post-facto approval of new infrastructure diminishes the decision-making process for non-
standard infrastructure, particularly for identifying efficiency and demand-side management (DSM)
solutions for communities, and potentially increases costs to consumers unnecessarily. Most states allow
for either a return on the capital investment or performance-based return for efficiency or DSM
investments.172
PROJECT DEVELOPMENT
For the purposes of this chapter, project development is broken into two main activities: project analysis
and selection, and project implementation. Analysis and selection include the pre-construction activities
that help determine if a project should be built. Implementation covers construction and related
requirements.
PROJECT ANALYSIS AND SELECTION
As already noted, the AkAES risks and barriers study analyzed the projects applicants chose to submit for
REF funding. Future research into the process through which energy projects are proposed by
communities could offer valuable insight for improving energy project selection and how the state can
best assist communities and other project proponents in the earliest stages of project development.
Economic analysis
The metric AEA has used to determine cost-effectiveness in REF proposal evaluation is the benefit-cost
ratio (B/C ratio), which is equal to the present value of the project’s lifetime benefits divided by the
present value of its lifetime costs. Under this methodology, costs and benefits to all participa nts are
considered equally, so State grant funds are not treated differently than community matching funds, and
savings to the State’s PCE program are not treated differently than fuel cost savings to the community.
170 Jim Lazar. “Electricity Regulation in the US: A Guide.” Second Edition. The Regulatory Assistance Project. 2016.
http://www.raponline.org/wp-content/uploads/2016/07/rap-lazar-electricity-regulation-US-june-2016.pdf
171 Lazar, 2016.
172 Lazar, 2016.
February 2017 CHAPTER 4: Project Risks and Barriers Page | 103
A project with a B/C ratio greater than one is considered cost-effective, because the benefits outweigh
the costs. A project with a B/C ratio less than one is not cost-effective, because the benefits are less than
the costs. A B/C ratio equal to one means that the benefits equal the costs; this could be seen as equivalent
to a direct subsidy if the State were to provide all funding, in which the state’s investment (the cost) equals
the benefits (the subsidy) to the recipients. Investing in a project that is not cost-effective (a B/C less than
1) means that the State could have provided more benefit to the community by simply giving a direct
subsidy.
Because it is a ratio, the result of the B/C analysis does not provide information about the magnitude of
the benefits or costs. For instance, a small project with a B/C of 3.0 may only save the community a few
thousand dollars, whereas a large project with a B/C of 1.2 could potentially save a community millions of
dollars over its lifetime. That said, a number of factors in addition to the B/C ratio must be considered
when evaluating which projects will have the greatest impact on the community. It is also important to
note that the economics of projects evaluated for REF funding are based on a comparison with the status
quo, not other options within a community.
Any economic analysis of an energy project requires a number of assumptions to be made about the
project and the circumstances surrounding its construction, operations, and maintenance. These
assumptions may change over time as new information is available. For example, over the past 10 years,
crude oil price forecasts have varied dramatically. These assumptions can have a large impact on the
estimated benefits of a project, particularly as most REF projects are evaluated by the value of diesel
displaced over the proposed project’s lifetime.173
Figure 52 shows the results of an analysis of all REF grant applications submitted in the first eight rounds
of project funding, from 2008 through 2016. Project B/C ratios were grouped into three categories —
economic (greater than 1.3), marginal (1 to 1.3) and uneconomic (less than 1). The marginal range
represents a conservative estimate of economic viability. The REF evaluation process does not generally
include financing costs, return on investment, or taxes, all of which would increase the costs of a project.
The uncertainty of future diesel prices, and the fact that the annual Energy Information Administratio n
(EIA) fuel price projection has turned out to have been optimistic for each year of the REF, suggest that
the actual benefits are likely to be less than forecasted.
173 For more information on the REF proposal evaluation process please see
http://www.akenergyauthority.org/Programs/RenewableEnergyFund
February 2017 CHAPTER 4: Project Risks and Barriers Page | 104
Figure 52: Distribution of benefit-cost ratios for REF applications174
As can be seen in Figure 52, almost as many REF applications were for uneconomic as for economic
projects. A much smaller number were found to be marginal. This could either indicate that it is difficult
to find economic energy projects or that applicants have difficulty identifying them.
While there is a reduction in uneconomic applications moving from reconnaissance to feasibility and
construction, it is expected that uneconomic projects would be more thoroughly weeded out by
applicants. The fact that the REF is a grant program means that applicants may propose projects they
might not otherwise consider. On the other hand, a community, utility or IPP must still spend th e time
and money to apply for a REF grant, which they could have spent pursuing other potentially more
economic projects.
Technical risks and barriers to project success
In addition to the economic analysis of each REF application that is performed by AEA staff and contracted
economists, a technical review is also performed. While the quantitative technical scoring is useful for
understanding the soundness of individual projects, a qualitative analysis of reviewers’ comments is
invaluable for understanding the wide range of potential barriers to successful completion and operation
faced by energy projects in Alaska. For the purposes of this risk and barriers study, the comments from
the first eight rounds of funding have been analyzed and summarized in Figure 53. Barriers can be grouped
into five main categories:
1. Project management issues constitute the largest category of identified barrier. Specific barriers
included incomplete prior phases (14%), poor project scoping (11%), poor cost estimates (5%),
and lack of experience/expertise (5%);
2. Project identification was the next most prevalent category of barriers. Barriers included projects
that were not economic (17%), a better option for the community existed (7%), and adverse
impact on current system (6%);
174 AEA analysis of Rounds 1-9 of REF economic analyses
0%
25%
50%
75%
100%
Reconnaissance Feasibility Design ConstructionPercent of applicationsDistribution of benefit-cost ratios for REF applications by project phase
Source: AEA analysis of REF applications (2008-2016)
Economic
(B/C>1.3)
Marginal
(B/C between
1 & 1.3)
Uneconomic
(B/C<1)
February 2017 CHAPTER 4: Project Risks and Barriers Page | 105
3. Technology or resource barriers included: not technically feasible (3%), insufficient resource (4%),
and pre-commercial technology (9%);
4. Potential business issues included no power sales agreements with utilities 12%, and lack of
business plan (6%); and
5. Access to the site included environmental permitting (8%) and site control (4%).
Figure 53: Identified barriers of REF proposals175
*Note: More than one barrier was allowed per proposal
Over 40% of all applications—from all phases, technologies and resources—had identified barriers. While
the identification of a potential barrier does not automatically mean a project would not be successful.
It should be noted that, as a grant program, the requirements of the REF are not as strict as they would
be for a project seeking loan financing. Although some REF projects have accessed debt financing to
supplement their REF grant, a successful REF application should not be seen as an indicator that a project
would be successful in securing debt financing. In keeping with AEA’s mission to reduce the cost of energy
in Alaska, the REF has been willing to take risks to help lower the cost of energy in the communities it
serves. The REF’s willingness to accept risk in service of its mission is likely to be greater than that of other
potential investors.
175 AEA interviews with REF project manager and REF review comments
0%5%10%15%20%
Incomplete prior phases
Poor project scoping
Poor cost estimates
Lack of experience/expertise
Not economic
Better option(s) for community
Adverse impact on current system
Incomplete resource assessment
Pre-commercial tech
Insufficient resource
Not technically feasible
No agreements with utility
Lack of business plan
Environmental permitting
Site control
OtherProjectmanagementProjectidentificationTechnology orresourcePotentialbusinessissuesSite accessPercent of proposed projects with identified barrier*
Source: REF Stage 2 Comments, AEA project managers (Rounds 1-9)
February 2017 CHAPTER 4: Project Risks and Barriers Page | 106
PROJECT IMPLEMENTATION
After REF project proposals were evaluated and ranked, a second ranking was done to balance the projects
across regions. This step, required by statute, means that some projects received funding which otherwise
would not have. The Alaska Legislature makes the final decision on which projects to fund, but in most
rounds, the Legislature has accepted AEA’s recommendations.
The following three figures break down the risks faced by REF projects acr oss different dimensions to
understand what influences the chances of an energy project becoming operational. The factors that
proved most insightful were sorting the risks by project phase and project type, and cataloging the
identified barriers.
RISK BY PROJECT PHASE
In Figure 54, the status of projects is broken down into: 1) operational, 2) active (the grant is still open
and the REF project phase is not complete), and 3) not continuing to operation. Each of these
determinations was made by the project manager.
Figure 54: Status of REF projects by project phase176
The percentage of REF projects that become operational generally increases as the project phase gets
closer to construction. It is expected that many reconnaissance projects are not found to be viable. In fact,
using the best-case scenario assumption—that currently active projects continue to operation—
approximately 75% of reconnaissance projects will not lead to successful construction and operation.
Thus, statistically speaking, to get one operational project, four projects will need to be funded at the
reconnaissance level. Even for projects that have made it to construction, a small percentage will not
become operational.
It is a natural in any project development process for only a minority of projects to move through each
successive stage and eventually become operational. This is not unique to renewable energy projects but
is indicative of any endeavor that includes uncertainty. A careful and thorough review process is needed
176 AEA analysis of interviews with REF project managers
0%20%40%60%80%100%
Recon
Feasibility
Design
Construction
Status of REF projects by project phase
Source: AEA project managers (2016)
Operational Active grant or continuing to operation Not continuing to operation
February 2017 CHAPTER 4: Project Risks and Barriers Page | 107
at each stage to reduce that uncertainty and determine whether a project sho uld proceed or be counted
as an opportunity that did not prove viable.
One unexpected result of the analysis shown in Figure 54 is the anomaly of increased risk at the design
stage, where the percentage of projects not continuing to operation increases rel ative to the previous
(feasibility) phase. This is likely due to a large number of projects stalled at the design phase for lack of
funds to continue to construction. Since financing plans for REF proposals are only required to cover the
project’s current phase (the phase the application is written to fund), many applicants may not have
planned for financing beyond the REF. This is a deficit that should be addressed in any future framework
to support and encourage Alaska energy projects.
RISK BY RESOURCE TYPE
Breaking the same results out by resource type, Figure 55 provides interesting insight into the potential
risks of different types of energy projects. As might be expected, different resources come with varying
levels of uncertainty and risk. The least risky project types are additions to existing infrastructure, such as
hydro to heat, wind to heat, heat recovery, and heat pumps. Other resource types, especially geothermal
and hydrokinetic, are associated with significant uncertainty and high risk.
Figure 55: Status of REF projects by technology type177
Figure 55 illustrates that, regardless of project phase or resource type, there are a number of general
factors that will keep an energy project from becoming operational. In the case of hydrokinetics, it is often
a technology risk—a resource might be known and identified, but the technology is not sufficiently
mature. In other cases, the resource itself may be insufficient, which is not an uncommon reason for wind
177 AEA analysis of interviews with REF project managers
0%20%40%60%80%100%
Hydro (heat)
Wind (heat)
Solar
Heat Pump
Heat Recovery
Other
Biofuel (heat)
Biomass
Wind
Transmission, Other
Hydro
Geothermal
Hydrokinetic
Status of REF projects by resource type
Source: AEA project managers and AEA data
Operational Active grant or continuing to operation Not continuing to operation
February 2017 CHAPTER 4: Project Risks and Barriers Page | 108
and hydro projects not to proceed. Other factors cut across all project and resource types, including
financial and management issues and complications of integrating a new project into an existing system.
The data for this analysis came from AEA project managers and gran t close-out documentation; more
than one reason was allowed per project.
Figure 56: Reasons for REF projects not continuing to construction178
Comparing Figure 56 with Figure 53 on page 105 which shows a similar analysis for REF applications, the
real barriers to energy project success become apparent. The most common single reason for Alaska
energy projects not to continue to operation is challenging economics. Other common reasons included
land use restrictions, lack of agreement with the utility, competing or better projects in the community,
and adverse impacts or other upgrades needed to the current system. Some of these risks can be
mitigated, while others require careful consideration and objective analysis to determine if a fatal flaw
exists at the earliest possible stage in the project development cycle.
In many cases, the most important lesson learned with regards to reducing project risk is to simply ensure
project managers, consultants, and contractors have sufficient experience and a demonstrated track
record of completing successful projects to be able to address the risks in Figure 56.
Cost overruns during construction also increase the risk that a project will not be cost -effective over its
economic life. Because REF grants are generally awarded for a single phase of a project, data on the total
cost of the project is not always available, making it difficult to know the prevalence of project cost
overruns. Even within the funded phase, cost overruns may be covered by the grantee and not reported
to AEA if they exceed required matching funds. Efforts to retroactively collect total project cost data from
178 AEA analysis of interviews with REF project managers
0%5%10%15%20%25%30%
Other reasons
Poor design
Other upgrades needed
Competing project(s)
No agreement with utility
Unspecified technical issues
Insufficient demand
Land use restrictions
Insufficient resource
Low community priority or no champion
Insufficient funding
Challenged economics
Percent of non-operational REF projects
Reasons why REF projects are not expected to continue
Source: AEA project managers (2016)
February 2017 CHAPTER 4: Project Risks and Barriers Page | 109
REF grantees have not been a priority until recently. Closeout documents for the past year or two have
reported the total project cost for construction projects.
FINANCIAL RISKS
Financial risk covers many types of risk typically associated with project financing, including the
uncertainty of return and the potential for financial loss or default on a loan. Here we include the risk of
a project not proceeding to construction due to failure to find funding. The second most common reason
for REF projects to stall or be cancelled is insufficient funding—an indication that many projects relied on
REF or other grant funding to bring the project to completion. This means that without a clear financing
plan, from conception through operation, the money spent on a project could have been spent more
productively elsewhere.
Financial literacy and capacity has been identified as a major impediment for private investment in rural
communities.179, 180 State loan programs have reported that applicant financial reporting was frequently
insufficient to provide loans without significant assistance.181 Analysis of utility reports to the RCA, IRS,
and/or the State showed inconsistencies in financial reporting.182
An analysis of debt ratios for 30 utilities, which provide power to over 90 communities, showed that many
communities within the AkAES study area had limited experience with project financing other than grant-
funded projects. Additionally, the study noted that over 40% had reported operational losses, which make
it difficult for the utility to access debt financing.183
In many cases, the assets a utility or community carries on its books are be counted as collateral for the
purposes of qualifying for a loan. For example, in order to receive a Bulk Fuel Loan from the State of
Alaska, additional security is required in the form of the assignment of payments from other State
programs. This is because fuel is not easily sold or moved once it has been delivered to a community. Even
with this requirement, AEA declined approximately 20% of Bulk Fuel Loan applications between 2000 and
2013. Figure 57 shows the reasons why applications were declined.
179 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” Alaska Center for Energy and Power. December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
180 Riley Allen, Donna Brutkoski, David Farnsworth, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.’ December
2015. https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
181 University of Alaska Center for Economic Development. “Utility Financial Analysis and Benchmarking Study.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/Utilityfinancialanalysisandbenchmarkingstudy.
pdf
182 UACED 2016
183 UACED 2016
February 2017 CHAPTER 4: Project Risks and Barriers Page | 110
Figure 57: Reasons for AEA Bulk Fuel Loan applications being declined184
Over 120 communities are included in the Bulk Fuel Loan dataset, so it provides a good cross -section of
the communities within the AkAES region. It is a fair assumption that the difficulties experienced by the
Bulk Fuel Loan program would also be experienced by other entities that would consider lending to the
same communities and utilities, especially as a State program, the Bulk Fuel Loan program is less risk
averse than a private lender would be.
As can be seen in Figure 57, numerous reasons exist for why loans were declined, all of which would make
it difficult for these entities to access private financing. From not paying back previous loans to not having
a way to secure the loans, to a general lack of financial information to evalute the creditworthiness of the
applicant, a number of improvements to financial and managerial practices are needed if the State expects
that more communities will be able to access debt financing.
Figure 58: Percent of Bulk Fuel Loans declined by region185
184 AEA analysis of Bulk Fuel Loan program data (2000-2013)
185 AEA analysis of Bulk Fuel Loan program data (2000-2013)
0%5%10%15%20%25%
Non-responsive applicant
Unpaid loans
Multiple reasons
Lack of collateral
Unspecified
Application expired
No financial statements
Uncreditworthy
Other
Refused assignment of securities
Percent of declined applications
Reasons for AEA Bulk Fuel Loan applications being declined
Source: AEA Bulk Fuel Loan data (2000-2013)
0%5%10%15%20%25%30%35%
Railbelt
Kodiak
Northwest Arctic
Lower Yukon-Kuskokwim
Aleutians
Yukon-Koyukuk/Upper Tanana
Southeast
Bering Straits
Bristol Bay
Percent of all applications from region
Percent of Bulk Fuel Loans declined by region
Source: AEA Bulk Fuel Loan data (2000-2013)
Average rate of
decline for all
loans—20%
February 2017 CHAPTER 4: Project Risks and Barriers Page | 111
There appear to be some regional differences in the rate of applications being declined, shown in Figure
58. The Bristol Bay and Bering Straits regions were the most likely to be declined and the Kodiak and
Railbelt regions the least likely.
Trying to develop an economy of scale for energy projects in a community may encounter new financial
complications. In 2014-15, Nuvista Light and Electric Cooperative worked to create a model to finance
efficiency projects in multiple non-residential buildings with the aim of developing an economy of scale.
Numerous complications were encountered, some of which are unique to rural Alaska. There was a
general lack of financial capacity from potential applicants, particularly the non-profit participants. The
entities that did have financial capacity, for-profit businesses and Native corporations, were unwilling to
take on the financial risks of those with less capacity. For numerous reasons, building owners do not
necessarily own the land the building rests on which made it difficult to get a loan. Since most commercial
loans do not accept the savings associated with efficiency upgrades as a way to secure a loan, the
unsecured loans that were available required 12-14% interest, which made many efficiency measures
uneconomic. Nuvista is still actively working to solve these issues.186
Other State and federal energy programs, such as the RPSU, budget a sufficient amount to cover the entire
scope of the project, thus reducing the risk that a project will stall due to insufficient funding, but placing
the entire financial burden and risk on the State and/or federal funding agency.
COST OF EQUITY AS A MEASURE OF RISK
Another way to understand the financial risk associated with energy projects is to look at the return an
investor would require in compensation for that risk. Although limited empirical data is available from
Alaska to help understand the risks for different project types and areas, other methods exist to estimate
the cost of equity. Work performed for the AkAES uses the volatility of sales among Alaska’s rural utilities
as a basis of analysis, since the cost of equity is a measure of the market and revenue risk associated with
a utility.187 A higher cost of equity indicates greater risk and can be expected to increase costs to
consumers.
186 Tiffany Zulkosky, former executive director of Nuvista Light and Electric Cooperative, personal communication December 16,
2016.
187 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
February 2017 CHAPTER 4: Project Risks and Barriers Page | 112
Figure 59: Cost of equity estimate vs. annual sales for PCE utilities188
Figure 59 shows that smaller utilities often have a higher cost of equity (COE). The increased COE is based
on the higher expected uncertainty in net revenue and cash flow. In order to cover these risks and attract
private capital, a greater return on equity is required by investors. In grant-funded projects, the risks are
absorbed by the state or federal government that is granting the infrastructure to the utilities.189 Since
the utilities do not have equity in the project, a return on equity is not needed. If grant-funding decreases
and utilities have more equity invested in future infrastructure projects, the risk from net revenue and
cash flow volatility can be partially mitigated through various rate-setting mechanisms, and/or different
types of insurance could be made available to reduce the risks associated with cash flow and net revenue
volatility.
There are two main potential solutions for reducing risk associated with revenue: 1) increasing fixed
charges or 2) move from a rate-based to a revenue-based system. Although passing fixed costs as a fixed
charge will remove some of the revenue volatility, it would disproportionately affect low -income
consumers, who tend to use less electricity, and remove some of the incentive of conserving energy.190 A
revenue-based system, also referred to as “decoupled,” ensures that the revenue needed to operate the
188 Foster and Townsend, 2017.
189 Foster and Townsend, 2017.
190 Janine Migden-Ostrander. “Technical Conference: Alternative Cost Recovery Mechanisms.” Presentation to Maryland Public
Service Commission. October 20, 2015. http://www.raponline.org/wp-content/uploads/2016/05/rap-jmo-mdpsc-
altcostrecmech-2015-oct-20.pdf
15%
16%
17%
18%
19%
20%
21%
22%
0 10 20 30 40 50 60Cost of equity estimateAnnual Sales (million kWh)
Cost of Equity Estimates vs. Annual Sales
Source: Adapted from MAFA (2016) Largemuni/ regional IOU 15-25MVillage utility<1MSmallmuni/co-op1-5MMediummuni/ co-op 5-12MLargeregional co-op 60MSmall village-
scale utilities'
cost of equity is
reduced by 4.5%
when they join a
large regional
cooperative
February 2017 CHAPTER 4: Project Risks and Barriers Page | 113
utility can be earned, even with volatile or declining sales. A revenue-based system can also provide for
greater incentives for utilities to increase the efficiency of their customers, and incentives that do not exist
with traditional rate-making. Downsides of decoupling are the care required in determining the revenue
requirements for utilities and the greater amount of involvement needed to adjust rates to achieve the
required revenue.191
As Figure 59 shows, consolidating utilities into larger organizations also decreases the cost of equity by
effectively spreading the risk over the entire system. There are some circumstances in which the risk
cannot be mitigated through fixed changes and/or insurance and make it such that private investments
are not viable at any rate of return.
Figure 59 also estimates the amount of return on equity that an independent power producer (IPP) may
require in communities eligible for PCE. Unless the project decreases generation costs, the required return
on equity would increase cost to consumers.
PROJECT OPERATION
The economic analysis performed as part of the evaluation of all REF grant applicatio ns makes certain
assumptions about the expected performance and economic life of the project. If it does not perform as
expected or its useful life is shorter than expected, the project may not end up being cost-effective.
Performance risks include the risks that the project, when complete, fails to perform as intended
or fails to meet business requirements that justified it. Poor design or technology choice,
inadequate maintenance and poor management all increase performance risks, as well as other
factors that may be beyond a utility’s control. If the project was primarily grant-funded, this may not
create financial difficulties for the community. However, if the underperforming project was partially or
completely debt-financed, the community or utility may have to continue to pay for infrastructure that is
inoperable or does not generate enough revenue to pay back the loans.
For many of the State’s energy programs, there is not sufficient long-term tracking of projects to
understand other factors that influence long-term performance. The State is generally not the owner of
community energy systems, and grant agreements typically give the infrastructure to the grantee. After
the State has transferred grant-funded project to the community or utility, the State is no longer
responsible for it, and the performance and longevity are the responsibility of the utility.
REF grant agreements mandate performance reporting at a fairly coarse level for the first 10 years of
operation (five years for earlier projects), so AEA can determine if the project is meeting performance
expectations. The reporting has not always been consistent with the specific infrastructure paid for by the
grant. For example, a community might report all the power produced by a wind farm even if the REF only
funded one of the turbines.
If a project is to be loan financed, it is especially important to be able to accurately estimate its future
performance. Any modeling is only as good as the inputs and assumptions, and operational projects are
the best source for predicting how future projects will perform. While REF-funded projects have not been
191 Jim Lazar. “Electricity Regulation in the U.S.: A Guide.” Second Edition. The Regulatory Assistance Project. 2016.
http://www.raponline.org/wp-content/uploads/2016/07/rap-lazar-electricity-regulation-US-june-2016.pdf
February 2017 CHAPTER 4: Project Risks and Barriers Page | 114
operational long enough to know if their full economic lives will be reached, there are a minority of
operational projects that have already experienced issues affecting their performance, as shown in Figure
60.
Figure 60: Reported barriers to REF project performance192
Approximately 35% of operational REF projects were identified as not meeting performance expectations,
either through performance reporting or interviews with AEA project managers. The primary reason for
projects not meeting expectations is maintenance issues, which is consistent with anecdotal evidence
collected from other state energy programs. Failures with wind turbines catching fire are prevalent
enough to be tied as the second most common issue along with poor design/equipment choice, poor
economics, and the community or utility choosing a different energy source. Some of the barriers reported
in Figure 60 have led to projects not being operational. While none is completely external to the project,
the steep drop in oil prices has led to the curtailment of at least one project. Almost all the identified
barriers could be successfully mitigated through pre- or post-operational planning by the project owner.
Non-REF renewable energy projects have also shown operational risks if preventative maintenance is not
performed. Recently, Sitka had to shut down its Green Lake hydroelectric power plant, forcing it to switch
to backup diesel generators, to fix an issue, at least partially caused by inadequate inspections and
preventative maintenance.193
OPERATIONAL RISKS OF DIESEL POWER PLANTS
The Rural Power System Upgrade program (RPSU) is an another state program that yields insight into the
operational risks facing rural energy infrastructure projects. The RPSU program provides a good baseline
192 AEA analysis of interviews with REF project managers and REF performance reports
193 Emily Kwong. KCAW. “Green Lake dam awaits replacement part to get back up and running.” December 26, 2016.
http://www.alaskapublic.org/2016/12/26/green-lake-dam-awaits-replacement-part-to-get-back-up-and-running/
0%2%4%6%8%10%
No business plan
Other environmental issues
Lower than expected load
Technical challenges
Other energy source chosen
Not economic to operate
Poor design and/or equipment choice
Turbine caught fire
Maintenance issues
Percent of operational projects citing the barrier
Barriers to REF projects performing to expectation
Source: REF performance data and AEA project managers
February 2017 CHAPTER 4: Project Risks and Barriers Page | 115
for analysis, because we know when a powerhouse was constructed. This helps eliminate the variable of
infrastructure age and focus the analysis on how operations and maintenance impact performance.
RPSU projects are intended to provide safe, stable, and reliable power to communities. Improving the
efficiency of electric generation is a close second priority, but not the primary goal of the RPSU. AEA
analyzed 32 RPSU projects commissioned between 2001 and 2009. Overall, the RPSU projects analyzed
were more efficient after the project, with a 10% average increase in efficiency. After projects were
commissioned and transferred to the community, the trends were more site-specific, with about half of
communities experiencing a general positive trend for efficiency and the other half experiencing declining
efficiency.
Line loss is another performance measure that can be partially analyzed with available data. The design
specification is 8% loss. Line loss is reported through the PCE program, but is defined as the amount of
unsold electricity (the difference between generation and sales). If there are reporting errors for either
sales or generation, the utility’s line loss number will be affected, regardless of the amount of actual loss
in kWh delivered through the utility’s distribution system. Given the numerous ways in which distribution
systems can lose energy, it is not always easy to identify and address the causes of line loss. For the 32
projects analyzed, only one utility met the long-term line loss expectation of 8%; others ranged up to 31%
loss. Because there was significant year-to-year variability, no meaningful trends in line loss could be
found at the community level. Despite potential reporting errors, line loss appears to be a significant yet
fixable performance issue that, if addressed, would reduce the cost of energy in AkAES communities. This
data reinforces the need for access to skilled technicians to assist communities with diagnosing and fixing
distribution issues.
Replacing a powerhouse or distribution system is generally not done for economic reasons, but to ensure
the safety and reliability of the power system. Nonetheless, diesel efficiency and line loss are performance
issues that must be taken into account when evaluating opportunities to make energy more affordable,
and they are important measures of whether an energy project will be cost-effective.
The expected operational life of a properly maintained powerhouse is 30 years. An analysis of AEA’s
Electrical Emergency Program showed that 23 of 32 RPSU projects built between 2000 and 2009
experienced emergencies after completion that were unassociated with project design or construction,
at a reported cost of almost $800,000. This data validates the institutional knowledge that proper training
for utility operators and managers is critically important.
Figure 61 shows an analysis by issue type of all electrical emergency response events from 2005 to 2015,
not just those associated with an RPSU project. Few of the emergency response calls can be ascribed to
natural causes. Engine failure and generator issues are most commonly due to poor maintenance. Some
distribution faults could be due to storms or other weather events, but it is difficult to know from the
data.
February 2017 CHAPTER 4: Project Risks and Barriers Page | 116
Figure 61: Number of electrical emergency response by type provided by AEA194
OPERATIONAL RISKS OF ENERGY EFFICIENCY PROJECTS
Building energy efficiency projects are subject to fewer project development risk factors, but potential
operational risks still need to be recognized and mitigated. Few evaluations of completed energy
efficiency projects have been performed in Alaska, and while it can be dangerous to extrapolate from just
a few case studies, the analyses of two Village Energy Efficiency Projects (VEEP) in Nightmute and
Shishmaref offer useful insights.
Nightmute underwent a whole village retrofit (WVR) in 2008 to 2009 that included retrofits to residential
and non-residential buildings. In November 2014, AEA sent a team representing state and regional
organizations that had been involved in the retrofits to learn what had worked and what could be
improved about the whole village retrofit concept. Overall, the team found that the WVR has been
successful, though it recommended a number of improvements that are relevant to this AkAES study.
One barrier to evaluating the effectiveness of the WVR project was lack of data. Baseline energy use data
from before the WVR was almost wholly lacking for both heating and electricity. In many cases, post-
retrofit consumption data was also not available. Still, an energy auditor was able to conduct walk-through
inspections of the retrofitted buildings and perform blower door tests, the results of which were
compared with tests and inspections done after the WVR was completed. Based on these findings, most
of the efficiency measures, both thermal and electric, were still performing as expected five years later.
In both residential and non-residential buildings, it was apparent that ongoing maintenance was needed
to keep air leakage at a minimum. This is a particular problem in areas known for building foundation
movement.195
194 AEA analysis of AEA’s emergency response program (2005-2015)
195 Katie Conway. “Nightmute Whole Village Retrofit—then and now.” Alaska Energy Authority. January 15, 2015.
http://www.akenergyauthority.org/Content/Efficiency/Veep/Documents/NightmuteWVR20082014FINAL11515.docx
0 25 50 75 100
Engine failure
Distribution fault
Other
Generator issue
Transmission issue
Switchgear issue
Tranformer failure
Number of electrical emergency response by type provided by AEA
Source: AEA data (2005-2015)
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
February 2017 CHAPTER 4: Project Risks and Barriers Page | 117
The 2010-2011 VEEP project in Shishmaref was evaluated in 2013 with Denali Commission funding. In this
case, the evaluators did not find that all the expected savings had been realized. They found that sa vings
were initially overestimated, particularly by not valuing the lost heat resulting from increased electric
efficiency. They also found that the building occupants had changed their behavior and were consuming
more energy, primarily through increased hours of operation. This does not negate the savings from
increased efficiency, but it does highlight a risk that if electrical bills do not go down, building occupants
may discount a project’s effectiveness, particularly if post-retrofit evaluations are not performed. The
Shishmaref case study underscores the need for realistic savings estimates and thoughtful messaging to
occupants.196 Some of the same operational issues, such as inadequate maintenance, that were evident
in the Nightmute case study were also present in Shishmaref.
CLIMATE CHANGE
It is likely that the impacts of rising sea levels, loss of sea ice (which protects coastal communities from
winter storm surges), and thawing permafrost will have significant, but currently unknown, impacts on
Alaska’s energy infrastructure. AEA’s work has been to identify specific challenges to infrastructure that
have the potential to increase costs and risks due to climate change.
Several of the bulk fuel tank farms built with Denali Commission funds since 2000 have been impacted by
flooding and coastal erosion that climate change has likely exacerbated. In Port Heiden, a 221,000-gallon
tank farm, constructed in 2002 for $1.3 million, was relocated due to coastal erosion in 2015 at an
estimated cost of $1.6 million.197
In 2009, the federal General Accountability Office (GAO) reported that 31 Alaska villages face imminent
threats from flooding and erosion. In 2009, 12 of these communities were exploring relocation options.
Relocation will require moving or rebuilding a community’s energy and sanitation infrastructure including
powerhouses, transmission and distribution lines, heat recovery loops, tank farms, and water and sewer
infrastructure. It is expected that the threats to communities will increase if Arctic temperatures continue
to rise as predicted.198
In areas with permafrost, damage to buildings due to the ground warming is well documented. Even
without a warming climate, buildings can warm and melt the permafrost, an issue that can be mitigated
in building design but could be exacerbated by rising temperatures. As seen in Nightmute, building
maintenance is an important part of preserving the effectiveness of weatherization activities and livability
of the housing stock.199
196 Armstrong, Richard. “Measurement and Verification Review of 2010/2011 VEEP & EECBG Energy Efficiency Retrofits.”
December 17, 2013.
197 Alaska Energy Authority. “Bulk Fuel Inventory Assessment Report.” 2016.
198 General Accountability Office. GAO-09-551. “Alaska Native Villages: Limited Progress Has Been Made on Relocating Villages
Threatened by Flooding and Erosion.” 2009. http://www.gao.gov/new.items/d09551.pdf
199 Conway, 2015.
February 2017 CHAPTER 4: Project Risks and Barriers Page | 118
Commonwealth North expects that energy infrastructure costs will increase, at least in response to
climate change.200 In 2008, a group of engineers and economists from Alaska and Colorado estimated the
additional community infrastructure costs due to climate change through 2030. Their model, which
included more than just energy infrastructure, estimated that climate change would likely increase
infrastructure costs 10 to 20% above normal wear and tear, amounting to an additional $3.6 to $6.1 billion
in needed infrastructure investment across Alaska.201 Using the estimates for power plants and bulk fuel
facilities developed in Chapter 2, this would indicate that climate change could require an additional $3.5
to $7 million in annual energy infrastructure spending in the communities with less than 2,000 people.
200 Commonwealth North. “Energy for a Sustainable Alaska: The Rural Conundrum.” February 2012.
http://www.commonwealthnorth.org/download/Reports/2012_CWN%20Report%20-
%20Energy%20for%20a%20Sustainable%20Alaska%20-%20The%20Rural%20Conundrum.pdf
201 Larsen, P.H., et al., Estimating future costs for Alaska public infrastructure at risk from climate change. Global
Environmental Change (2008), http://climatechange.alaska.gov/aag/docs/O97F18069.pdf
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 119
CHAPTER 5: THE IMPACT OF PROGRAMS ON ENERGY AFFORDABILITY AND
STATE ENERGY POLICIES
This chapter investigates current and historical State energy programs to see how they have impacted
energy affordability across the AkAES study area. The State has four primary mechanisms for achieving its
policy objectives—direct funding, technical assistance, statutory or regulatory requirements, and
disincentives (such as taxes). Given limited methods and financial resources for affecting change, it is
important to understand how different types of programs have benefited communities so that methods
can be improved and public funding used more efficiently over time.
In Alaska, more than a dozen individual State and federal energy programs assist communities with
reducing energy costs. In many cases, the State and federal programs work in concert, with the State
Key takeaways
1. Federal capital grants and State and federal direct consumer subsidies have had the biggest
impact in reducing energy costs in the AkAES study area to date.
2. Programs that have increased energy affordability in the study area include the Rural Power
System Upgrade (RPSU), Bulk Fuel Upgrade (BFU), Renewable Energy Fund (REF), Power Cost
Equalization (PCE), Alaska Heating Assistance Program (AKHAP), and the Weatherization and
Village Energy Efficiency Program (VEEP) energy efficiency programs.
3. State energy programs that have primarily served the Railbelt and urban areas include the
Home Energy Rebate/New Home Rebate programs and the Sustainable Energy Transmission
and Supply (SETS) loan.
4. Some State energy programs provide their primary benefits to AkAES communities and help
protect the State’s investment by ensuring the safety and reliability of rural energy
infrastructure, including RPSU, BFU, Circuit Rider, Electrical Emergency Response, and other
training and technical assistance programs.
5. There is an opportunity to capture greater and more lasting generation efficiency
improvements by creating new incentives or requirements for lifetime operations and
maintenance, including ongoing performance tracking and reporting for publicly funded
projects.
6. Loan and other debt financing programs, by themselves, are unlikely to incentivize new
renewable energy or energy efficiency projects until technical, communication, and financial
barriers to participation are addressed.
7. More robust community-level data is needed to better analyze the cost-effectiveness of State
energy programs on affordability.
8. The State can make more progress on achieving the energy sustainability policy goals
established in 2010 (15% increase in energy efficiency by 2020, 50% of renewable energy by
2025) if goals are supported by greater accountability, new reporting requirements to track
progress, continued technical assistance, and more capacity building for rural projects.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 120
supplementing the federal program, or vice versa. This chapter will focus on State energy programs, with
federal data included where appropriate. The chapter is organized into two main sections. The first section
provides a brief analysis of core State energy programs. Based on the availability of data and previous
evaluations, each program analysis includes a description of the total funding over time by source, the
regional spread of funding, and the savings and benefits to those regions. The last section describes how
those programs help advance the State’s sustainable energy goals: the goal of improving per capita energy
efficiency by 15% by 2020, and the goal of generating 50% of statewide electricity from renewable sources
by 2025.
STATE ENERGY PROGRAMS
State energy programs are administered by seven agencies and divisions:
1. Alaska Energy Authority (AEA): Rural Power System Upgrade program (RPSU), Bulk Fuel Upgrade
program (BFU), Renewable Energy Fund (REF), Power Project Loan fund (PPF), Village Energy
Efficiency Program (VEEP), and administered the Bulk Fuel Loan program until 2013
2. Alaska Housing Finance Corporation (AHFC): Weatherization Assistance Program (Wx), Home
Energy Rebate program (HER), Home Energy Loan, Alaska Energy Efficiency Revolving Loan Fund,
and Energy Efficiency Interest Rate Reduction (EEIRR)
3. Department of Health and Social Services (DHSS): Low-income Heating Assistance Program
(LIHEAP) and the Alaska Heating Assistance Program (AKHAP)
4. Department of Commerce, Community, and Economic Development (DCCED): Alternative Energy
and Conservation Loan
5. Department of Transportation and Public Facilities (DOT&PF): Public Facilities Energy Efficiency
Improvement Program
6. Division of Community and Regional Affairs (DCRA) at DCCED: Bulk Fuel Loan and Bulk Fuel Bridge
Loan programs
7. Alaska Industrial Development and Export Authority (AIDEA): Sustainable Energy Transmission
and Supply (SETS) program and commercial loan program
The Department of Natural Resources oil and gas tax programs , the Alaska Gasline Development
Corporation, and the Regulatory Commission of Alaska, which regulates electric utilities and natural gas
utilities in the study area, are not included in this program review.
Since the State cannot change federal programs, this section does not include analysis of federal
programs, except where they supplement or are supplemented by State energy programs. The ability of
communities to access federal programs and of the State to coordinate with them will be increasingly
important as State energy funds become more scarce and federal funding assumes a larger role.
A short analysis of each State energy program follows, organized by type of funding:
1. State capital grant programs
2. State energy subsidies
3. State energy loans
4. Other state energy programs
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 121
The high-level analysis of program outcomes in this chapter is based on the best publicly available data
and formal program evaluations, where available. Due to the challenges described in Chapter 1 of defining
“affordable” in a way that works as an objective policy measure, programs were not evaluated against a
single metric. Where no reliable quantitative data exists, gaps have been bridged with qualitative data,
including information from program managers, staff, and beneficiaries.
Although the Railbelt is excluded from the study area, Railbelt data is included in some analyses in order
to evaluate how effectively each program has addressed the needs of the AkAES target area and has
contributed to progress on statewide sustainable energy goals.
STATE CAPITAL GRANT PROGRAMS
Along with the Power Cost Equalization (PCE) Program, State capital grants have provided the majority of
state energy funding in the AkAES region. These include grants for residential efficiency, electrical
generation, renewable energy and bulk fuel storage. In many cases, State capital grants have been
supplemented by funding from federal sources. Where possible, federal and local contributions were
identified for each of the programs evaluated.
Rural Power System Upgrade program
Established under 3 AAC 108.100 – 130, AEA’s Rural Power Systems Upgrade (RPSU) program provides
financial and technical assistance to rural electric utilities, including grant funding for the construction of
power generation and related infrastructure and utility operations training for eligible recipients.
Upgrades may include powerhouse upgrades or replacements, intertie assessments, distribution lines to
new customers, heat recovery, and repairs to generation and distribution systems. Funding for the RPSU
program depends on State legislative appropriations, federal Denali Commission grants and other
matching funds.202
RPSU projects must meet eligibility criteria, and they are ranked and chosen through a non -competitive
process.203 Every 10 years an inventory and evaluation of powerhouse infrastructure in eligible
communities is performed; the most recent was completed in 2012.204 To be eligible, communities must
have a population between 20 and 2,000, not be predominately a military or industrial site, and not be
connected to the Railbelt, Four Dam Pool, or Juneau power distribution systems.205 Communities are then
ranked by the condition of the power generation and distribution infrastructure. The financial ability of
the community or utility to pay for the infrastructure is not a criterion for selection. Basing the non-
competitive selection process on the age and disrepair of the generation infrastructure could create an
unintentional incentive for not maintaining infrastructure.206
202 AEA Rural Power System Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
203 3 AAC 108.110, http://www.touchngo.com/lglcntr/akstats/aac/title03/chapter108/section110.htm
204 See Alaska Energy Data Gateway (https://akenergygateway.alaska.edu/)
205 3 AAC 108.110, http://www.touchngo.com/lglcntr/akstats/aac/title03/chapter108/section110.htm
206 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 122
Figure 62: Rural Power System Upgrade Program for AEA and AVEC by funding by year and source207
Figure 62 includes all state and federal funding for rural power systems over the past 15 years. The Denali
Commission provided over $170 million dollars to communities through AEA and the Alaska Village Electric
Cooperative (AVEC). The State contributed another $19.5 million over the same period. Other matches
include funding from the U.S. Department of Agriculture (USDA), local communities and AVEC. The total
budget for these years was $183 million, an average of approximately $12 million/year.
Figure 63: Distribution of Rural Power System Upgrade funding by AEA energy regions (2000-2015)208
With the largest population and the most communities, the Lower Yukon-Kuskokwim region also received
the most RPSU funding, almost $53 million in federal and State funds. Bristol Bay, Bering Straits, Yukon-
207 Data compiled from Denali Commission database and AEA financial data
208 Data compiled from Denali Commission database and AEA (2000-2015)
$0
$20,000,000
$40,000,000
$60,000,000
$80,000,000
$100,000,000
2001 2002 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Total budget per yearRural Power System Upgrade program for AEA and AVEC funding by year
and source
Sources: Denali Commission database and AEA data
Other Match
State Match
Denali Commission
Budget to Other
Denali Commission
Budget to AVEC
Denali Commission
Budget to AEA
$0 $10,000,000 $20,000,000 $30,000,000 $40,000,000 $50,000,000 $60,000,000
Kodiak
Copper River/Chugach
Northwest Arctic
Aleutians
Yukon-Koyukuk/Upper Tanana
Southeast
Bering Straits
Bristol Bay
Lower Yukon-Kuskokwim
Distribution of Rural Power System Upgrade funding by AEA energy regions
Sources: Denali Commission database and AEA (2000-2015)
Denali Commission State Other match
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 123
Koyukuk/Upper Tanana and Aleutians received between $17 and $30 million over the 15 years. The
Northwest Arctic, Copper River/Chugach, and Kodiak regions all received significantly less. Much of the
Copper Valley/Chugach region is connected by intertie. Similarly, on Kodiak, the regional electric
association serves the majority of the population, while five villages rely on small, independent
powerhouses.
The program’s impact on generation efficiency and residential rates can be analyzed using program data
in combination with PCE data. AEA restricted its analysis to RPSU projects that would provide at least five
years of operational data in order to identify longer-term trends. This included projects completed
between 2000 and 2009. The costs for these projects ranged from $400,000 to $3.25 million. The majority
involved construction of new powerhouses, but hydro and distribution projects were also funded during
this time.
It should be noted that reducing the cost of energy is
not the main purpose of the RPSU program, and it
would be unfair to evaluate the program solely through
that lens. The RPSU program’s primary mission is
ensuring safe, reliable, and stable power by assisting
rural electric utilities in upgrading their infrastructure.
Prior to the RPSU program, many of the powerhouses
in rural Alaska communities were unreliable, in poor
condition, and in some cases, dangerous. Anecdotes
from AEA staff indicate that it was not uncommon in the 1970s and 1980s for multiple powerhouses to
burn down each year.209
While not the RPSU program’s main goal, better generation efficiency and heat recovery are some of the
main ways that the program can help make energy more affordable in the rural communities it serves.
After a project has been completed and the equipment or other infrastructure transferred to the
community, AEA is no longer responsible for the project. The performance and longevity of the new or
upgraded infrastructure become the responsibility of the utility. As a result, the long-term effect on the
operational efficiency of an RPSU project is heavily contingent on the day-to-day operations of the local
utility.
The average long-term improvement in diesel generation efficiency from RPSU projects was
approximately 10%, based on an analysis of PCE and RPSU program data for projects completed between
2001 and 2009. Figure 64 provides a regional look at the data. The results represent the difference
between the average diesel efficiency for five or more years before and after a project was complete.
209 Kris Noonan, personal communication. December 6, 2016.
… reducing the cost of energy is not the
main purpose of the RPSU program, and
it would be unfair to evaluate the
program solely through that lens.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 124
Figure 64: Change in powerhouse efficiency after RPSU project210
As Figure 64 illustrates, there is considerable variability in the long-term results. The biggest improvement
by a utility was 30%, while several others actually saw reductions in generation efficiency in the years
following their projects. Even among utilities initially experiencing big improvements, performance
tended to decline over time, bringing the utility back nearer to its pre-RPSU baseline. This underscores
the importance of following good operations and maintenance protocols. It also represents an
opportunity to capture greater and more lasting efficiency improvements by creating new incentives or
requirements for post-project operations and maintenance (O&M), including ongoing performance
tracking and reporting.
Similarly, most communities did not maintain the line loss design expectation of 8% after infrastructure
was turned over to the utility. Line loss has a direct impact on the amount of fuel consumed, which impact s
electric rates (see Figure 36 on page 78). If all 32 RPSU projects commissioned between 2001 and 2009
had maintained the expected 8% line loss, fuel use would be reduced by 150,000 gallons per year, for an
annual savings of over half a million dollars.211
The RPSU program has lowered electric rates in communities where projects have been performed. Some
of the cost reduction is directly due to the improvements in generation efficiency. By getting more kWhs
from every gallon of diesel, a utility’s fuel costs are reduced. We make the assumption that at least a
portion of these savings is passed onto the consumer through lower electric rates. Table 11 shows the
average reduction by region in utility fuel costs following RPSU projects completed between 200 1 and
2009. The fuel cost reductions are shown on a per-kilowatt-hour basis to show their potential impact on
consumer electric rates.
210 AEA analysis of Power Cost Equalization data (2000-2013), accessed from the Alaska Energy Data Gateway.
(https://akenergygateway.alaska.edu/)
211 AEA analysis of RPSU design documents and PCE data.
-10%-5%0%5%10%15%
Aleutians
Bering Straits
Bristol Bay
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
Northwest Arctic
Southeast
Yukon-Koyukuk/Upper Tanana
Percent change in powerhouse efficiency after RPSU projects (2001-2009)
Sources: PCE and AEA RPSU data (2000-2013)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 125
Table 11: Long-term reduction in fuel costs due to efficiency improvement after RPSU project212
Region
Number of
projects in
region
Minimum Fuel
Cost Reduction
($/kWh)
Average Fuel
Cost Reduction
($/kWh)
Maximum Fuel
Cost Reduction
($/kWh)
Aleutians 3 $0.00 $0.04 $0.08
Bering Straits 2 -$0.02 $0.01 $0.03
Bristol Bay 4 -$0.05 $0.04 $0.12
Copper River/Chugach 1 $0.03 $0.03 $0.03
Kodiak 2 $0.01 $0.06 $0.11
Lower Yukon-Kuskokwim 12 $0.01 $0.06 $0.19
Northwest Arctic 2 -$0.03 $0.01 $0.05
Southeast 4 $0.01 $0.02 $0.04
Yukon-Koyukuk/Upper Tanana 2 -$0.12 -$0.04 $0.04
It is clear from Table 11 that fuel cost reductions attributable to RPSU efficiency gains have varied widely.
The average per kWh savings in fuel costs for all 32 projects was $0.03/kWh. The largest reductions in fuel
costs, on a per kWh basis, were in the Lower Yukon-Kuskokwim region, where average savings were
$0.06/kWh.
A greater savings to rural utilities and electric consumers comes from grant funding capital infrastructure.
Because consumers do not have to pay the capital or financing costs of new or upgraded infrastructure,
they are likely to see little direct change in their electric rates following a major powerhouse renovation
or expansion.
For most of the program’s life, utilities that received an RPSU project funded by the Denali Commission
were required to maintain a reserve account to pay for 40% of the expected capital cost for the eventual
replacement of the powerhouse. The reserve accounts were meant to allow for sustainable operation of
the facilities and avoid a future liability for the State or federal government. In 2012, the Denali
Commission’s Inspector General was unable to determine if these accounts were set up and being funded
by ratepayers. 213 The following analysis assumes that these reserve accounts are not being capitalized.
Table 12 summarizes the average per-KWh savings by region from both the capital expense (CAPEX) and
efficiency benefits of RPSU projects completed between 2000 and 2009.
212 AEA analysis of Power Cost Equalization data (2000-2013), accessed from the Alaska Energy Data Gateway.
(https://akenergygateway.alaska.edu/)
213 Office of Inspector General, Denali Commission. Analysis of R&R Accounts as Highlighted in the FY2012 Second Half Semi-
Annual Report to Congress. June 12, 2013. http://oig.denali.gov/wp-content/uploads/2015/01/SAR-2012-09.pdf
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 126
Table 12: Reduction in generation costs due to RPSU capital grants214
Region
Number
of
projects
in region
Minimum total
savings/kWh
(CAPEX and
efficiency)
Average total
savings/kWh
(CAPEX and
efficiency)
Maximum total
savings/kWh
(CAPEX and
efficiency)
Aleutians 3 $0.07 $0.49 $0.94
Bering Straits 2 $0.24 $0.25 $0.26
Bristol Bay 4 $0.17 $0.38 $0.53
Copper River/Chugach 1 $0.44 $0.44 $0.44
Kodiak 2 $0.10 $0.18 $0.25
Lower Yukon-Kuskokwim 12 $0.09 $0.33 $0.74
Northwest Arctic 2 $0.13 $0.16 $0.19
Southeast 4 $0.09 $0.30 $0.65
Yukon-Koyukuk/Upper Tanana 2 $0.38 $0.85 $1.31
By comparing Tables 11 and 12, it is clear that by far the largest cost savings to utilities and consumers
comes from the offset in capital expenses. Average total savings (CAPEX and efficiency) varies by region
from a low of $0.18 in Kodiak to $0.85/kWh in the Yukon-Koyukuk/Upper Tanana region. In some cases,
per-kWh savings actually exceed the current residential rate. Ratepayers who are not eligible for PCE (e.g.
private businesses) would see a sizeable increase in their electric rates if utilities had to pay the full capital
cost of infrastructure. For the portion of residential and community facility kWhs covered by the PCE
program, the increased cost to cover capital expenses would be mostly absorbed by the PCE program
It is more difficult to evaluate the RPSU’s success in its primary mission, since there is little quantitative
data available to track the safety, stability, and reliability of the state’s many unregulated small utilities,
including most in the study area. Even utilities that are economically regulated by the Regulatory
Commission of Alaska (RCA) do not consistently report metrics related to safety and reliability.215
RPSU projects have not eliminated the need for electrical emergency assistance, as shown by a high-level
analysis exploring the relationship between AEA’s Electrical Emergency Response program and the RPSU
program during the 10-year period from 2005 to 2015. In the years after an RPSU project was completed,
recipient communities received approximately $800,000 in emergency services from the State, about one-
quarter of the total number and cost of the emergency assistance program responded to over that time.
The continued need for emergency assistance in these communities suggests that the age of
infrastructure is not the primary cause of emergencies and that other factors, including proper training,
maintenance, and management at the utility are also critical to keeping utilities safe, stable, and reliable.
The State does not have a statutory or regulatory obligation to replace powerhouses that have reached
the end of their useful lives. A liability may exist if the powerhouses fall under the regulations associated
214 AEA analysis of Power Cost Equalization data (2000-2013), accessed from the Alaska Energy Data Gateway.
(https://akenergygateway.alaska.edu/)
215 James Layne. Electric Utility Outage Reporting 2003 to 2013. Regulatory Commission of Alaska. April 22, 2015.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 127
with the Electrical Emergency Response program and the critical energy infrastructure becomes unsafe
and presents a public hazard.216
There are currently no standards requiring unregulated electric utilities to prove that they are operated
in a way that provides safe, stable, reliable, and affordable energy once they have received a Certificate
of Public Convenience and Necessity (CPCN). However, an opportunity exists to reduce community energy
costs and State expenditures for emergency response by providing additional oversight of operations at
small rural utilities (including proper training, maintenance, and management) and improved access to
non-State financing for infrastructure upgrades and replacement.
Bulk Fuel Upgrade program
Before the Bulk Fuel Upgrade (BFU) program, many of Alaska’s rural bulk fuel storage facilities had been
constructed in the 1970s or earlier. Many of these facilities had reached the end of their useful life, leaked
fuel, and did not comply with State and federal codes and regulations. Regulatory agencies, such as the
Alaska Division of Fire and Life Safety, the Coast Guard, and the Environmental Protection Agency, could
prohibit fuel deliveries to these facilities due to safety and compliance concerns, although this has not
happened yet. Not all communities have been served by the program and some noncompliant bulk fuel
storage is still in use.
The goal of AEA's Bulk Fuel Upgrade program is to upgrade non-compliant bulk fuel facilities in
communities that meet community size, use, and geographic restrictions.217 By providing adequate
capacity for current and planned needs, communities may purchase fuel in larger quantities at a lower
cost per gallon.218 However, purchasing fuel in bulk comes with some market risk. Fuel prices may be
significantly higher on the day the bulk order is shipped than the average price will be over the perio d in
which the fuel is consumed. This happened to many communities between 2014 and 2015.219
Since 2000, BFU funding to replace community bulk fuel facilities has come from Denali Commission
grants, direct legislative appropriations, Community Development Block Grants, Indian Community
Development Block Grants, USDA grants and loans, owner-financing, and other sources. Due diligence is
carried out to ensure that project participants meet Denali Commission and State of Alaska sustainability
standards.220
216 3 AAC 108.200 – 240.
217 3 AAC 108.110.
218 AEA Bulk Fuel Upgrade Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
219 Lisa Demer. “Bush Alaska locked into high gas prices for fuel delivered last summer and fall.” Alaska Dispatch News. May 31,
2016. https://www.adn.com/rural-alaska/article/bush-alaska-locked-high-gas-prices-fuel-delivered-last-summer-and-
fall/2015/01/01/
220 Denali Commission Policy. Rural Alaska Energy Infrastructure Criteria for Sustainability. 2002.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 128
Figure 65: Bulk Fuel Upgrade funding by source and year221
Figure 65 shows all funds disbursed by the Denali Commission for bulk fuel upgrades, including those paid
to AEA and to the Alaska Village Electric Cooperative (AVEC). Over 150 projects funded were funded from
2001 through 2015, including feasibility and conceptual design. The majority of the funding was allocated
in 2002. The average annual budget for all years from all funding sources was nearly $20 million. The total
budget for the 15 years was over $293 million.
As in the RPSU program, the allocation of BFU grants is decided by AEA through a non-competitive process.
The status of bulk fuel facilities is assessed periodically in areas expected to have the most need. The most
recent bulk fuel inventory was performed by AEA in 2015 with a review of 56 communities. The
assessment found that a number of communities needed replacement of their bulk fuel facilities, but that
others were in need of less expensive upgrades.222
Figure 66 shows project funding by AEA energy region. Like the previous figure, it includes BFU pr ojects
managed by AEA and AVEC. Over 40% of total funding went to the Lower Yukon-Kuskokwim. While this
may appear unbalanced, it is only slightly more than the region’s per-capita representation among BFU-
eligible communities. Nearly 20% of the funding went to the Bering Straits region. With both a maritime
climate and permafrost, it is unsurprising these regions demonstrated the greatest need. The lowest need
in the AkAES study area was found in the Copper River/Chugach region, where most communities are on
the road system and do not have tank farms.
221 Denali Commission database and AEA financial data
222 Alaska Energy Authority. “Bulk Fuel Inventory Assessment Report.” 2016.
$0
$40,000,000
$80,000,000
$120,000,000
$160,000,000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Bulk Fuel Upgrade funding by source and year
Source: Denali Commission database and AEA data
Other Match
State Match
Denali Commission to Other
Denali Commission to AVEC
Denali Commission to AEA
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 129
Figure 66: Bulk Fuel Upgrade funding by AEA energy region223
Bulk fuel construction projects include a business operating plan, which outlines the existing
organizational structure, qualifications of responsible personnel, training opportunities, and estimated
operation and maintenance costs.224 Once a project is complete, there is currently no formal oversight for
these facilities to ensure adherence to business plans.
An analysis of data in the Denali Commission database, accessed in summer 2015, showed that recipients
of BFU projects represent a wide variety of public and private entities, including school districts, utilities
(public, cooperatives, and private), seafood processors, and local fuel distributors (including cities,
villages, village corporations, and private stores). BFU funding was used to install 20 million gallons of
capacity between 2001 and 2015. Costs of new and/or refurbished storage ranged between $7 and $40
per gallon of capacity.225
BFU projects provide multiple benefits, including cost savings, training, and jobs for local workers, greater
code compliance and resulting reductions in safety, health, and environmental risks. The focus of the
AkAES analysis is on cost savings for communities. The savings from bulk fuel upgrades come from several
factors, including:
lower fuel transportation costs due to increased efficiency in fuel delivery,
lower unit costs by being able to order more fuel at one time,
reductions in fines, and
capital costs for infrastructure that consumers do not have to pay.
223 Denali Commission database and AEA financial data
224 AEA Bulk Fuel Upgrade Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
225 Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in Rural Alaska.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElectricityFuel102616.pdf?ver=
2016-10-27-083402-423
$0 $30,000,000 $60,000,000 $90,000,000 $120,000,000 $150,000,000
Copper River/Chugach
Kodiak
Railbelt
Aleutians
Southeast
Northwest Arctic
Yukon-Koyukuk/Upper Tanana
Bristol Bay
Bering Straits
Lower Yukon-Kuskokwim
Bulk Fuel Upgrade funding by AEA energy region
Source: Denali Commission and AEA financial data (2001-2015)
Denali Commission State Other match
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 130
Negotiated fuel prices and delivery charges are proprietary, but public data is available to assess the
economic benefit to communities from the last source of savings—the reduction in infrastructure costs.
BFU projects are saving AkAES communities an average of $0.43 to $1.76 per gallon on capital costs. Table
13 shows average community savings on bulk fuel infrastructure by region over the lifespan of the facility,
expressed as savings per gallon. To calculate the offset capital costs enjoyed by consumers by the grant-
funded infrastructure, Table 13 assumes the bulk fuel facility lasts 40 years, is financed through a loan at
5%, there is one delivery per year and all available tankage is sold during the year. These represent
significant savings for rural fuel customers, including electric utilities, residential and commercial heating
oil consumers, and transportation fuel consumers.
Table 13: Value of bulk fuel upgrades in $/gallon226
Region
Minimum
equivalent
$/gal
Average
equivalent
$/gal
Maximum
equivalent
$/gal
Aleutians $0.32 $0.63 $0.81
Bering Straits $0.39 $0.78 $1.40
Bristol Bay $0.43 $0.94 $2.75
Copper River/Chugach $1.76 $1.76 $1.76
Kodiak $0.47 $0.69 $0.91
Lower Yukon-Kuskokwim $0.13 $0.78 $1.81
Northwest Arctic $0.50 $0.84 $1.44
Railbelt $0.43 $0.43 $0.43
Southeast $0.15 $0.93 $1.45
Yukon-Koyukuk/Upper Tanana $0.50 $1.17 $2.47
The assumption in Table 13 of one fuel inventory turnover per year is not accurate for all communities. A
few communities receive fuel by air and the number of turnovers is many times higher. Others receive
barge deliveries twice a year—at the beginning and end of the ice-free season. For this reason, the savings
shown should be considered an upper limit, as greater throughput will reduce the per gallon savings.
As with RPSU projects, most BFU grant recipients have been required to maintain an account to pay for
40% of the eventual replacement of the infrastructure. If these accounts had been maintained, and the
cost of this replacement had been priced into the fuel, there would be still be a savings of 60% of the
capital costs to the community. It does not appear that most grant recipients have been saving enough
for the eventual replacement of the bulk fuel infrastructure.227 Although bulk fuel facilities are not
economically regulated, similar logic to electric utilities would dictate that current customers should pay
for assets that are used and useful and not pre-fund infrastructure for future consumers.
226 AEA analysis of Denali Commission database
227 Denali Commission. “Analysis of R&R Accounts as Highlighted in the FY2012 Second Half Semi-Annual Report to Congress.”
June 2013.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 131
The savings in bulk fuel capital costs also results in electricity savings. Each $0.50/gallon in the pri ce of
diesel translates into approximately $0.04/kWh in electricity rates, so any reductions in a utility’s fuel
costs can be expected to result in a smaller but real reduction in electricity costs for consumers and
increased savings to the State through reduced PCE expenditure. In a study commissioned for the AkAES,
it was estimated that one-third of new BFU fuel capacity was for fuels used in electric generation.228
As with powerhouse replacements, the State does not have a statutory or regulatory requirement to
replace tank farms when they have reached the end of their useful life, though unsafe infrastructure poses
health, safety, and environmental risks that the State has an interest in mitigating.
Renewable Energy Fund
The Alaska Renewable Energy Fund (REF) provides benefits to Alaskans by assisting communities across
the state to reduce and stabilize the cost of energy through the appropriate integration of cost-effective
renewable energy for power or heat.
The Alaska Legislature created the Renewable Energy Fund in 2008, with the intent to appropriate $50
million annually for five years.229 The REF was part of a suite of programs, including the Home Energy
Rebate program and the rapid increase in Weatherization funding, developed or expanded in 2008 in
response to historically high oil prices. In 2012, the Legislature extended the program for an additional 10
years.
In 2008, global oil prices were at a record high and the State enjoyed increased revenues from royalties
paid by oil and gas producers. These record-breaking energy prices were at the same time causing rural
consumers considerable burden. These two factors combined to raise awareness of the problem while
providing the resolve and means to find a solution. The REF, created to incentivize renewable energy
production, was a key part of the solution.
To date, the program has leveraged hundreds of millions in non-state contributions for $257 million in
State appropriations. State funding peaked in the first year of the REF program at $100 million. Since then
REF funding has ranged from $5 million to $25 million per year, and received no funding in FY16, as shown
in Figure 67. 230 The chart does not include direct legislative appropriations for renewable energy
projects—those that did not go through the formal project application and vetting process. Several REF
projects have received additional direct support from the Legislature, including $47 million for Sitka’s Blue
Lake hydroelectric expansion and $12 million for the Railbelt’s Eva Creek wind project.
228 Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in Rural Alaska.” October
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElectricityFuel102616.pdf?ver=
2016-10-27-083402-423
229 Chapter 31 SLA 08 House Bill 152,
http://www.akenergyauthority.org/Content/Programs/RenewableEnergyFund/Documents/Chapter31_SLA08_HB152.pdf
230 AEA Renewable Energy Fund Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 132
Figure 67: Renewable Energy Fund appropriations and match (2008-2015)231
The REF application review process has mechanisms, including preferential selection criteria for higher
energy costs communities and regional spreading, to help ensure that the benefits of the REF are not
concentrated in urban Alaska. The program has been successful in providing grant funds to communities
off the Railbelt, as 89% of REF grant funds have accrued to communities in the AkAES study area.
Figure 68: Renewable Energy Fund grants by AEA energy region
231 Alaska Energy Authority. “Renewable Energy Fund Round Status Report and Round IX Recommendations.” May 2016.
http://www.akenergyauthority.org/Portals/0/Programs/RenewableEnergyFund/Documents/REFRound9StatusRptPrintSpreads.
pdf
$0
$25
$50
$75
$100
$125
$150
2008 2009 2010 2011 2012 2013 2014 2015Funding in millionsRenewable Energy Fund appropriations and grant match (2008-2015)
Source: AEA data
State funding Local grant match
$0 $20,000,000 $40,000,000 $60,000,000
Statewide
North Slope
Bristol Bay
Yukon-Koyukuk/Upper Tanana
Kodiak
Aleutians
Bering Straits
Copper River/Chugach
Northwest Arctic
Railbelt
Lower Yukon-Kuskokwim
Southeast
Renewable Energy Fund grant amount (Round 1-8)
Source: REF Round 9 Status Report
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 133
The REF program has been successful in increasing renewable energy use in Alaska and decreasing the
amount of fossil fuels used for heat and electricity. This is best seen i n Kodiak, where two large REF
projects (a third turbine for the Terror Lake hydro project and the 9-MW Pillar Mountain wind project)
have allowed the local utility to generate almost solely with renewable energy.
The primary contribution of the REF program to energy affordability comes from replacing imported diesel
and heating oil with cheaper alternative fuels and resources. This is usually expressed as the number of
gallons of diesel equivalent displaced by a project and the project’s cost savings represents the value of
that displaced fuel at current prices.
In 2015, over 27.8 million gallons of diesel equivalent were displaced, for an annual savings of $73.7
million.232 Wind projects—particularly the large multi-MW installations in Kodiak and Fairbanks—have
been the major source of fuel savings for the REF program to date, although hydro surpassed wind in
2015. The Anchorage Landfill Waste to Energy project has also contributed a significant portion to fuel
displacement; this appears in the chart as biofuel. The fact that prior investments in wind feasibility
studies had led to “shovel-read” construction projects was the likely reason for the early primacy of
wind.233 The absolute and relative contributions to fuel displacement from REF hydro projects is expected
to increase as several more hydro projects are brought on-line.
Figure 69: Fuel displaced by REF projects (2009-2015)234
232 Alaska Energy Authority, 2016.
233 Vermont Energy Investment Corporation. Renewable Energy Grant Recommendation Program Impact Evaluation. 2012.
https://www.veic.org/documents/default-source/resources/reports/veic-alaska-energy-authority-rgrp-impact-and-process-
evaluation-report.pdf?sfvrsn=2
234 Alaska Energy Authority. “Renewable Energy Fund Round Status Report and Round IX Recommendations.” May 2016.
http://www.akenergyauthority.org/Portals/0/Programs/RenewableEnergyFund/Documents/REFRound9StatusRptPrintSpreads.
pdf
0
5
10
15
20
25
30
2009 2010 2011 2012 2013 2014 2015Fuel Displaced (diesel equivalent, millions of gallons)Fuel displaced by Renewable Energy Fund (2009-2015)
Source: AEA REF data
Biomass
Heat Pump
Heat Recovery
Hydro
Biofuel
Solar
Transmission
Wind
Wind to Heat
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 134
Figure 70: Percent of total energy savings from REF program by AEA energy region235
The majority of REF project savings are in regions and communities that are not eligible for PCE, as shown
in Figure 70. The three most heavily populated regions (Kodiak, Railbelt, Southeast), which collectively
comprise almost 90% of the state’s population, have captured nearly 90% of REF savings. Because of the
larger size of these energy markets, projects are on a larger scale than the more remote regions of the
AkAES study area.
In 2012, a third party conducted a process and impact evaluation of the REF program. The process
evaluation provides valuable insights into how any energy program in Alaska could be administered more
efficiently and effectively for participants and the State:
1. Provide for more project differentiation in the selection process by creating separate tracks to
lessen competition between large and small communities.
2. Provide for more coordinated and directed development of renewable energy projects, and rely
less on the open market to service communities with less capacity.
3. Provide for differentiation of financial and technical support to meet market needs and more
effectively leverage State resources. Larger communities and utilities may not need grants and
technical assistance. These communities may be better served through direct loans and/or loan
guarantees. Other smaller may need greater technical, managerial, and financial assistance.236
Emerging Energy Technology Fund
The Emerging Energy Technology Fund (EETF) was created by the Alaska State Legislature in 2010 through
AS 42.45.375 to promote the expansion of energy sources available to Alaskans. Administered by AEA, the
EETF funds projects that test emerging energy technologies or methods of conserving energy, improve an
235 AEA analysis of REF performance data
236 Vermont Energy Investment Corporation. Renewable Energy Grant Recommendation Program Process Evaluation. 2012.
https://www.veic.org/documents/default-source/resources/reports/veic-alaska-energy-authority-rgrp-impact-and-process-
evaluation-report.pdf?sfvrsn=2
0%10%20%30%40%
Kodiak
Railbelt
Southeast
Copper River/Chugach
Bering Straits
Lower Yukon-Kuskokwim
Northwest Arctic
Aleutians
Yukon-Koyukuk/Upper Tanana
Bristol Bay
North Slope
Percent of total energy savings from REF program by AEA energy region
Source: AEA REF performance data (2009-2015)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 135
existing technology, or deploy an existing technology that has not previously been demonstrated in the
state. EETF grants must be used to demonstrate technologies that have a reasonable expectation of
becoming commercially viable within five years. Eligible types of energy technologies include
improvements to renewables, conservation of energy, and technologies enabling the efficient and
effective use of hydrocarbons.237
Since 2012, a combination of legislative appropriations and contributions from the Denali Commission
have resulted in grant awards totaling $11.3 million, which leveraged an additional $4.8 million in
committed match, as shown in Table 14.
Table 14: Emerging Energy Technology Fund appropriations by year and source238
State
Federal (Denali
Commission or
Dept. of Energy)
2012 $4,800,000 $4,800,000
2014 $2,000,000
2017 $250,000
The EETF has tested and advanced several technologies to date to determine their economic and technical
feasibility in Alaska. The grants are intended to test technologies that are expected to be commercially
viable within five years. It may be some time before we know which technologies will prove out in Alaska,
and under what conditions, in order to increase the range of economical energy solutions. This is true
even for technologies receiving funding in Round 1 of the EETF, w hich should be nearing
commercialization.
No formal program evaluation of the EETF has been commissioned. Since its inception in 2010, the EETF
has tested and, in some cases, advanced technologies in several areas: hydrokinetic devices, energy
storage devices, the use of exhaust thimbles (sleeves that increase the energy efficiency of a
furnace/boiler at its ceiling penetration), and biomass reforestation techniques to improve the
sustainability of wood energy systems in Alaska.239
Round 3 of the EETF, in 2016, focused on microgrid and microgrid-enabling technologies based on the
input of Alaska energy stakeholders about where the program could have the greatest impact . Round 3
funding came from Round 1 and 2 funds, that were returned to the EETF, and an additional $250,000 from
the Department of Energy was granted to AEA.240
237 3 AAC 107.700-799
238 AEA Emerging Energy Technology Fund Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
239 Alaska Energy Authority. “Emerging Energy Technology Fund Project Status Updates. February 2016.”
http://www.akenergyauthority.org/Portals/0/Programs/EETF/Documents/EETFProjectUpdatesFeb2016.pdf?ver=2016-03-23-
095100-640
240 AEA Emerging Energy Technology Fund Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 136
Weatherization Assistance program
Weatherization Assistance program (Wx) is a long-standing federal program of the Department of Energy
to assist low-income households (both homeowners and renters) in reducing their energy costs. State and
federal programs also require that Wx address imminent health and safety issues.241 In 2008, the Alaska
Legislature increased funding for the program sharply and expanded income eligibility to include
households earning up to 100 percent of Area Median Income (AMI).242
Since 2008, Wx has been primarily funded through the State of Alaska’s capital budget. Prior to 2008, Wx
funding was steady and split nearly equally between State and federal sources. In 2008, the State funding
level increased by nearly one hundredfold, from approximately $3 million to $200 million. The significant
increase challenged existing organizational structures and capacity to deploy weatherization services, so
it took the program time to ramp up activity. In 2012, the Legislature appropriated an additional $62.5
million for the program, and funding has declined in each year since 2012. Between the 2008 and
September 2015, a total of $323.4 million in State funding was spent on Wx services.
Figure 71: Weatherization funding by source (2000-2016)243
Since 2008, more than 20,000 housing units statewide have been made more energy efficient through the
Weatherization program, primarily through State funds, saving participating households 20 to 45%
annuallly on their energy costs. Approximately 47% of the retrofits were in the AkAES study area. The
number of units weatherized per energy region and the total costs savings by region are shown in Figures
72 and 73 respectively. Since eligibility is based on income, some of the regional differences may reflect
the percentage of households that meet the income guidelines.
The funding available per household is determined by community and region. Homes in the Railbelt or
along the Marine Highway system receive an average of up to $11,000 per home in energy, health, and
241 Cold Climate Housing Research Center. “Weatherization Assistance Program Outcomes.” August 6, 2012.
http://www.cchrc.org/sites/default/files/docs/WX_final.pdf
242 FY 2016 Income Limits for Alaska. April 2016. https://www.ahfc.us/files/1114/7198/9173/Alaska_Income_Limits_-
_FY_2016_with_Median_Incomes-FINAL.pdf
243 AHFC data on Weatherization Assistance Program funding (Updated 10/5/16)
$0
$50,000,000
$100,000,000
$150,000,000
$200,000,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Weatherization Assistance program funding by source (2000-2016)
Source: AHFC
Federal (Dept. Of Energy)Federal (LIHEAP)State of Alaska (AHFC)
Approximately $3M/year
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 137
safety measures, while homes in remote rural areas of the state may receive up to an average $30,000
per home of Enhanced Weatherization services.244
Figure 72: Weatherization Program units by AEA energy region245
Figure 73: Weatherization program total estimated annual energy cost savings by AEA energy region246
While most of the savings have occurred in Railbelt communities due to the greater number of
weatherized units, the higher energy costs in other regions increased their per-unit savings.
244 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
245 AEA analysis of AHFC Weatherization Assistance Program data (accessed December 2016).
246 AEA extrapolations of 2012 AHFC Wx energy savings data based on 2016 Wx completions.
0 2,000 4,000 6,000 8,000 10,000 12,000
Kodiak
North Slope
Aleutians
Bering Straits
Copper River/Chugach
Northwest Arctic
Bristol Bay
Yukon-Koyukuk/Upper Tanana
Lower Yukon-Kuskokwim
Southeast
Railbelt
Number of weatherized units
Weatherization Assistance Program units by AEA energy region
Source: AEA analysis of AHFC data (2008-2015)
2008 2009 2010 2011 2012 2013 2014 2015
$0 $2,500,000 $5,000,000 $7,500,000 $10,000,000
Kodiak
North Slope
Aleutians
Copper River/Chugach
Bering Straits
Bristol Bay
Northwest Arctic
Yukon-Koyukuk/Upper Tanana
Lower Yukon-Kuskokwim
Southeast
Railbelt
Estimated annual savings
Estimated annual cost savings from Weatherization Assistance Program
Source: AEA analysis of AHFC data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 138
The percentage of household savings in heating fuels show some regional differences as well, with
modeled savings ranging from 20% to 45%. Kodiak had the lowest average savings and the rural Interior
(Yukon-Koyukuk/Upper Tanana) had the highest. In general, regions with higher heating oil costs and
colder climates realize more savings. Although there are a number of determinants for how much savings
a Wx project produces, the initial condition of the housing is a huge factor: lower quality housing has much
higher savings potential.
The success of Wx in rural Alaska is likely due to the activities of regional housing authorities, many of
which would walk door to door in communities to sign up eligible applicants.247 In some communities, this
led to all residential buildings being served by Wx.
In 2012, AHFC commissioned the Cold Climate Housing Research Center (CCHRC) to do an impact
evaluation of the Weatherization program. CCHRC found that the Weatherization program was generally
performing as expected and did not note any significant gaps or barriers in program delivery.248
Home Energy Rebate program
In 2008, AHFC initiated the Home Energy Rebate (HER) program. The HER Program, funded through the
State capital budget, provided homeowners a rebate of up to $10,000 in materials and contracted labor
for making pre-approved energy efficiency improvements.249 The State’s investment in the program was
intended to make homes more energy efficient while stimulating private investment in home retrofits and
reducing energy costs.250 Program participation was limited to year-round residents who occupied their
home; there were no income limits and no match requirements. The program was suspended in 2016 for
lack of funding.
Participants received an initial home energy audit including a ranked list of cost-effective measures for
increasing the efficiency of the house. Health and safety improvements related to energy use, such as
ensuring adequate ventilation, were also included, and generally reimbursable. The homeowner was
responsible for choosing and implementing any or all the energy efficiency improvements listed in the
energy audit. The time allowed after the initial energy rating to complete all improvements, receive a
post-improvement rating, and submit final paperwork and receipts was 18 months.
The rebate amount was based on the improvement in the home’s energy efficiency and the submittal of
eligible receipts. In addition to the energy improvements, homeowners were reimbursed up to $500 for
the initial and post energy rating.251 Program participants were not required to submit all receipts for work
completed, only receipts totaling up to the allowed reimbursement.
247 Scott Waterman, personal communication. December 2016.
248 Cold Climate Housing Research Center. “Weatherization Assistance Program Outcomes.” August 6, 2012.
http://www.cchrc.org/sites/default/files/docs/WX_final.pdf
249 https://www.ahfc.us/efficiency/energy-programs/home-energy-rebate/
250 Cold Climate Housing Research Center. Home Energy Rebate Program Outcomes. 6/26/2012.
http://www.cchrc.org/docs/reports/HERP_final.pdf
251 https://www.ahfc.us/files/6114/1295/9895/Consumer_Guidelines_100114.pdf
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 139
After high initial participation, when a long waitlist formed, the demand for new HER audits gradually
slowed. AHFC did not advertise the program, but the program still averaged over $20 million in rebates
per year.
Figure 74: Annual funding for Home Energy Rebate program (2008-2015)252
From the program’s inception through October 2015, the state invested a total of $204.6 million, resulting
in 23,980 completed retrofits and leveraging over $120 million in homeowner investments.253
The overwhelming majority of HER rebates went to homeowners in the Railbelt, only 14% of HER funding
was within the AkAES study area, primarily in the four largest cities in the Southeast .254 Figure 75 breaks
out estimated HER rebates by energy region. Since regional rebate data was not available, AEA
approximated regional spending by dividing total State funding by the number of rebates per region.
Figure 75: Estimated Home Energy Rebates disbursed per AEA energy region255
252 AHFC data on Home Energy Rebate Program funding (Updated 10/5/16).
253 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
254 AEA analysis of Home Energy Rebate data provided by AHFC (December 2016).
255 AEA extrapolations of 2012 AHFC per household savings based on unpublished 2016 AHFC data on rebates.
$0
$25,000,000
$50,000,000
$75,000,000
$100,000,000
2008 2009 2010 2011 2012 2013 2014 2015Annual fundingAnnual funding for Home Energy Rebate program (2008-2015)
Source: AHFC data
$176,840,000
$21,590,000
$2,380,000
$2,280,000
$550,000
$280,000
$220,000
$180,000
$170,000
$90,000
$20,000
$0 $50,000,000 $100,000,000 $150,000,000 $200,000,000
Railbelt
Southeast
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
Bristol Bay
Northwest Arctic
Bering Straits
Yukon-Koyukuk/Upper Tanana
Aleutians
North Slope
Estimated Home Energy rebates per AEA energy region
Source: Unpublished AHFC data
No additional
funding 2010-
2011
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 140
Rural residents in the AkAES study area had lower participation and completion rates than urban Alaskans.
Approximately two-thirds of all HER applicants completed their post-rating and paperwork to receive a
rebate, but in rural areas of the state, the completion rate was between 32% and 54%.256
A 2013 online survey of 574 program participants found that the demographics of participants were not
representative of Alaska as a whole; HER participants had higher average incomes and significantly higher
education levels than statewide averages.257 A number of barriers likely led to the lower number of
households in the AkAES study area participating in the program:
The rate of home ownership is lower in rural than urban Alaska making fewer rural residents
eligible for the program.258
Since the program is based on rebates, it required homeowners to have sufficient cash or credit
to pay for upfront costs and wait for reimbursement, which lower income households are less
able to do. 46% of respondents to the survey stated that lack of money was the reason they had
not completed the program.259
Outside urban centers, poor access to materials and labor, including qualified energy raters, made
it more difficult for homeowners to make needed improvements to their houses.
The amount of funding allotted for Enhanced Weatherization services in rural Alaska (three times
as much as for communities on the road system) indicates a significantly higher cost to make
home improvements in rural locations. The HER program did not adjust maximum reimbursement
amounts for remote locations—reimbursement amounts seemed more appropriate for expenses
incurred in urban areas of the state. Therefore, it would appear that the HER program offered an
insufficient amount for rural participants to cover the higher costs for improving the efficiency of
their houses.
AEA estimated the annual savings per region shown in Figure 76 based on the number of homes retrofitted
in each region and the average savings per household of 34%, as calculated by AHFC in 2012. Since most
of the rebates were disbursed to the Railbelt region, which has 78% of the state’s population, it is not
surprising that most of the annual savings were also captured by that region. AEA estimates that HER
retrofits are saving residents of the AkAES study area nearly $7.3 million per year, less than $1.1 million
of that is in more rural parts of the region (outside the city of Kodiak and the larger Southeast cities).
256 Cold Climate Housing Research Center. Home Energy Rebate Program Outcomes. 6/26/2012.
http://www.cchrc.org/docs/reports/HERP_final.pdf
257 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
258 Jack Cannon. “Housing Trends.” Alaska Department of Labor and Workforce Development. 2004.
http://laborstats.alaska.gov/trends/jun04art2.pdf
259 Cold Climate Housing Research Center. Home Energy Rebate Program Outcomes. 6/26/2012.
http://www.cchrc.org/docs/reports/HERP_final.pdf
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 141
Figure 76: Annual energy cost savings for Home Energy Rebate program260
Participation in the HER program does not mean all cost-effective efficiency measures were performed,
since the number of measures completed was limited by the time, money, and effort the homeowner
could afford. AHFC does not know what the average homeowner investment was in the HER program,
because participants were not required to submit all receipts, only those up to the maximum allowable
reimbursement based on the home’s improved energy rating. Table 15 summarizes the estimated average
costs and returns of the HER program. The average homeowner costs are based on submitted receipts.
AHFC costs only include the reimbursement, and do not include program administration. The simple
payback and return on investment are calculated based on the modeled energy savings and current costs
at the time of the rating.
Table 15: Home Energy Rebate program cost-effectiveness261
Average costs
(2012 $) Simple payback (years) Return on investment
AHFC $6,516 5.0 20%
Homeowner $4,447 3.4 29%
Total $10,963 8.5 12%
Other research indicates that additional savings may be unaccounted for through this analysis. As a result
of the Home Energy Rebate program, Chugach Electric found a 2% reduction in electricity consumption,
260 AEA analysis of AHFC data
261 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
$34,310,000
$5,680,000
$690,000
$520,000
$140,000
$90,000
$50,000
$40,000
$30,000
$30,000
$-
$- $10,000,000 $20,000,000 $30,000,000 $40,000,000
Railbelt
Southeast
Copper River/Chugach
Kodiak
Lower Yukon-Kuskokwim
Bristol Bay
Bering Straits
Northwest Arctic
Aleutians
Yukon-Koyukuk/Upper Tanana
North Slope
Estimated annual savings
Estimated annual savings from Home Energy Rebate program per AEA
energy region
Source: AHFC data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 142
which is surprising since the HER program does not directly address measures to reduce electricity
consumption.262
While the average total cost (homeowner plus State) of approximately $11,000 per housing unit is about
half as much as what was reported for the Weatherization program, this does not mean t hat
Weatherization is less cost-efficient than the HER. Since Weatherization assisted many more rural areas
where logistics make it more expensive to work, it is expected to cost more to retrofit a house than
through the HER program, which primarily served Alaska’s major urban areas where labor and materials
are both more available and much less expensive. Additionally, costs for the Weatherization program are
actual totals, while for the HER program costs are those reported by participants and may underestimate
total investment.
New Home Rebate program
The New Home Rebate program, administered by AHFC, provided an incentive for reaching a high
standard of residential efficiency. Funded initially in conjunction with the Home Energy Rebate program,
the New Home Rebate program began in 2008 and paid out $7,500 rebates for new homes that received
an energy rating of 5 Star Plus using the AkWarm modeling software. When the Building Energy Efficiency
Standard (BEES) was updated in 2013, the New Home Rebate incentive was modified so that buyers of a
Five Star Plus home could qualify for a rebate of $7,000, and buyers of the newly added stretch goal of Six
Star could qualify for a $10,000 rebate. The amount of the Six Star home rebate was informed by an
economic analysis of the additional costs required to increase the energy efficiency of a home from the
minimum BEES standard, Five Star, to a Six Star rating. The New Home Rebate is paid directly to the buyer;
builders have suggested that more homes would be built to these standards if the rebate was made
available to them as well.263
Figure 77: Houses accessing New Home Rebate program 2008-2016264
262 Northern Economics. “The AHFC Home Energy Rebate Program and Electric Consumption by Chugach’s Residential
Customers.” May 2013.
263 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
264 AHFC data on New Home Energy Rebate Program funding (Updated 10/5/16)
0
200
400
600
2008 2009 2010 2011 2012 2013 2014 2015 2016Number of rebates per yearNumber of New Home Rebates by year
Source: AHFC data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 143
Between the inception of the New Home Rebate program in 2008 and November 2015, AHFC paid out
over 3,000 Five Star Plus rebates and 139 Six Star rebates, for a total estimated State cost of $22 million.265
Figure 76 shows the demand for New Home Rebates has been fairly consistent since 2009 with
approximately 400 rebates disbursed each year.
Figure 77 shows that there have been few New Home Rebate participants in the AkAES study area. Nearly
all rebates have gone to home buyers in the Railbelt. Outside of urban centers, most housing is built
through regional housing authorities, which do not receive the rebate, although they are eligible for the
Supplemental Housing Development grant. The distribution of rebates also mirrors the concentration of
new construction, which has been focused in the Mat-Su area in the period the program has been
active.266
Figure 78: New Home Rebates per AEA energy region267
Calculating the benefits of the New Home Rebate program is complicated. A primary difficulty is
accounting for so-called free riders, homes that would have been built to the Five Star Plus or Six Star
standard even if the homeowner/builder had not been offered a rebate. Since Alaska does not have a
statewide residential building energy code, it is difficult to know what to use as a baseline.
Village Energy Efficiency Program
The goal of the Village Energy Efficiency Program (VEEP), managed by AEA, is to implement energy- and
cost-saving efficiency measures in community buildings and other facilities in small Alaska communities.
Contractors work with individual communities and school districts to determine the best energy-saving
measures within the budgeted grant to the community.
265 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
266 Karinne Wiebold. “Alaska’s Housing Market: Characteristics, affordability, and what makes us unique.” Alaska Department of
Labor and Workforce Development. 2014. http://laborstats.alaska.gov/trends/apr14art1.pdf
267 AHFC data on New Home Energy Rebate Program funding (Updated 10/5/16)
1
2
3
6
8
29
31
148
3387
0 500 1000 1500 2000 2500 3000 3500
Northwest Arctic
Bristol Bay
Lower Yukon-Kuskokwim
Bering Straits
Yukon-Koyukuk/Upper Tanana
Copper River/Chugach
Kodiak
Southeast
Railbelt
Number of rebates per region
New Home Rebates per AEA energy region by year
Source: AHFC data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 144
The VEEP program began as the Village End Use Efficiency Measures (VEUEM) Program in 2005 with
funding from the Denali Commission. Measures implemented under this program were primarily lighting
upgrades and some weatherization. Between 2005 and 2009, 51 communities benefited from the
program. Between 2010 and 2012, the federal American Recovery and Reinvestment Act (ARRA) funded
energy efficiency improvement projects in an additional 110 communities and small boroughs through
both the Small Cities Energy Efficiency Community Block Grants (EECBG) and VEEP programs. VEEP in
particular used the VEUEM model but increased the funding per community to accomplish a greater
number of, and deeper, building efficiency improvements.268
Figure 79: Village Energy Efficiency Program Funding (2005-2015)269
Communities with a population of less than 8,000 residents are eligible for VEEP funding, which is awarded
competitively after each open application period. The FY14, state-funded VEEP program awarded a total
of approximately $1.4 million to seven communities for energy- and cost-saving efficiency projects.270
Despite the program’s demonstrated success and strong support from communities and regions, no
legislative appropriations have been made since FY14.
268 http://www.akenergyauthority.org/Efficiency/veep
269 AEA analysis of data from Village Energy Efficiency Program (compiled 2015)
270 http://www.akenergyauthority.org/Efficiency/veep
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Village Energy Efficiency Program Funding (2005-2015)
Source: AEA data
Federal funding State funding In-kind match
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 145
Figure 80: VEEP funding by region (2005-2015)271
Primarily funded through federal sources through 2011 and State appropriation in 2014-15, VEEP has also
been successful in leveraging cash and in-kind matches. The program has generally benefitted the regions
with the highest energy costs and the AkAES study area in general, as seen in Figure 79.
Outcomes for the VEEP program were reported at the community level between 2005 and 2010. The
program has aggregate data for ARRA-funded retrofits performed by the Alaska Building Science Network
(ABSN) between 2010 and 2012 (roughly half of all retrofits done over that period). The aggregate data
show that, on average, ABSN retrofits achieved a simple payback period of 5.4 years, taking into
consideration local in-kind contributions of labor and materials.272 These outcomes are summarized by
energy region in Figure 80 with modeled electricity savings converted to gallons of diesel equivalent saved,
based on an assumed generation efficiency of 13 kWh/gallon. The VEEP projects saved approximately
178,000 gallons of heating oil and 88,000 gallons of diesel for electric generation.
271 AEA analysis of data from Village Energy Efficiency Program (compiled 2015)
272 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
$- $500,000 $1,000,000 $1,500,000 $2,000,000
Copper River/Chugach
North Slope
Kodiak
Railbelt
Aleutians
Northwest Arctic
Bering Straits
Southeast
Bristol Bay
Yukon-Koyukuk/Upper Tanana
Village Energy Efficiency Program funding by region (2005-2015)
Source: AEA data
Federal funding State funding In-kind match
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 146
Figure 81: Estimated annual savings from VEEP communities (2005-2015)273
An analysis of 40 VEEP energy audits that used AkWarm modeling software from several different phases
of the program shows that, on average, energy used for space heating was reduced by 28%. While
reported data in Figure 80 show that the savings in heating fuel is significantly greater than for electricity,
electrical savings may be significantly underrepresented in the data due to recording errors in the early
years of the program, particularly for Kodiak and Copper River/Chugach. The ABSN report found that
electricity savings were approximately 44% of total savings from the buildings retrofitted in their
projects.274
VEEP illustrates one of the main difficulties in evaluating the effectiveness of State and federal energy
programs: energy data collection is not a priority for many program participants, and significant barriers
exist to gaining access to consumption records, particularly heating fuel data. AEA sent a team to
Nightmute in 2014 to follow-up on the city’s 2009 VEEP project. A number of buildings were re-audited
and the community’s heating oil records were located and copied, however there was still not enough
data of sufficient quality to quantify the benefits of the retrofits with a high degree of certainty. This does
not mean that benefits didn’t exist, but rather that there were not good baseline and post-retrofit records
to demonstrate the change in consumption. The team also looked at PCE data to determine changes in
electricity consumption following the project, but there was too much year-to-year volatility in the data
to isolate a direct effect.275 The Denali Commission commissioned a study to evaluate a VEEP project in
Shishmaref which reported similar issues with the availability of data.276
273 AEA analysis of data from Village Energy Efficiency Program (compiled 2015)
274 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
275 Katie Conway. “Nightmute Whole Village Retrofit—then and now.” Alaska Energy Authority. January 15, 2015.
http://www.akenergyauthority.org/Content/Efficiency/Veep/Documents/NightmuteWVR20082014FINAL11515.docx
276 Armstrong, Richard.” Measurement and Verification Review of 2010/2011 VEEP & EECBG Energy Efficiency Retrofits”
December 17, 2013.
0 20,000 40,000 60,000 80,000
Copper River/Chugach
Kodiak
North Slope
Railbelt
Aleutians
Northwest Arctic
Bering Straits
Southeast
Bristol Bay
Yukon-Koyukuk/Upper Tanana
Lower Yukon-Kuskokwim
Estimated heating oil and diesel savings (gallons)
Estimated annual energy savings from Village Energy Efficiency Program
communities (2005-2015)
Source: AEA data Estimated heating fuel savings (gallons)Estimated electricity savings (in gallons of diesel eq.)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 147
STATE ENERGY SUBSIDY PROGRAMS
The two primary state energy subsidy programs are the Power Cost Equalization program and the Alaska
Heating Assistance Program (AKHAP), which supplements the federal Low Income Heating Assistance
Program (LIHEAP).
The structure, requirements, and outcomes of PCE and AKHAP are very different. AKHAP is a focused
subsidy for low-income households in all Alaska communities, while PCE subsidizes electricity
consumption for community facilities and residential customers irrespective of income in eligible
communities.
Power Cost Equalization
The Power Cost Equalization program was created to even out the large disparities in power costs
statewide by subsidizing power costs in rural areas to bring them close or equal to the population-
weighted average of the per kWh cost in Anchorage, Fairbanks, and Juneau.277 The FY17 PCE rate is
$0.1667/kWh. Communities that receive power from the state-funded Four Dam Pool hydroelectric
projects (Tyee Lake, Swan Lake, Solomon Gulch, and Terror Lake) or are connected to the Railbelt grid are
not eligible for PCE.278
According to Alaska Statutes 42.45.100-170, the Regulatory
Commission of Alaska (RCA) determines if a utility is eligible to
participate in the program and calculates the amount of PCE per
kWh payable to the utility. The per kWh PCE payment is based
on the RCA’s determination of the eligible expenses submitted
by the utility. Eligible expenses include costs for fuel, generation,
personnel, interest, bad debt, administration, depreciation, and
other direct costs of producing electricity. Some expenses, such
as unpaid fuel bills, are not eligible. It is a common misconception that PCE only subsidizes a utility’s diesel
fuel consumption. In some years, diesel costs are the largest component of reported expenses, but all
generation expenses, including renewable generation costs, are allowed under the program.
Common PCE terms
PCE base rate The population-weighted average of the per kWh cost in Anchorage, Fairbanks,
and Juneau
PCE level
Amount payable per kWh, expressed in cents. Calculated by subtracting the
PCE base rate from the lesser of the reported, eligible costs (expressed in
$/kWh) or the Utility rate
Utility rate Rate charged to customers prior to PCE reimbursement
Effective rate Subsidized rate calculated by subtracting the PCE level from the Utility rate.
The PCE program is funded by the earnings of the PCE Endowment Fund. AS 42.45.085 provides that 5%
of the PCE Endowment Fund’s three-year monthly average market value may be appropriated to the PCE
277 Power Cost Equalization Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
278 AS 42.45.115
It is a common misconception
that PCE only subsidizes a
utility’s diesel fuel
consumption.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 148
program. The PCE Endowment Fund’s market value of total invested assets was $949.9 million as of Aug.
31, 2016.279 The most recent deposit to the PCE Endowment was $400 million in 2012.
Year-to-year subsidy levels are not constant since PCE reimbursements are based on utilities’ reported,
eligible expenses and on actual electricity consumption by utility customers. Figure 81 summarizes annual
PCE subsidy for fiscal years 2001 to 2016.
Figure 82: Annual Power Cost Equalization subsidy (FY2001-2016)280
PCE subsidy levels grew steadily through 2012. Between 2012 and 2016 there has been a decline of just
under $10 million, even though more communities now receive PCE. This has largely been due to the
decrease in the price of fuel. The sharp drop in crude oil prices that has created deep fiscal problems for
the State has resulted in a 17% savings to the PCE program between 2015 and 2016. A secondary factor
behind the gradual decline in annual PCE subsidies since 2012 is the growing amount of diesel displaced
by REF-funded renewable energy projects that have come online.281
Figure 83: FY2001-2016 Power Cost Equalization subsidy per AEA energy region282
279 Power Cost Equalization Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
280 AEA financial data
281 David Hill, Chris Badger, Leslie Badger, Nikki Clace, and Molly Taylor. “Alaska Energy Authority: Renewable Energy Grant
Recommendation Program Impact Evaluation Report.” 2012. https://www.veic.org/resource-library/alaska-energy-authority-
renewable-energy-grant-recommendation-program-process-and-impact-evaluation-reports
282 AEA financial data
$-
$15,000,000
$30,000,000
$45,000,000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Annual FundingAnnual Power Cost Equalization subsidy
Source: AEA data (FY2001-2016)
$- $40,000,000 $80,000,000 $120,000,000 $160,000,000
North Slope
Kodiak
Copper River/Chugach
Aleutians
Southeast
Northwest Arctic
Bristol Bay
Bering Straits
Yukon-Koyukuk/Upper Tanana
Lower Yukon-Kuskokwim
FY2001-2016 Power Cost Equalization subsidy per AEA energy region
Source: AEA data (2001-2016)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 149
The Lower Yukon-Kuskokwim has the largest population and the largest total subsidy. The cumulative PCE
subsidy has been remarkably similar for five of AEA’s energy regions, which have each received $45 to $55
million over the past 16 fiscal years, as shown in Figure 82. Communities in most of the remaining regions
(including Juneau, Ketchikan, Petersburg, Wrangell, Sitka, Kodiak, and all of the service area of Copper
Valley Electrical Cooperative) do not receive PCE either because their rates are not high enough to qualify
or they are statutorily excluded. The North Slope Borough subsidizes residential rates to a low enough
level that North Slope communities are eligible for little reimbursement.
Generation efficiency and line loss standards for PCE-eligible utilities are set in regulations. The standards
are a maximum 12%-line loss and a generation efficiency ranging from 8.5 to 13.5 kWh/gallon, as shown
in Table 16.
Table 16: PCE generation efficiency and line loss standards283
Minimum kWh
generated
Maximum
kWh
generated
Efficiency
standard
(kWh/gallon)
>80% diesel
Efficiency
standard
(kWh/gallon)
<80% diesel
- 99,999 9.5 8.5
100,000 499,999 10.5 10
500,000 999,999 11.5 11
1,000,000 9,999,999 12.5 12
10,000,000 13.5 13
For communities that fail to meet the standard, their PCE reimbursement is reduced to the amount that
would have been necessary if the performance standards were met.284
The RCA determines the PCE level for each community, and AEA determines the eligibility of residential
customers and community facilities, and it authorizes reimbursement to the electric utility for the PCE
credits extended to customers.285 AEA and RCA spend approximately $600,000 per year to administer and
provide regulatory oversight for the approximately $30 million annual program.
PCE brings the effective residential rate to less than $0.22/kWh in 71% of eligible communities. To reach
this level, 61% of PCE communities received a subsidy between $0.30 and $0.50 per kWh. 286
Figure 84 illustrates how PCE brings down the effective residential rate. Without PCE, electric rates for
rural residents would be at the top of each bar (each bar represents one community). PCE reimbursement
brings the effective residential rate (the rate the resident will pay for the first 500 kWh of electricity used
each month) down to the light gray line. If the unsubsidized residential rate in every community were
283 3 AAC 52.620. Generation efficiency and line loss standards
284 “Power Cost Equalization Program Guide.”
http://www.akenergyauthority.org/Content/Programs/PCE/Documents/PCEProgramGuideJuly292014EDITS.pdf
285 “Power Cost Equalization Program Guide.”
http://www.akenergyauthority.org/Content/Programs/PCE/Documents/PCEProgramGuideJuly292014EDITS.pdf
286 AEA analysis of Alaska Energy Statistics (2013)
http://www.akenergyauthority.org/Portals/0/Publications/2013DetailedSumTbl.xlsx
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 150
exactly equal to the utility’s eligible expenses, then all the gray bars would be about the same height—at
about $0.15/kWh. A community with an effective rate above that indicates that the utility is charging
residents more than what is needed to cover its reported, eligible expenses as determined by the RCA.
These charges are not reimbursed by the State.
Figure 84: Residential electricity rates in Power Cost Equalization communities287
The energy data collected through the PCE program, even though it contains reporting errors, is an
invaluable resource for policy analysts, researchers, and potential investors, as well as the communities
themselves. It represents an important non-monetary benefit of the PCE program. Without it, there would
be very scant information available about electric
generation, use and sales for nearly 200 of Alaska’s
communities. Energy use and cost data, such as
that collected by the PCE program, provides the
most basic information needed for comparing the
cost-effectiveness of potential energy projects.
Without it, this report would not have been
impossible to produce.
Alaska Heating Assistance Program
The Alaska Heating Assistance Program (AKHAP), administered by the Department of Health and Social
Services, supplements the federal Low Income Heating Assistance Program (LIHEAP). LIHEAP/AKHAP
assists households with incomes at or below 150% of federal poverty guidelines, who have a minimum of
$200 in out-of-pocket heating costs per year and meet all other eligibility criteria. The program is open to
homeowners and renters.288 Benefits are calculated using a point system based on: the area of the state
287 Alaska Energy Statistics (2013) http://www.akenergyauthority.org/Portals/0/Publications/2013DetailedSumTbl.xlsx
288 http://dhss.alaska.gov/dpa/Pages/hap/default.aspx
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
$1.60
$1.80
Rates, $/kWhPCE communities
Residential electricity rates in Power Cost Equalization communities
Source: Alaska Energy Statistics (2013)
Effective Rate PCE Reimbursement
PCE and other energy data provides the most
basic information needed for comparing the
cost-effectiveness of potential energy projects.
Without it, this report would not have been
impossible.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 151
where the home is located, heat type, dwelling type, as well as household size and income.289 The benefit
is a one-time annual payment sent directly to the household’s heating fuel vendor and credited to the
customer’s account.
Since 2009, total LIHEAP/AKHAP subsidies have been similar in scale to PCE reimbursements—$25 million
to $45 million per year, with the overwhelming majority coming from federal funds, as seen in Figure 84.
AKHAP was cut at the end of FY16 due to the reduced State budget, and approximately 10,000 Alaskans
in both urban and rural areas are expected to receive reduced or no heating assistance because of the
cuts. The federal LIHEAP program is still in place, but it only serves the lowest-income Alaskans.290
Figure 85: Yearly funding for LIHEAP & AKHAP (2000-2015)291
Unlike the PCE program, there are no limitations on which communities can participate in LIHEAP/AKHAP.
With no geographic restrictions and 78% of Alaskans living in the Railbelt, the majority of LIHEAP/AKHAP
households have also been in the Railbelt, as seen in Figure 86. The amount of heating assistance per
household does factor in geography and costs, with larger benefits going to households in colder and
higher cost areas of the state.
289 http://dhss.alaska.gov/dpa/Documents/dpa/programs/hap/FY17-HAP-Application.pdf
290 McChesney, Rashah. KTOO Public Media. “In rural Alaska, loss of heating assistance hits hard.” 11/11/2016,
http://www.ktoo.org/2016/11/11/rural-alaska-loss-heating-assistance-hits-hard/
291 AEA analysis of LIHEAP and AKHAP data from Department of Health and Social Services, November 2016
$0
$10,000,000
$20,000,000
$30,000,000
$40,000,000
$50,000,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Funding per yearYearly funding for LIHEAP & AKHAP (2000-2015)
Source: Alaska Department of Health and Social Servies
LIHEAP Total AKHAP Total
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 152
Figure 86: Total LIHEAP and AKHAP funding by AEA energy region (2000-2015)292
On a per-capita basis, the Railbelt and Southeast are underrepresented in their share of LIHEAP/AKHAP
funding, while some other regions, especially the Lower Yukon-Kuskokwim, are overrepresented. This is
consistent with the lower household incomes and higher heating fuel costs outside of the Railbelt and
Southeast. It is not known what proportion of eligible households access benefits in each region.
The average subsidy provided per household varies considerably by region due to differences in median
income, climate, heating fuel costs, and other factors where there could also be regional variation
(household size, housing type, and fuel type). The regions with the highest average household subsidy
(Northwest Arctic and Bering Straits) received nearly $3,000 or almost five times more than the region
with the lowest average household subsidy (Kodiak) at just over $600 per year, as shown in Figure 87.
Figure 87: Average heating fuel subsidy per participating household for LIHEAP/AKHAP (2000-2015)293
292 AEA analysis of LIHEAP and AKHAP data from Department of Health and Social Services, November 2016
293 AEA analysis of LIHEAP and AKHAP data from Department of Health and Social Services, November 2016
$- $20,000,000 $40,000,000 $60,000,000 $80,000,000 $100,000,000
Kodiak
North Slope
Aleutians
Copper River/Chugach
Bristol Bay
Southeast
Yukon-Koyukuk/Upper Tanana
Northwest Arctic
Bering Straits
Lower Yukon-Kuskokwim
Railbelt
Total LIHEAP and AKHAP funding by AEA energy region (2000-2015)
Source: DHSS LIHEAP/AKHAP data
Total LIHEAP (2000-2015)Total AKHAP (2009-2015)
$0 $1,000 $2,000 $3,000
Kodiak
Southeast
Railbelt
Lower Yukon-Kuskokwim
Aleutians
Copper River/Chugach
Yukon-Koyukuk/Upper Tanana
North Slope
Bristol Bay
Bering Straits
Northwest Arctic
Average subsidy per participating household
Average heating fuel subsidy per participating household for LIHEAP/AKHAP
Source: Alaska Department of Health and Social Services (2000-2015)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 153
The LIHEAP/AKHAP data make it clear that even with other local, State, and federal programs in place
aimed at making energy more affordable, many Alaska households still qualify for heating assistance using
objective measures of income, family size, and heating cost established by the LIHEAP/AKHAP programs.
This is true even in areas of the state with the lowest average energy prices, the Railbelt and Southeast,
and on the North Slope where borough subsidies greatly reduce heating fuel prices. This suggests that
existing programs are not sufficient to make energy truly affordable for all Alaskans, at least not without
programs like LIHEAP/AKHAP.
Municipal Energy Assistance Program
The Municipal Energy Assistance Program, created under Governor Murkowski in FY06294, provided
grants to communities with populations less than 2,500 before it was discontinued in FY08. The grants
could be used:
1. To repay any indebtedness of the city or borough to the Bulk Fuel Revolving Loan Fund;
2. To repay any indebtedness of the city or borough to a fuel company or fuel vendor; or
3. For the purchase of fuel by the city or borough.
The three years of funding is shown in Table 17.
Table 17: Municipal Energy Assistance Program 2006-2008295
Year Amount
2006 $6.5 million
2007 $48.0 million
2008 $48.7 million
STATE ENERGY LOAN PROGRAMS
Although State energy programs have historically
focused on grants, it is likely that future loans—either
from State or other sources—will provide a greater
share of the money needed to build energy
infrastructure projects.
Given the availability of grant funds, it is not surprising
that communities have not availed themselves of the
State’s energy loan products or loans products from
other sources, including private and federal financing.
Based on data from state and federal loan programs, it appears that many communities have made the
rational choice of waiting for grant opportunities instead of taking out loans.
294 Administrative Order No. 230. http://www.gov.state.ak.us/admin-orders/230.html
295 Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. “Components of Delivered Fuel Prices in Alaska.”
June 2008. http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
Although State energy programs have
historically focused on grant funds, it is
likely that future loans—either from the
State or other sources—will provide a
greater share of the money needed to build
energy infrastructure projects.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 154
Five State loan programs are discussed in this section: four are loans for capital expenses and one for
short-term credit.
Power Project Loan Fund (PPF)
AEA administers the Power Project Loan Fund (PPF), which is a revolving loan fund that provides low-cost
loans to local utilities, local governments, or independent power producers for the development,
expansion, or upgrade of electric power facilities, including distribution, transmission, efficiency and
conservation, bulk fuel storage, and waste energy.296 PPF loans often assist higher-risk communities that
would be unable to get traditional financing from banks and other government sources, or to fund energy
projects seeking lower-than-market rates. Loan repayments remain with the program and are available
for new loans.
Per 2010 State energy policy, the PPF was to become the primary funding source for energy projects.297
Yet even for communities within the AkAES region, which accounts for the greatest share of PPF loans,
this has not been the case as REF, RPSU, BFU, direct legislative appropriations and other grants funds have
remained available.
Since 1980, 119 loans have been requested by 70 applicants, with 87 loans actually disbursed.298 Of the
approximately $29 million currently disbursed or committed in the PPF, nine loans are currently being
repaid, three are still being disbursed, and two have been committed but not yet disbursed. No loans are
currently in default; however, a few loans have been forgiven by the State in the past. As of Aug. 31, 2016,
the outstanding balance of AEA’s Power Project loans was approximately $6.2 million. The regional
distribution of PPF applications is shown in Figure 88.
Figure 88: PPF applications by AEA energy region299
296 Power Project Loan Fund Fact Sheet. October 2016. http://www.akenergyauthority.org/Publications
297 AK Stat § 44.99.115 (through 27th Leg Sess 2012)
298 Power Project fund application data (1980-2016)
299 Power Project fund application data (1980-2016)
0 4 8 12 16
Bering Straits
Kodiak
Northwest Arctic
Copper River/Chugach
Railbelt
Yukon-Koyukuk/Upper Tanana
Bristol Bay
Aleutians
Southeast
Lower Yukon-Kuskokwim
Number of PPF applications from region
Regional distribution of applications to Power Project Loan Fund
Source: AEA data (2002-2016)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 155
Since 2002, the PPF has serviced between one and five communities per year. The total value of loans has
ranged between $60,000 and nearly $3 million per year. In the last few years, there has been a trend
toward smaller communities with lower loan amounts, primarily for generator repairs and replacements.
Figure 89: Power Project Loan Fund: principal advanced per year300
Loan terms are related to the productive life of the project and are not allowed to exceed 50 years. Interest
rates vary between zero, at the low end, and tax-exempt rates at the high end. As of Sept. 12, 2016, the
upper rate was 3.64%. The interest rate can be adjusted downward in certain circumstances to improve
financial feasibility.
Security for PPF loans is flexible and written to accommodate the ability of the applicant while maximizing
security for the State loan funds. Traditional types of security include: taking a security interest in
equipment, land, and other assets; cash reserve requirements; debt-service ratio requirements;
requirement to pledge revenue streams from business activities; and in the case of local governments
from other revenue sources as well (e.g. community assistance program revenue). The PPF loan program
also mitigates risk in less traditional ways including: requiring utilities that struggle with financial
management to maintain a relationship with a third party professional bookkeeping service; requiring
utilities that have a history of failure to maintain equipment to provide regular operations ; and
maintenance reporting and communication with AEA technical staff.
Bulk Fuel Loan program
AEA administered the Bulk Fuel Loan program from the late 1990s until 2013, when the Division of
Community and Regional Affairs (DCRA) took over management of the program. Loans from the Bulk Fuel
Revolving Loan Fund, currently capped at $750,000 per year are now made either as bulk fuel loans or
bulk fuel bridge loans as provided in AS 42.45.250-42.45.299. Bulk fuel bridge loans are specifically for
applicants that were rejected for a bulk fuel loan, and have zero percent interest rate for the first loan.
Loans may assist communities in purchasing bulk fuel, which can include diesel, heating oil, avgas, low
300 Power Project fund application data (1980-2016)
$867,822
$1,053,968
$889,954
$511,037
$1,172,633
$1,815,575
$975,924
$2,667,232
$1,345,454
$2,070,000
$1,906,285
$279,530
$648,609
$60,700
$0
$1,000,000
$2,000,000
$3,000,000
2002 2003 2004 2005 2006 2007 2008 2009 2011 2012 2013 2014 2015 2016
0
1
2
3
4
5
6
Total principalNumber of loansPower Project Loan Fund: principal advanced and number of loans per
calendar year
Source: AEA data
Number of loans per year Total Principal
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 156
sulfur diesel, and gasoline. Loans are limited to communities with populations under 2,000 and can be
made to a municipality, unincorporated village, private individual, or private company (including village
corporations) retailing fuel or electricity in a community.301
Borrowers must agree to secure bulk fuel revolving loans with revenues from fuel sales and other legally
available monies. They may be required to assign payments from the State of Alaska for funds they
expect to receive from Community Revenue Sharing, Payment in Lieu of Taxes (PILT), Power Cost
Equalization or other programs.302
While the DCRA and AEA Bulk Fuel loan programs were identical, DCRA made the Bridge loan available
for those communities that could not qualify for a Bulk Fuel loan. Since 2009, the Bridge loan has
comprised up to 25% of all fuel loans from the State. Chapter 4 includes an analysis of the reasons for
this.
Figure 90 shows the amount of lending under AEA’s Bulk Fuel loan, the DCRA Bulk Fuel loan, and the
DCRA Bridge loan. The annual total of all Bulk Fuel Loans increased steadily through 2009, when it held
relatively stable for a few years before decreasing over the past couple of years. The increase and
decrease broadly follow the cost of oil.
Figure 90: Bulk Fuel Loan program disbursements303
*Note: Bulk Fuel Bridge Loan data unavailable pre-2005.
Although most regions are served by the Bulk Fuel Loan program (the exceptions are the North Slope and
Copper River/Chugach regions), the primary beneficiaries are communities in the AkAES study area, as
shown in Figure 90. The Lower Yukon-Kuskokwim region was the recipient of nearly half of the loan value
301 https://www.commerce.alaska.gov/web/Portals/4/pub/Bulk%20Fuel%20Revolving%20Loan%20Fund%20Statutes.pdf
302 https://www.commerce.alaska.gov/web/dcra/BulkFuelLoanProgram.aspx
303 Unpublished data from AEA bulk fuel loan, unpublished data from DCRA bulk fuel loan and bulk fuel bridge loan, 2014 and
2015 DCRA annual reports.
$0
$5,000,000
$10,000,000
$15,000,000
$20,000,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Annual value of loansBulk Fuel Loan disbursements by year
Sources: AEA and DCRA Bullk Fuel Loan programs (2000-2015)*
AEA Bulk Fuel Loan DCRA Bulk Fuel Loan DCRA Bridge Loan
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 157
between 2000 and 2013, followed by Bristol Bay, Northwest Arctic, and Yukon -Koyukuk/Upper Tanana
regions, each of which received approximately 15% of the total value.
Figure 91: Total value of Bulk Fuel Loan program by AEA energy region (2000-2013)304
The Bulk Fuel Loan program has served an important niche by transferring higher risk loans from the
private sector to the government. In discussions with at least one fuel deliverer, removing the uncertainty
of getting repaid for fuel deliveries allowed them to continue delivering fuel to communities with a history
of poor repayment.305 A similar risk transfer is provided by regional fuel consolidators, such as the Norton
Sound Economic Development Corporation’s Consolidated Bulk Fuel program, which helped group and
negotiate the delivery of $4.1 million in fuel in 2014.306, 307
Even though loan recipients are required to provide security for repayment of the loans, the delinquency
rates were approximately 15% in 2014 and 14% in 2015.308, 309 See Chapter 4 for further analysis of risks
associated with the Bulk Fuel Loan program.
Sustainable Energy Transmission and Supply
The Sustainable Energy Transmission and Supply (SETS) program is a loan program managed by AIDEA.
The SETS loan fund was capitalized in 2013 and 2014 with $67.5 million and $125 million, respectively.
AIDEA has a number of loan products that can be accessed through SETS, including loan participation,
direct loans, and loan guarantees.310 No loans have been serviced in the AkAES study area. To date, the
SETS has been used solely for the Interior Energy Project, a project to bring LNG to Fairbanks.
304 Unpublished data from AEA bulk fuel loan
305 Trevor Crowder, Everts Fuel, personal communication 4/25/2016.
306 http://www.nsedc.com/programs/community-benefits/consolidated-bulk-fuel/
307 http://www.nsedc.com/wp-content/uploads/267304-NSEDC-AR-proof.pdf
308 DCRA, “Bulk Fuel Revolving Loan Program Annual Report 2014”
309 DCRA, “Bulk Fuel Revolving Loan Program Annual Report 2015”
https://www.commerce.alaska.gov/web/Portals/4/pub/BulkFuelAnnualReport.pdf
310 http://www.aidea.org/Programs/EnergyDevelopment.aspx
$- $20,000,000 $40,000,000 $60,000,000
Lower Yukon-Kuskokwim
Bristol Bay
Northwest Arctic
Yukon-Koyukuk/Upper Tanana
Aleutians
Southeast
Kodiak
Bering Straits
Railbelt
Total value of Bulk Fuel Loan program by AEA energy region (2000-2013)
Source: AEA data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 158
Alaska Energy Efficiency Revolving Loan Program
The Alaska Energy Efficiency Revolving Loan Program (AEERLP), administered by AHFC since the loan’s
creation in 2010, provides financing for permanent energy efficiency improvements to buildings owned
by regional educational attendance areas, the University of Alaska and the State of Alaska municipalities.
The loan can be repaid through guaranteed savings from energy efficiency improvements identified in an
Investment Grade Audit.311 The ability to use expected savings from efficiency improvements as security
is a unique feature of AEERLP; almost all other loans require collateral, adequate cash flow, and other
measures to guarantee that the loan can be repaid. For many lenders, the future is too uncertain—from
energy price fluctuations, changes in building use, or ownership, etc.—to base the repayment of a loan
on future energy savings.
Although the enabling legislation allowed for AHFC to bond for up to $250 million to support AEERLP, it is
not clear that there is a need for the program or if the requirements to access program funds are too
restrictive. In an attempt to develop customers for AEERLP, auditors conducted 327 energy audits
throughout the state, including approximately 58 percent in the AkAES study area. Although building
owners and operators welcomed the audits, no loans have resulted through the program as of November
2016.312
AHFC contacted building owners or their representatives for 76% of the audited buildings. Of these, 84%
said they had implemented some of the recommended energy efficiency measures. Of these, 29% were
funded with bonds, 22% with grants, and 33% with cash on hand. The remainder did not report how they
funded their projects.313
Energy Efficiency Interest Rate Reduction
The Energy Efficiency Interest Rate Reduction (EEIRR) program is a program to promote energy efficiency
in existing and newly constructed homes. As the name implies, the EIRR provides a reduced interest on
mortgages financed through AHFC. The interest rate reduction is available either for new or existing
energy-efficient properties that meet specific criteria or existing properties that perform efficiency
upgrades.314
311 https://www.ahfc.us/efficiency/non-residential-buildings/energy-efficiency-revolving-loan-fund-aeerlp/
312 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
313 VEIC 2016
314 https://www.ahfc.us/efficiency/energy-programs/energy-efficiency-rate-reduction/
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 159
Table 18: Energy Efficiency Interest Rate Reduction based on efficiency improvement315
Access to
natural
gas
No access
to natural
gas
1 Step: -0.125% -0.250%
2 Steps: -0.250% -0.375%
3 Steps: -0.500% -0.625%
4 Steps: -0.625% -0.750%
Although the EEIRR program does not provide an upfront grant for efficiency improvements, it can provide
significant financial incentives for efficiency improvements in existing structures. For instance, if a
property with a $200,000 mortgage achieves the 0.625% reduction, the interest payments would be
reduced over $900 per year.
Only 571 EEIRR loans were closed between 2012 and 2014. Eighty-seven percent of the loans were in
Railbelt communities, and no EEIRR loans were financed in small, rural communities in the AkAES study
area.316
Existing and new energy-efficient properties that meet either the Five Star Plus or Six Star energy rating
can receive interest rate reductions as well.317 Without new funding for the Home Energy Rebate program
the EEIRR remains the best option for improving the energy efficiency of residences not eligible for the
low-income Weatherization Assistance Program.
Alternative Energy and Conservation Loan
The Alaska Department of Commerce, Community and Economic Development (DCCED) offers the
Alternative Energy and Conservation Loan Fund for small businesses to construct and install alternative
energy systems or make energy efficiency improvements in commercial buildings. The legislature
amended the Alternative Energy Loan program in 2010 and made it effective in 2012, with a capital outlay
of $2.5 million. The maximum loan amount from the fund is $50,000 and the maximum loan term is 20
years. At the end of 2015, no loans had yet closed.318 Some of the reasons why no loans have been closed
include: lighting retrofits are not allowed, the applicant must have been denied by two financial
institutions, and the maximum loan amount is insufficient for retrofitting many commercial facilities.
OTHER STATE ENERGY PROGRAMS
In addition to grant, subsidy and loan programs, Alaska has a number of programs that provide technical
assistance and other energy-related services. The three programs addressed in this section are
administered by DOT&PF and AEA, and does not cover all technical assistance provided by State energy
315 https://www.ahfc.us/efficiency/energy-programs/energy-efficiency-rate-reduction/
316 AEA analysis of AHFC EEIRR data
317 https://www.ahfc.us/efficiency/energy-programs/energy-efficiency-rate-reduction/
318 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 160
program staff. Other technical assistance activities provide benefits to communities but are not codified
in statute or regulations.
Public Facilities Energy Efficiency Improvement Program
Passed in 2010, the Alaska Sustainable Energy Act (SB220 Chapter 83 SLA10) required that DOT&PF retrofit
25% of all state-owned facilities of at least 10,000 square feet by 2020. DOT&PF achieved this requirement
in 2014. To accomplish this, DOT&PF used a combination of commercial financing, American Recovery
and Reinvestment Act (ARRA) funds as well as agency deferred maintenance funds. The energy efficiency
work completed to date is saving the State over $2.8 million each year in energy costs, based on estimated
costs and savings.319 The net savings is less, as some of the energy savings are being used to pay off the
loans.320
The DOT&PF program is an excellent example of how a clearly defined energy efficiency goal can lead to
benefits for the State and individual communities. By reducing energy costs in State buildings, money is
available for more productive programs and core agency services, providing indirect benefits to
communities. One likely reason for this program’s success is the close, clear alignment between the policy
requirement and the authority of the organization tasked to fulfill it. As the owner and operator of the
buildings, the State clearly has the authority to effect the necessary upgrades. The legislation also included
meaningful metrics to track program success. Given the number and size of state buildings, an economy
of scale is created throughout the program.
DOT&PF has also provided technical assistance to other government entities including the City of Sitka
and, in 2015, the Anchorage School District.321 An opportunity exists for the expertise and resources
developed through this program to be expanded beyond State buildings. As discussed in Chapter 6, there
is a significant cost-effective energy efficiency potential throughout the AkAES study area for both public
and privately-owned non-residential buildings.
Circuit Rider & Technical Assistance
Under 3 AAC 108.200 – 240, the Alaska Energy Authority’s Circuit Rider program provides utilities in
communities with populations of less than 2,000 with technical assistance to improve the efficiency,
safety and reliability of their power systems, and to reduce the risk and severity of emergency
conditions.322 AEA is required by statute Sec. 42.45.900 to provide this service to communities.323
Through the Circuit Rider & Technical Assistance program, AEA instructs rural utility operators and
managers in the proper operations and maintenance of their generation and distribution infrastructure.
Technical staff can help diagnose and troubleshoot issues through remote monitoring, or can provide
onsite training, technical consultation, assistance and minor repairs. The program does not provide
319 Department of Transportation and Public Faculties. “Alaska Sustainable Energy Act: Annual Report. 2015 Progress Report.”
January 2016
320 Rebecca Smith. Personal correspondence. 11/8/2016.
321 Department of Transportation and Public Faculties. “Alaska Sustainable Energy Act: Annual Report. 2015 Progress Report.”
January 2016
322 Circuit Rider Program Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
323 http://www.legis.state.ak.us/basis/folioproxy.asp?url=http://wwwjnu01.legis.state.ak.us/cgi-
bin/folioisa.dll/stattx15/query=[JUMP:%27AS4245900%27]/doc/{@1}?firsthit
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 161
funding for major repairs or reconstruction of utility systems, nor does it replace the need for rural
utilities’ maintain an operations and maintenance budgets.324
The Circuit Rider & Technical Assistance program, in concert with other AEA programs, has reduced the
number of catastrophic events, according to AEA program staff.325 Quantitative data on the communities
assisted by the Circuit Rider program is only available from 2015 through the third quarter of 2016. In less
than two years, 61 utilities, all located in the AkAES study area, received assistance from the Circuit Rider
program, including some who received services up to four times.
As a share of the total operations and maintenance costs for all utilities and energy infrastructure in the
AkAES study area, the Circuit Rider program represents well under one-tenth of one percent. Although
the relative cost is very low, the program, at least anecdotally, has had positive impacts on energy safety,
reliability and affordability by preventing catastrophic events and helping to protect investment in rural
energy infrastructure.
Electrical emergency assistance
Under 3 AAC 108.200 – 240, the Alaska Energy Authority provides on-call emergency response to reduce
imminent threat to life or property during extended power outages. If an eligible utility suffers an
electrical emergency, AEA, subject to the availability of appropriations, assists the utility in re-establishing
power to the utility's customers in a manner that does not constitute a sig nificant threat to life or
property. Assistance may include financial or technical assistance, including emergency repairs.326
Since emergencies cannot be planned for, the amount of annual program funding shown in Figure 92 is
based on the actual costs incurred in responding to calls each year. There is no clear trend in annual
costs from 2005 to 2015.
Figure 92: Cost of AEA electrical emergency response per year327
324 Circuit Rider Program Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
325 Kris Noonan, personal communication, December 2016.
326 Circuit Rider Program Fact Sheet, October 2016.
327 AEA analysis of unpublished Electrical Emergency Response program data
$0
$200,000
$400,000
$600,000
$800,000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Cost of AEA electrical emergency response per year (2005-2015)
Source: AEA data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 162
Figure 93: Electrical Emergency Response cost per AEA energy region per year328
The highest costs for responding to electrical emergencies are in the Lower-Yukon-Kuskokwim and Yukon-
Koyukuk/Upper Tanana regions, as shown in Figure 93.
Slightly more than half (41 out of 70) of all communities accessing Electrical Emergency Response services
between 2005 and 2015 had incidents requiring assistance in more than one year, as is shown in Figure
93. For example, the figure shows that 10 communities accessed emergency response in six to seven years
between 2005 and 2015.
Figure 94: Frequency of communities accessing AEA Electrical Emergency Response (2005-2015)329
328 AEA analysis of unpublished Electrical Emergency Response program data
329 AEA analysis of unpublished Electrical Emergency Response program data
$- $300,000 $600,000 $900,000 $1,200,000 $1,500,000
Lower Yukon-Kuskokwim
Yukon-Koyukuk/Upper Tanana
Bristol Bay
Northwest Arctic
Bering Straits
Kodiak
Aleutians
Copper River/Chugach
Southeast
Electrical emergency response cost per energy region per year (2005-2015)
Source: AEA data
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
0
5
10
15
20
25
30
1 2-3 4-5 6-7 8-9 10Number of communities accessing emergency response servicesNumber of years in which the same community accessed emergency response services
Frequency of community accessing AEA Electrical Emergency response
(2005-2015)
Source: Analysis of AEA data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 163
The electrical emergency response program directly benefits communities by assisting utilities in re-
establishing power in a manner that does not constitute a significant threat to life or property, and it
protects investments in rural infrastructure by addressing problems before a catastrophic emergency
occurs.330
The average community size for Electrical Emergency Response is 229 and the median is 151, both of
which are smaller than the median community size in the AkAES study area. About 93% of Electrical
Emergency Response expenditures were for standalone village- and city-owned utilities. Regional co-ops
and regional investor-owned utilities (IOUs) accounted for 1% of all expenditures.331 The data appears to
confirm the benefits of larger utility structures in assisting smaller communities, either in reducing the
number of emergency episodes or by being able to respond to the emergency without State assistance.
AEA training programs
AEA provides training opportunities for local
residents to learn how to operate and maintain
their energy infrastructure and keep facilities code-
compliant and sustainable. Proper maintenance
and operation of energy infrastructure are essential
components of delivering safe, stable, reliable, and
affordable power to a community. Currently, there
are no administrative or regulatory requirements
for utilities to prove the maintenance and operational capacity to deliver the services required of them as
a utility.
AEA contracts with Alaska Vocational Technical Center (AVTEC) in Seward to deliver training courses that
include: Power Plant Operator, Advanced Power Plant Operator, Bulk Fuel Operator, and Hydroelectric
training.
AEA also provides training on an as-available basis for utility clerks in PCE reporting, RCA reporting, and
general accounting practices.332
330 Kris Noonan, personal communication, December 2016.
331 AEA analysis of unpublished Electrical Emergency Response program data
332 Training Programs Fact Sheet, October 2016. http://www.akenergyauthority.org/Publications
Proper maintenance and operation of
energy infrastructure are essential
components of delivering safe, stable,
reliable, and affordable power to a
community.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 164
Figure 95: Number of trainees per AEA course333
Power plant and bulk fuel operator courses each account for one-third of all trainees, as shown in Figure
95. Utility clerk training accounts for approximately 17%, with the balance made up by other financial and
management and hydro trainees.
From 1995 to 2015, more than 1,400 individual trainings were started and approximately 87% completed
by about 1,000 different participants from 160 communities. Individual training participants took between
one and six courses. The breakdown of participation by region is in Table 19.
Table 19: AEA training program participation by region (1995-2014)334
AEA energy region Communities
Trainings
completed
Average
participants per
community
Lower Yukon-Kuskokwim 41 491 14
Yukon-Koyukuk/Upper Tanana 27 169 8
Bristol Bay 24 165 7
Bering Straits 15 115 10
Aleutians 10 89 9
Kodiak 6 60 11
Northwest Arctic 10 59 7
Southeast 15 48 3
Copper River/Chugach 4 28 8
Railbelt 4 18 5
North Slope 3 5 3
Good utility operations and maintenance relies on qualified, well-trained staff; high staff turnover makes
this challenging. AEA’s training program has helped to train new hires and allow for continued professional
333 AEA analysis of unpublished AEA training data (1995-2014)
334 AEA analysis of unpublished AEA training data (1995-2014)
0 100 200 300 400
Elec. utility business training
Bulk fuel book
Bulk fuel management
Hydro
Adv. power plant operator
Itinerant bulk fuel operator
Utility clerk
Bulk fuel operator
Power plant operator
Number of trainees per AEA course
Source: AEA data (1995-2014)
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 165
development for experienced personnel. Quantifying the benefits of any training program is difficult, and
AEA was unable to find sufficient data to support quantitative analysis.
In particular, it is not clear how to interpret the participants-per-community data in Table 19. The high
number of trainees from some small communities is either an indication of high staff turnover or that the
community has found benefit in having multiple people trained, or a combination of factors. There is a
common perception that personnel turnover at rural utilities is high, and the list of training participants
kept by AEA suggests that is true with some exceptions. A few participants in AEA’s training program have
remained at the same utility since the 1990s; these employees have taken multiple AEA courses over that
time. AEA’s 2015 bulk fuel assessment provided another source of information about rural utilities that
showed a staff experience, but not tenure. That evaluation of 56 communities, pre-identified as being
most in need, showed that the 130 bulk fuel operators in those commun ities had an average of 10 years
of experience.335
NON-PROGRAMMATIC DIRECT LEGISLATIVE APPROPRIATIONS
Outside of the State energy programs, the Legislature has also funded energy projects through direct
appropriations. Direct appropriations ranged in size from $25,000 for a biomass pilot project in the
Southeast to $180.9 million for planning the Susitna Hydroelectric project. The amount of annual
appropriations by AEA energy region is shown in Figure 96.
Figure 96: Non-programmatic state direct legislative energy appropriations by AEA energy region336
335 AEA analysis of data from Alaska Energy Authority. “Bulk Fuel Inventory Assessment Report.” 2016.
336 Data from Office of Management and Budget, 2015.
$- $150,000,000 $300,000,000 $450,000,000 $600,000,000
Bering Straits
Northwest Arctic
Yukon-Koyukuk/Upper…
Undesignated
Bristol Bay
Kodiak
Copper River/Chugach
Statewide
Lower Yukon-Kuskokwim
Southeast
Railbelt
Non-programmatic direct legislative appopriations by AEA energy region
(FY12-FY15)
Source: Office of Management and Budget
FY 2012 FY 2013 FY 2014 FY 2015
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 166
For the four fiscal years from 2012 to 2015, the Railbelt received nearly 80% of all direct legislative
appropriations. Appropriations for Railbelt projects included funding for the Susitna-Watana Dam, the
Interior Energy Project, and an additional $200 million for other projects. About 79% of appropriations for
Southeast went to Sitka. The figure does not include $379.2 million for the In-State Gas Pipeline Fund,
otherwise known as the Alaska Stand Alone Pipeline (ASAP) project.
Table 20 shows direct legislative appropriations by energy region on a per capita basis for FY12 through
FY15. The average per capita funding amount across the state is nearly $1,000. Four regions received more
than the average, while two regions received no direct appropriations for energy projects. The regional
distribution shows that non-programmatic legislative appropriations have not generally targeted areas
with the highest energy costs. With the exception of the Lower Yukon-Kuskokwim, the largest recipients
of direct legislative appropriations, both on a total and per capita basis, were regions with lower energy
costs.
Table 20: Per capita direct legislative appropriations by AEA energy region337
AEA energy region
Funding
per capita
Copper River/Chugach $1,830
Lower Yukon-Kuskokwim $1,230
Southeast $1,090
Railbelt $1,000
Kodiak $440
Bristol Bay $350
Yukon-Koyukuk/Upper Tanana $190
Northwest Arctic $130
Bering Straits $30
Aleutians $0
North Slope $0
FUNDING LEVELS FOR STATE AND FEDERAL ENERGY PROGRAMS
This section outlines how State and federal funding for various energy programs has changed over time.
While this is not an exhaustive index of funding sources, Figure 97 captures the largest and most
consistent State and federal funding sources. The chart shows how funding levels and sources have
changed over time as the availability of funds and priorities have changed.
Funds not represented in the chart include: State and federal loans; some large, technology-specific grants
to Alaska communities from the U.S. Department of Energy; some funding for the Railbelt (some Railbelt
spending is included, but Railbelt data was not systematically researched or collected since the region is
not in the AkAES study area); and tax credits and other incentives for natural gas exploration and
337 AEA analysis of Office of Management and Budget data
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 167
development in the Cook Inlet region. A number of State and federal programs were also left out because
their funding levels were too low to be reflected on the chart. These include training, electrical emergency
response, Circuit Rider & Technical Assistance, Emerging Energy Technology Fund, and Village Energy
Efficiency Program.
Two large appropriations are omitted from Figure 97. A $400 million deposit into the PCE Endowment
Fund, which was excluded from the direct appropriation totals since deposits into the endowment fund
are not spent, but serve as a source of long-term investment income. The $379.2 million allocated to the
ASAP gasline project funding is also not included in the chart.
February 2017 CHAPTER 5: Recent and Current Alaska Energy Programs Page | 168
Figure 97: Historical State and federal energy funding
$-
$100,000,000
$200,000,000
$300,000,000
$400,000,000
$500,000,000
$600,000,000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
State and federal funding sources for energy in Alaska
Sources: Multiple
State Direct legislative appropriations
(AkAES study area)
State Direct legislative appropriations
(Railbelt)
State HER
State Wx
State RPSU
State BFU
State REF
State Municipal Energy Assistance
State AKAHP
State PCE
Federal Other--Denali Com
Federal RPSU--Denali Com
Federal BFU--Denali Com
Federal USDA grants
Federal LIHEAP
February 2017 CHAPTER 5: Current Alaska Energy Programs Page | 169
Federal funding has generally declined from a high of more than $300 million in 2002. Denali Commission
funding spiked in 2002 with $230 million allocated for RPSU and BFU projects. Not all of the funds
allocated in 2002 were spent in that year as the funding was spread over the next several years. Total
federal funding was less than $50 million in 2015, most of which was for LIHEAP. The federal funding levels
before 2009 are underreported, since AEA does not have pre-2009 data for USDA. LIHEAP has been a
consistent and sizeable source of energy subsidy over the past 15 years.
Identified State energy funding peaked in 2008, with more than $400 million in allocations not including
direct appropriations. This included $100 million for REF, $200 million for the Weatherization Assistance
Program, and $100 million for the Home Energy Rebate program. Not all 2008 allocations were spent that
year. Direct legislative appropriations, which were sizeable from 2012 to 2015, also existed in previous
years, but the data was not systematically captured for earlier years. In 2014, direct legislative
appropriations for Railbelt projects were more than half of all government energy funding. Overall, PCE
has been the State’s most consistent, though not the largest, source of energy funding.
HOW STATE ENERGY PROGRAMS HELP TO ACHIEVE STATE ENERGY POLICIES
In 2010, the State Legislature declared a State energy policy under AS 44.99.115. As part of that energy
policy, five key intentions were outlined:
1. The state [should] achieve a 15% increase in energy efficiency on a per-capita basis between 2010
and 2020;
2. The state [should] receive 50% of its electric generation from renewable and alternative energy
sources by 2025;
3. The state [should] work to ensure a reliable in-state gas supply for residents of the state;
4. The Power Project Fund (AS 42.45.010) [should] serve as the main source of state assistance for
energy projects; and
5. The state [should] remain a leader in petroleum and natural gas production and become a leader
in renewable and alternative energy development.
The first two policies will be explored in more depth in this section. The fourth policy, concerning the PPF,
has already been reviewed. The third policy will be partially addressed in the next section and the fifth is
outside of the purview of this report.
Understanding how current State energy programs have helped to achieve these energy policies sheds
light on how well current programs are aligned with State policy, as well as how the AkAES can most
effectively achieve its policy goals. Four questions will aid in developing this understanding: Which entities
are ultimately responsible for achieving the goal? What requirements are pla ced on those entities? How
can State energy programs help to achieve the goal? How is progress towards the goal tracked?
THE STATE WILL ACHIEVE A 15% INCREASE IN ENERGY EFFICIENCY ON A PER-CAPITA BASIS
BETWEEN 2010 AND 2020.
Who is ultimately responsible?
Residential and non-residential building owners and occupants
February 2017 CHAPTER 5: Current Alaska Energy Programs Page | 170
What requirements exist for the entities responsible for achieving the goal?
Legislation from 2010 suggests the building energy codes should be encouraged338, but no building
energy codes have been enacted statewide.
The Alaska Sustainable Energy Act (SB220 Chapter 83 SLA10), passed in 2010, required that the
DOT&PF retrofit 25% of all state-owned facilities that are at least 10,000 square feet by 2020. DOT&PF
met the requirement by 2014.
AS 42.45.130 requires that each “eligible electric utility shall cooperate with appropriate State
agencies to implement cost-effective energy conservation measures…”339
No other requirements exist for reducing either thermal or electric energy consumption in the state.
Which State of Alaska energy programs help to achieve the goal?
A number of State energy programs can help to achieve the energy efficiency goal. State energy
efficiency grant programs include: Weatherization, Home Energy Rebate/New Home Rebate, and the
Village Energy Efficiency Program.
State loan programs that can be used for energy efficiency include: The Power Project Loan fund, the
Alaska Energy Efficiency Revolving Loan fund, the Alternative Energy and Conservation Loan, and the
Sustainable Energy Transmission and Supply Development fund. The DOT&PF’s Public Facilities Energy
Efficiency Improvement program also helps to achieve the statewide efficiency goal.
In addition to the DOT&PF energy program, technical assistance for energy efficiency is provided
through AEA and AHFC energy efficiency programs. Aside from supporting specific funded projects
and programs, AEA and AHFC efficiency programs are not codified in law or regulation.
What reporting requirements are there for tracking progress towards the goal?
The Alaska Office of Management and Budget is directed to work with State agencies to develop a
standardized methodology to collect and store energy consumption and expense data.340
There are no reporting requirements for any sector. Electricity consumption is tracked through PCE
and Energy Information Authority (EIA) for other purposes. No heating or transportation fuels
consumption data is systematically collected or stored. Some fuel price data is tracked but not
required.
THE STATE WILL RECEIVE FIFTY PERCENT OF ITS ELECTRIC GENERATION FROM RENEWABLE AND
ALTERNATIVE ENERGY SOURCES BY 2025
Who is ultimately responsible for achieving the goal?
Electric utilities, distributed generation owners, and independent power producers
What requirements exist for the entities responsible for achieving the goal?
338 AS 44.99.115
339 AS 42.45.130
340 AS 37.07.040(12)
February 2017 CHAPTER 5: Current Alaska Energy Programs Page | 171
No requirements exist for utilities to install renewable or alternative energy systems or reduce
consumption of diesel, natural gas, or naphtha.
AS 42.45.130 requires that each “eligible electric utility shall cooperate with appropriate state
agencies to … plan for and implement feasible alternatives to diesel generation.”341
What State of Alaska energy programs help to achieve the goal?
A number of State energy programs can help to achieve the renewable and alternative energy goal.
Aside from direct legislative appropriations and the Susitna-Watana Dam project, which is outside the
scope of this study, the Renewable Energy Fund is the primary grant program that helps to achieve
this goal. AEA’s RPSU program has assisted communities to integrate hydro and wind projects in a
number of communities. The Emerging Energy Technology Fund aims to aid in the development of
alternate energy sources for communities, though grants are unlikely to result in additional renewable
generation before 2025 due to the pre-commercial status of the technologies funded.
A number of loan programs can be used to fund renewable and alternative energy infrastructure,
including AIDEA’s SETS program, AEA’s PPF, and the DCCED Alternative Energy and Conservation Loan
fund.
AEA’s Alternative Energy and Energy Efficiency and Rural Energy Groups provide technical assistance
for alternative and renewable energy development and implementation. Aside from providing
technical assistance for REF and other legislatively funded capital projects, the program is not codified
in law or regulation.
What reporting requirements are there for tracking progress towards the goal?
No specific reporting requirements exist to track renewable and alternative electric generation,
although electric generation by source is collected by AEA through the PCE program and by the
federal EIA for other purposes. This data is published by AEA as the Alaska Energy Statistics.
LESSONS LEARNED
1. Voluntary participation in programs requires targeted, predictable incentives. Many of the State’s
energy programs respond to community applications and requests, which requires that participants
have the capacity needed to comply with requirements of the program. Programs such as the Home
Energy Rebate program and Renewable Energy Fund have been very effective with sectors that exhibit
sufficient capacity but less successful with other groups.
2. Proactive grant programs, such as the Weatherization program that search to find eligible applicants,
can be very successful in developing projects in underserved markets.
3. Loan and other debt financing programs are not, by themselves, effective in incentivizing
development of new renewable energy or energy efficiency projects. Technical, communication, and
financial barriers to participation must be addressed before non-grant financing can be effective.
341 AS 42.45.130
February 2017 CHAPTER 5: Current Alaska Energy Programs Page | 172
4. As seen by the DOT&PF program, requiring energy efficiency improvements for public building owners
can be effective and cost-efficient, assuming the owner has the authority and means to make the
improvements. By extension, other requirements could provide cost-effective savings.
5. A number of programs exist outside the scope of the 2010 State energy policy goals articulated in AS
44.99.115, including:
a. Rural Power System Upgrade program
b. Bulk Fuel Upgrade program
c. Circuit Rider & Technical Assistance program
d. Electrical Emergency Response,
e. Power Cost Equalization
f. Alaska Heating Assistance Program
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 173
CHAPTER 6: INFRASTRUCTURE AND NON-INFRASTRUCTURE
OPPORTUNITIES TO REDUCE COMMUNITY ENERGY COSTS
This chapter will explore various infrastructure and non-infrastructure strategies and opportunities for
reducing the cost of energy in communities within the study area. Although there are opportunities
available in all communities, no single solution or suite of solutions will quickly reduce energy costs for all
consumers in all communities. The purpose of this chapter is to evaluate and compare the potential
opportunities that will represent the best return. It should be noted that although much of this chapter
addresses infrastructure projects, for those
communities that do not have cost-effective
infrastructure projects, AEA has identified other
cost savings measures. The end of Chapter 6
includes a comparison of the cost-effectiveness of
the various project types.
This chapter draws heavily from existing research done over the past decade, as well as research and
analysis performed as a part of the AkAES project. The work covers existing and new that investigate
resource and technology feasibility and pull from the Alaska Center for Energy and Power (ACEP), Alaska
Housing Finance Corporation (AHFC), Cold Climate Housing Research Center (CCHRC), Northern
Economics, U.S. Army Corps of Engineers (USACE), Vermont Energy Investment Corporation (VEIC),
Institute of Social and Economic Research (ISER), Denali Commission, National Renewable Energy
Laboratory (NREL), and previous AEA studies, among others.
In particular, the Alaska Affordable Energy Model (AAEM), an AEA-designed model programmed by the
University of Alaska Fairbanks’ (UAF) Geographic Information Network of Alaska (GINA), is used
extensively to evaluate energy infrastructure opportunities in study-area communities. The AAEM uses
Key Takeaways
1. Almost all communities have at least one cost-effective opportunity for more affordable
energy.
2. Energy efficiency—for both residential and non-residential buildings and facilities—is the most
common, has the highest expected savings, and is consistently the most cost-effective
opportunity across the AkAES study area.
3. In order to perform thorough evaluations of potential opportunities in a community, a
significant amount of detailed data is required and much of that data is not readily available.
4. Many of the best bets for more affordable energy, such as non-residential efficiency, are not
currently being pursued very often.
5. Non-infrastructure opportunities such as improved business management may also hold
significant potential for reducing community energy costs.
….no single solution or suite of solutions
will quickly reduce energy costs for all
consumers in all communities
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 174
the best data available for each community, including resource assessments, residential and non-
residential building audits, energy consumption information, and generation infrastructure details.
The AAEM uses historical and status quo data on energy costs, consumption, generation, and
infrastructure to create a snapshot of energy use and costs in a community. The AAEM provides a high-
level assessment of opportunities based on numerous data sources, including the Alaska Energy Data
Gateway, the Alaska Retrofit Information System, the Alaska Energy Data Inventory, AEA’s Renewable
Energy Fund program, work performed by the ACEP, ISER, the Department of Energy, national
laboratories, and numerous other sources.
Forecasts were developed for the factors that will lead to changes in the consumption, generation and
costs of energy in a community. These factors include the prices of diesel, heating oil and electricity,
community population, and trends in consumption. Consumption trends are calculated by the model for
each community and/or intertie.
The most recent and best data on resource availability (including wind, hydro, solar, residential and non -
residential efficiency, diesel efficiency, and heat pumps) are captured from multiple sources. If a study
has estimated the costs and generation for a proposed project, those values are incorporated into the
model, otherwise regional or statewide average values are used.
A community-level economic analysis is performed by integrating the status quo, forecasted and resource
data for all potential resources in a community. A reconnaissance-level analysis is provided for each
potential resource, which allows a community or potential investor to compare opportunities available to
the community and identify the best, most cost-effective opportunities to pursue.
For a comprehensive description of the model, please see Appendix B and the model documentation.342
Community-specific model outputs, which will be available via AEA’s website
(www.akenergyauthority.org), are intended to help guide communities toward infrastructure
opportunities most likely to be cost-effective. In this chapter, the community-level results are aggregated
by AEA energy regions.
OPPORTUNITIES INVESTIGATED FOR MORE AFFORDABLE ENERGY IN COMMUNITIES
Figure 98 is a reprint Figure 25, first used in Chapter 3 to provide a framework for understandi ng the
components of bringing more affordable energy to communities. Each of the boxes in the figure
represents both potential opportunities and impediments to reducing the cost of energy in study area
communities. There are a limited number of ways to reduce consumers’ energy costs.
342 http://www.akenergyinventory.org/energymodel
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 175
Figure 98: Components of consumer energy costs
The following sections of this chapter include the options investigated. Not all of the investigations and
studies were able to identify a viable opportunity. In these cases, changes or improvements in technology
and/or better data may result in viable projects.
For the analysis in this chapter, it is important to remember that all of the options are compared against
the status quo, which in most cases is grant-funded infrastructure. A key assumption for this analysis is
that all new infrastructure will be debt financed with a 5% interest rate.
CROSS-CUTTING OPPORTUNITIES FOR ELECTRICITY AND HEATING COST REDUCTION
Some options could potentially reduce the cost of both heat and electricity and will be explored in this
“cross-cutting” section.
CHANGE FUELS
A common hope expressed by many Alaskans is that there might be a lower cost alternative fuel to diesel
and heating oil. As part of the AkAES, two potential fuel switching options were investigated: liquefied
natural gas (LNG) and propane.
AEA commissioned a study to investigate the feasibility of LNG as an alternate fuel in the AkAES study
area. The results of that study, performed by Anchorage-based Northern Economics with engineering
consultation from Michael Baker International, did not indicate that LNG was likely to be economically
feasible as an alternate fuel for electricity generation, thermal loads, or a combination of uses.343 There
343 Northern Economics, Inc. “LNG Feasibility for Alaska Affordable Energy Strategy Communities.” Prepared for Alaska Energy
Authority. July 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/LNGFeasibilityStudy2016.pdf?ver=2016-07-29-
145517-400
Consumer
Electric Rate
Consumer
Electricity
Consumption
Consumer
Heating Fuel
Rate
Consumer
Heating Fuel
Consumption
Consumer
Electricity Cost
Consumer
Heating Fuel Cost
Total Consumer
Energy Cost
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 176
are indications that communities and utilities may be interested in LNG for reasons aside from reduced
cost, particularly for meeting air quality requirements, as has recently been the case in Tok.344
While the commodity cost of LNG can be significantly cheaper than diesel and heating oil—as little as 20%
of the cost per unit of energy at the export terminal—the complex logistical, safety, storage, and
infrastructure requirements to use the LNG increase the retail cost in the community. Even though LNG is
cooled to -260 degrees Fahrenheit, LNG is less energy dense than diesel, necessitating 1.7 gallons of LNG
to replace each gallon of diesel. Since LNG must remain very cold or it will expand and gasify, a very heavy,
specially insulated container is required. For most uses, the weight of the container is greater than the
weight of the LNG delivered, increasing the cost of delivery. Even with a specially insulated container, LNG
has a limited shelf life (approximately 90 days before off gassing becomes problematic) that would
prevent LNG from being used as the sole fuel in communities without year-round access to barge
service.345
Similarly, in a 2010 study commissioned as part of the “Pathways” report, AEA determined that propane
was not a viable alternative to heating oil in study area communities.346 Propane could be a viable
electricity replacement in certain applications—particularly cooking appliances and water heaters—but
due to many of the same the logistical challenges as LNG (lower energy density, heavy container), it does
not appear to be a viable solution for community heating needs.347 In many study area communities,
propane appears to be priced competitively with electricity.348
AEA did not investigate the viability of local gas resources. In 2016, both Ahtna and Doyon investigated
potential resources in the Copper Valley and Minto Flats areas, respectively. The Doyon investigation in
2016 did not find commercially-viable deposits of oil and gas. 349 The results of the Ahtna drilling program
were not made public before the completion of this report. State investment in these two projects will
likely be approximately $9 million for the Copper Valley project and $60 million for the Minto Flats
exploration. To put this in perspective, the $9 million on the Copper Valley project could weatherize 28%
of the existing residential buildings still to be weatherized in the Copper Valley/Chugach region.
FUEL TRANSPORTATION IMPROVEMENTS
Increasing the efficiency of delivering fuel into communities has been proposed by a number of previous
studies as a possible way of reducing the cost of fuel in communities.
344 Tim Ellis. “Utility officials: Test project shows LNG could help reduce cost of generating electricity in Tok.” 11/4/2016.
http://fm.kuac.org/post/utility-officials-test-project-shows-lng-could-help-reduce-cost-generating-electricity-tok
345 Northern Economics, 2016.
346 Western Alaska Propane Conversion. Discussion Paper. 2010.
ftp://ftp.aidea.org/2010AlaskaEnergyPlan/2010%20Alaska%20Energy%20Plan/Propane%20Study/AEA_Plan_Propane.pdf
347 Alaska Gasline Development Corp. In-State Propane Utilization Study for the Alaska Gasline Development Corporation. July
1, 2011. http://www.arlis.org/thepipefiles/Record/1465394
348 AEA analysis of data from Alaska Energy Data Gateway.
349 Alex DeMarban. “Native Wildcatters push ahead with exploration at oil and gas projects.” Alaska Dispatch News. November
17, 2016. https://www.adn.com/business-economy/energy/2016/11/17/native-wildcatters-pushing-ahead-with-exploration-at-
oil-and-gas-prospects/
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 177
AEA commissioned a study by the U.S. Army Corps of Engineers (USACE) to investigate potential
improvements to infrastructure for fuel delivery, including solutions such as the establishment of regional
fuel depots. The study concluded that enough cost savings potential exists in the construction and
operation of new regional fuel depots along the Yukon and Kuskokwim Rivers to warrant further analysis,
and that most other regional storage options are not cost-effective.
The creation of two new regional fuel depots and a new fuel facility at the Dalton Highway bridge over
the Yukon River, as well as increased capacity in Aniak (on the Kuskokwim River), were found to m erit
additional analysis. Including the approximately $4 million capital cost to construct a new fuel depot, the
USACE estimated an average annual net benefit of approximately $200,000 could be accrued by using a
new fuel depot constructed at the Dalton Highway bridge. The estimated average annual net benefits
from the increased capacity in Aniak is approximately $540,000/year for an initial capital cost of nearly
$5.6 million. The main benefits of the Aniak depot would be realized by a barge being able to travel upriver
from Aniak more fully laden to serve communities upriver on the Kuskokwim during the high-water time
prior to the lower reaches of the Kuskokwim being open.350
Approximately a dozen other communities had a combination of local moorings and i ncreased tankage
that showed the possibility of having cost-effective benefits. While the analysis on increased tankage is
suspect due to the methodology and data used, it does identify some communities that could merit
further investigation to determine if increased tankage could be beneficial. The recommended moorings,
a continuation of work the USACE performed for the Denali Commission351, showed annual net benefits
that were generally less than 1% of the estimated cost of delivered fuel.352
The community-specific recommendations are accessible through the Alaska Energy Data Inventory
[http://www.akenergyinventory.org/].
FUEL COOPERATIVES
In 2012, the Alaska Village Electric Cooperative (AVEC) entered into the fuel delivery business to supply
its communities with fuel. AVEC reports that it has saved its communities approximately $1 million by
operating its own barge service in 2012353 and $500,000 in 2014.354 These values would translate in a $0.10
to $0.20 per gallon decrease in delivered costs to communities. As there are numerous factors that lead
to delivered cost of fuel in communities, it is difficult to verify reported cost reductions.
The experiences and research of others indicate that it may be difficult to replicate AVEC’s reported
successes. The Norton Sound Economic Development Corporation (NSEDC) has had success with the
Consolidated Bulk Fuel program, where NSEDC has assisted communities and shouldered some of the risk
350 US Corps of Engineers, Alaska District. “Fuel Transportation Improvement Report.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AEAfueltransportationreport101416.pdf
351 US Corps of Engineers, Alaska District. “Alaska Barge Landing System Design Statewide Phase 1, Various Locations Final
Report.” January 2009.
http://www.poa.usace.army.mil/Portals/34/docs/civilworks/archive/alaskabargelandingsystemdesignstatewidephase1.pdf
352 US Corps of Engineers, Alaska District. 2016.
353 Laurel Andrews. “New fuel barges deliver energy savings to rural Alaska.” Alaska Dispatch News. 5/6/2013.
https://www.adn.com/rural-alaska/article/new-barges-brought-energy-savings-rural-alaska-electric-co-op-says/2013/05/07/
354 http://avec.org/wp-content/uploads/2016/03/2014-Annual-Report.pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 178
of bulk fuel transactions.355 Results from other co-ops have been less clear-cut.356, 357 Others have noted
the difficulties that come from trying to coordinate purchases within a community. Additional challenges
exist where business models and/or financial strengths vary too significantly among communities
considering shared fuel purchasing via a co-op. 358
Fuel co-ops and coordinating purchases within a community could in theory reduce the cost of fuel
through several mechanisms. First, it is possible that larger purchases could allow for a better price at the
wholesale level through a volume discount. Researchers have noted that this would require the existence
of undue profits, which a 2010 attorney general investigation did not find at the distribution level.359
Second, there is research indicating discounts to some communities in co-ops would result in a zero-sum
game from a statewide perspective, in which costs are shifted to communities outside the co-op.360
Third, the most likely way in which a co-op would reduce costs in a community is by maximizing the
efficiency of delivering the fuel to a community. By limiting the number of trips to a community and the
fixed costs of preparing to offload fuel, operational savings could be realized. This conclusion parallels the
method chosen by USACE for evaluating benefits of different options for increasing the efficiency of
transporting fuel.
CONSUMER ELECTRICITY COST
The State mechanism to directly reduce the cost of electricity for residential consumer is the Power Cost
Equalization program (PCE).
Since PCE only covers a portion of the electricity sold in communities (between 8% and 70% depending
on the community361), the program could further reduce costs through extending the subsidy to other
customers and/or the rest of electricity sold in the communities. Extrapolating from the 2014
reimbursement rates in communities, extending PCE to cover all sales would cost an additional $82 million
per year. Since there is insufficient revenue from the PCE Endowment to cover this additional subsidy, the
funds would either drain the endowment or need to be found elsewhere.
Approximately 30 communities within the AkAES study area are excluded from receiving PCE
reimbursement. Extending PCE to currently excluded communities, primarily the Copper Valley Electric
Association service area, would cost an additional $7 million per year.
355 http://www.nsedc.com/programs/community-benefits/consolidated-bulk-fuel/
356 Steve Colt, Ginny Fay, Matt Berman, Sohrab Pathan. “Energy Policy Recommendations Draft Final Report.” January 25, 2013.
http://www.iser.uaa.alaska.edu/Publications/2013_01_25-EnergyPolicyRecommendations.pdf
357 Rural Energy Action Council. “Rural Energy Action Council. Findings and Action Recommendations for Governor Frank
Murkowski.” April 15, 2005. http://www.arlis.org/docs/vol1/60412439.pdf
358 Dave Pelunis-Messier, personal communication, January 2016.
359 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
360 Colt et al, 2013.
361 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 179
CONSUMER ELECTRIC RATE—FUEL COSTS
Only a few ways exist to potentially reduce fuel costs for generating electricity: 1) generate and distribute
power more efficiently; 2) interconnect communities to develop a greater economy of scale; or 3) switch
to a renewable source. The option of switching to an alternate fuel, such as LNG or propane, was
addressed in the previous section and was not found to be a cost effective option for any communities.
1. Historically, the State has improved generation efficiency in communities by building a new
powerhouse. In most of the communities in the AkAES study area, a diesel powerhouse is basic
infrastructure, just as the airport and roads are basic infrastructure. While this section focuses on the
cost-effectiveness of replacing a powerhouse for the efficiency that could be gained, efficiency is
rarely the driving force behind upgrading the powerhouse. Rather, maintaining the safety, stability,
and reliability of the community’s energy system will determine when a powerhouse needs to be
upgraded or replaced.
The AAEM uses the average efficiency gains found in the RPSU program (approximately 10%) and a
cost model to estimate the cost of a new powerhouse based on the expected load in each community.
The AAEM combines these factors and the community-specific forecasts to evaluate the economic
feasibility of replacing the powerhouse based on a 30-year expected life.
Based on the assumptions made by the Alaska Affordable Energy Model for this analysis , improving
generation efficiency through a powerhouse replacement was cost-effective in only one community.
Other ways to increase generation efficiency include replacing individual generators instead of the
entire powerhouse.362
Table 21: Savings from increasing generation efficiency in PCE-eligible communities363
AEA energy region
Annual fuel cost
savings
(2017 estimate)
Gallons of diesel
saved per year
Lower Yukon-Kuskokwim $1,908,000 827,000
Yukon-Koyukuk/Upper Tanana $583,000 248,000
Bristol Bay $581,000 225,000
Northwest Arctic $444,000 194,000
Copper River/Chugach $255,000 158,000
Bering Straits $226,000 116,000
Southeast $176,000 107,000
Aleutians $224,000 103,000
North Slope $240,000 96,000
Kodiak $19,000 10,000
Total of AkAES study area $4,661,000 2,085,000
362 “Diesel Efficiency” “Alaska Rural Energy Plan.” 2004
363 AEA analysis of PCE data. Note: due to the rounding, the total may sum properly
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 180
Table 21 estimates the diesel savings potential by region based on PCE data from 2013. The savings
estimated in Table 21 assume that communities larger than 500 people can achieve a diesel efficiency
of 15.5 kwh/gallon and communities smaller than 500 can achieve 14 kWh/gallon. These efficiencies
are technically possible but likely challenging, since only a few communities in these size ranges are
able to maintain this level of efficiency.
Federal emissions standards are making it more difficult to find operational savings with newer diesel
generation units. Replacing older generators with newer, higher-efficiency units that are compliant
with EPA Tier 4 emission standards could actually increase operational costs. In many cases, the newer
models are more complex, and the added complexity of newer units can increase the amount and
cost of maintenance, particularly if the local operator does not have requisite skills to maintain the
gensets.364
System efficiency can also be improved by reducing losses that occur when distributing electricity,
what is generally referred to as line loss. Line loss, calculated as the difference between the kWhs
generated and those sold, can be caused by myriad reasons, such as improperly sized or faulty
transformers, unseen grounds, malfunctioning meters, and uncharged customers. Because of all these
possible sources of loss, there is no reliable way to determine the costs of reducing line losses.365 The
potential benefits are sizeable in some communities.
Table 22: Potential savings from reducing line loss to 10% in PCE-eligible utilities366
AEA energy region
Annual fuel cost
savings
(2017 estimate)
Gallons of diesel
saved per year
Lower Yukon-Kuskokwim $644,000 329,000
Yukon-Koyukuk/Upper Tanana $404,000 171,000
Aleutians $321,000 124,000
Southeast $210,000 133,000
North Slope $189,000 88,000
Northwest Arctic $161,000 46,000
Copper River/Chugach $124,000 75,000
Bristol Bay $91,000 34,000
Bering Straits $3,000 1,000
Railbelt $2,000 1,000
Kodiak $0 -
Total of AkAES study area $2,151,000 1,004,000
Lower Yukon-Kuskokwim appears to have the largest opportunity for reducing energy costs through
improving line losses. As mentioned before, there is not a clear way to evaluate the costs, along with
these benefits, to be able to compare these estimated benefits with the other opportunities within
364 Kris Noonan, personal communication, December 2016.
365 Kris Noonan, personal communication, December 2015.
366 AEA analysis of 2013 PCE data, Note: due to the rounding, the total may sum properly
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 181
this chapter. Generally, distribution upgrades are relatively minor costs, and it is likely that the line
loss reductions will more than pay for the capital costs.
Line losses also have a direct impact on the amount of PCE that communities receive. Since the
amount of PCE reimbursement is based on a maximum line loss of 12%, PCE reimbursement is lower
than would be expected in communities that exceed this cap.
2. Interties are low voltage transmission lines between communities. Interties have been proposed by a
number of studies as a potential way of reducing energy costs in communities. The most likely savings
from an intertie would come from the avoided capital expenditure associated with the replacement
of a powerhouse. Operational benefits from interconnections could come from lower operational
costs if a power house was eliminated in the process of connecting, greater efficiency and/or
incorporation of renewables by being able through economy of scale or lower operational and
management costs by combining utilities. Physically larger utilities are not necessarily more cost-
efficient or more efficient than smaller utilities, and most of these economic benefits could be gained
without interties through close coordination between communities. Larger utilities were shown to be
more cost-efficient administratively, but this economy of scale does not require physical
interconnections.367
Based on work performed by ACEP for the AkAES project, the AAEM uses per-mile cost assumptions
of $500,000/mile off of the road system and $200,000/mile on the road system for the construction
of new transmission lines.368 As a best-case scenario assumption, to estimate costs of new
transmission lines in the AkAES study area, a straight-line distance between communities was used.
For comparison, the model was run against the nearest community with lower priced power or the
regional hub. The costs and benefits are based on an assumed economic life of 30 years.
Regional distribution systems do not appear to be a cost-effective solution for most of rural Alaska
and do not appear to create sufficient economies of scale to merit the investment. Only one project
in Southeast was identified as potentially cost effective. The distances traversed are too large, and
the loads connected and the savings are too small to cost-effectively reduce the cost of energy in
communities. Specific cases may exist that could utilize a low-cost renewable energy or significantly
more efficient generation capacity, but based on current conditions these instances are rare.
Insufficient data was available to test when an intertie could be used to offset the capital cost of a
new powerhouse, but this is likely the situation which would provide the best benefit to communities.
3. Renewable energy reduced and/or stabilized the cost of energy in many Alaska communities. In
particular, hydro, wind, biomass, and solar power have been touted as solutions for energy costs in
367Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
368 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 182
study area communities. In general, however, it can be technically and economically challenging to
integrate renewables into the local grid, particularly in small, isolated communities. While it can be
difficult, there are a number of potential, site-specific renewable energy resources across the state
that could reduce the cost of energy based on today’s technology.
The following does not include analysis of all possible renewable energy resources. In particular, it
does not include geothermal, tidal, in-river, wave, or biomass for electricity. Geothermal is not
included because of the inability to assess a resource without significant, expensive drilling, and no
community resource to date have been found to be economically viable. Tidal, in-river hydrokinetics,
wave energy, and small-scale biomass for electricity are not mature technologies, and there is
insufficient data on which to base the economic analysis of potential projects.
Hydropower can be an especially cost-effective and stable energy source for communities. Although
limited by the seasonality of flow and size of resource, both run-of-river (which does not require a
sizeable dam) and storage-type projects can displace some or all non-renewable electricity generation
in a community.
The data for the evaluation of potential hydro projects comes from more than 400 resource
evaluations compiled by the USACE369 and the REF. Currently, there is no way to effectively model the
cost of hydropower due to the multitude of factors that can skew the cost, although this capacity may
be available in the future.370 Some recently identified projects have not been added to the dataset.371
If there were multiple potential projects in a community or on an intertie, the highest-performing
option was used so that there would not be double counting of the opportunity. The results in Table
23 are based on an assumed 50-year economic life.
As can be seen in Table 23, many of the potential projects are in regions, particularly Southeast, where
hydropower already supplies the majority of electricity. The analysis does include some potential
projects that have been deemed infeasible for non-economic reasons. For example, one of the two
projects in the Lower Yukon-Kuskokwim region was the Chikuminuk Lake Hydroelectric project, which
the region was not able to pursue because the resource is in protected lands and permitting was not
probable. Copper River/Chugach region will likely have less need for power with the Allison Creek
hydroelectric project now online.372 It is possible that, once data is available from the project, one of
the projects within that region will no longer be viable.
369 US Army Corps of Engineers, Alaska District. “Alaska Hydropower Evaluation.” May 2014.
370 Alex DeMarban. “Department of Energy eyes hydropower to help Alaska.” Alaska Dispatch News. October 16, 2016.
http://www.adn.com/business-economy/energy/2016/10/16/department-of-energy-eyes-hydropower-to-help-alaska/
371 Elizabeth Jenkins, “Is hydropower renewable? One village in SE Alaska needs it to be.” January 6, 2017. KTOO public media.
http://www.ktoo.org/2017/01/06/hydropower-renewable-energy-one-village-se-alaska-needs/
372 Alex DeMarban. “Valdez hydropower project makes utility all-renewable in the summer.” Alaska Dispatch News. October 14,
2016. http://www.adn.com/business-economy/energy/2016/10/14/valdez-hydropower-project-makes-utility-all-renewable-in-
summer/
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 183
Table 23: Hydropower opportunity373
AEA energy region
Projects
analyzed
in region
Number of
cost-
effective
projects
identified
Investment
needed for
cost-
effective
projects
Net benefit
of cost-
effective
projects
Gallons of
diesel
offset per
year
Aleutians 36 13 $99,935,000 $111,653,000 1,756,000
Lower Yukon-
Kuskokwim 7 1 $224,462,000 $79,940,000 3,181,000
Southeast 182 4 $22,205,000 $42,877,000 446,000
Copper River/Chugach 48 7 $241,595,000 $30,293,000 3,622,000
Bristol Bay 29 2 $44,868,000 $13,414,000 872,000
Northwest Arctic 8 3 $35,167,000 $2,591,000 360,000
Yukon-
Koyukuk/Upper
Tanana
37 1 $15,610,000 $1,123,000 260,000
Bering Straits 16 0 $0 $0 -
Kodiak 34 0 $0 $0 -
Total of AkAES study
area 397 31 $683,847,000 $281,893,000 10,499,000
Wind power uses turbines to extract energy from the wind. Using current technologies, wind power
acts as a supplementary source of electricity with another source, such as diesel generators, which
provide the majority of power, forming and stabilizing the grid.
The resources evaluated by the AAEM came from multiple sources—the NREL wind map374, data from
anemometers375, REF projects, and AEA project manager input. Unless specific analysis had been done
on a specific system, the assumed project capacity factors for each wind class—the primary means of
estimating power production—borrows from the REF evaluation method.
For non-REF projects, the modeled wind nameplate capacity was based on 150% of the average
community load, with a minimum average load of 100 kW. It is assumed that 20% of the electricity is
diverted to a secondary load to heat a community facility.376 The estimate for the capital cost was
developed by ACEP through work commissioned for the AkAES based on installed projects in Alaska.377
Insufficient data was available to differentiate the cost estimates by region. The costs and benefits
presented in Table 24 are based on an assumed 20-year economic life.
373 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
374 http://www.akenergyinventory.org/data
375 http://www.akenergyauthority.org/Programs/AEEE/Wind
376 Josh Craft, personal communication
377 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 184
Table 24: Wind power opportunity378
AEA energy region
Projects
analyzed in
region
Number of
identified
cost-
effective
projects
Investment
needed for
cost-effective
projects
Net benefit
of cost-
effective
projects
Gallons
of diesel
offset
per year
Lower Yukon-
Kuskokwim 53 4 $64,695,000 $39,360,000 2,137,000
Bristol Bay 31 3 $36,594,000 $10,393,000 1,364,000
Aleutians 16 2 $31,950,000 $8,661,000 1,206,000
Copper River/Chugach 8 1 $18,307,000 $8,057,000 607,000
Bering Straits 20 1 $11,292,000 $1,872,000 454,000
North Slope 12 3 $8,369,000 $7,659,000 253,000
Kodiak Region 8 0 $0 $0 -
Northwest Arctic 12 0 $0 $0 -
Southeast 23 0 $0 $0 -
Yukon-Koyukuk/Upper
Tanana 42 0 $0 $0 -
Grand Total 225 14 $171,209,000 $76,003,000 6,024,000
Given the site-specific nature of the wind resource, it is not surprising that many communities would
not have an economically viable project. Another challenge for wind projects is that small projects
cost significantly more per installed nameplate capacity than larger projects. For instance, a 2-MW
(megawatt) wind project is estimated to cost one-quarter of the amount per installed capacity of a
100-kW project.
Solar power uses photovoltaic (PV) panels to convert light into electricity. Like wind, using current
technologies, solar power acts as a supplementary source of electricity with another source, such as
diesel generators, which provide the majority of power to form and stabilize the grid.
The resource estimate for each reference community was pulled from NREL’s PVWatts web
application379, and AEA used a distance formula to find the nearest reference community for each
AkAES community. Based on work performed by ACEP, commissioned for the AkAES, a price of
$6,000/kW was chosen. Based on the data collected by ACEP, solar power in Alaska has had an
installed cost between $6,000/kW- $11,000/kW.380 The costs and benefits in Table 25 are based on
the 20-year economic life of the projects and should be considered a best-case scenario.
378 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
379 National Renewable Energy Laboratory. PVWatts Calculator. http://pvwatts.nrel.gov/
380 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 185
Table 25: Solar PV opportunity381
AEA energy region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-
effective
projects
Net
benefit of
cost-
effective
projects
Diesel
Offset
Bristol Bay 22 1 $71,000 $36,000 1,100
Yukon-Koyukuk/Upper
Tanana 40 1 $56,000 $100 700
Aleutians 12 0 $0 $0 -
Bering Straits 16 0 $0 $0 -
Copper River/Chugach 8 0 $0 $0 -
Kodiak Region 8 0 $0 $0 -
Lower Yukon-
Kuskokwim
39 0 $0 $0 -
North Slope 8 0 $0 $0 -
Northwest Arctic 10 0 $0 $0 -
Southeast 23 0 $0 $0 -
Total of AkAES study
area 160 2 $127,000 $36,100 1,800
Solar does not currently appear to be an economically viable resource for utility-scale projects in
Alaska. While the prices for solar panels have dropped significantly over the past decade, it is unknown
if those hard costs will continue to drop and if the other “soft” costs, which constitute the majority of
costs for Alaska projects382, can be reduced sufficiently in the future to make utility-scale solar power
economically viable.
This analysis only includes utility-scale solar projects and does not address building-scale projects. In
some communities, it would be possible for a building-scale project to be less expensive than the retail
rate for electricity. Utility-wide financial and technical difficulties can be caused by too much
distributed generation so these building level projects can cause problems that increase costs if not
managed properly.
CONSUMER ELECTRIC RATE—NON-FUEL COSTS
While controlling non-fuel costs has potential to offer energy cost savings, it is not as certain of reducing
fuel costs. Infrastructure projects can be modeled relatively easily with physical and economic constraints;
utility non-fuel costs are not as easily investigated. While most of Chapter 6 has tried to be as quantitative
and data-driven as possible, this section is more qualitative and speculative due to insufficient data.
381 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
382 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 186
The six potential opportunities to reduce the rates that consumers pay for electricity, by reducing utility
non-fuel costs include: 1) direct capital grants, 2) utility consolidation, 3) reducing bad debt, 4) reducing
non-productive investments, 5) access to more training, and 6) operational and managerial efficiencies.
1. Direct capital grants—Most current and historical State energy programs (RPSU, BFU, REF, etc.) have
focused on direct capital grants to reduce costs in communities. Anecdotally, capital grants based on
the disrepair of the infrastructure instead of the financial need of the entity can create disincentives
to properly maintain facilities.383 There was insufficient data to test this hypothesis quantitatively.
2. Consolidation of utilities to increase the scale of operations—Since it was indicated above that
interties were not likely to be cost-effective, except in cases where it would avoid the replacement of
a powerhouse, the most realistic means of consolidating utilities in the AkAES region is through larger
regional utilities—either investor-owned utilities (IOUs) or cooperatives. As seen in Chapter 3, larger
utilities exhibited reduced non-generation costs.
Figure 99 shows the amount of electricity produced at different cost points. The text provides the per
kWh cost savings associated with joining a large regional co-op, e.g. AVEC or large regional IOU.
Figure 99: Non-generation costs per kWh by cost bin and organization type384
383 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
384 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
0 30,000,000 60,000,000 90,000,000 120,000,000
$0.00
$0.05
$0.10
$0.15
$0.20
$0.25
$0.30
$0.35
$0.40
Cumulative kWh per year by cost bin ($/kWh) and organization type
Non-generation costs per kWh by cost bin and organization type
Source: Adapted from MAFA (2016)
Village Regional Coop
AVEC
IPEC
High cost of service utilities; ~28c/kWh vs potential cost reduction to 7c/kWh or
below if combined with Large Regional Co-op with dozens of small villages
High cost of service utilities; ~24c/kWh vs potential cost reduction to 7c/kWh or
below if combined with Large Regional Co-op with dozens of small villages
High cost of service utilities; ~16-21c/kWh vs potential cost reduction to 7c/kWh or
below if combined with Large Regional Co-op with dozens of small villages
Medium cost of service utilities; ~9-13c/kWh vs potential cost reduction to 7c/kWh
or below if combined with Large Regional Coop with dozens of small villages
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 187
Figure 99 indicates a potential savings of approximately $15 million per year across PCE
communities.385
A number of communities have either joined or have expressed interest in joining larger utilities.386
While savings may be available, not all communities will be in favor of losing control of their utility,
especially if they have goals that are not directly about saving money. The example of Yakutat is
particularly instructive. Although the incorporation of Yakutat’s utility into AVEC would likely benefit
Yakutat financially, the RCA received a petition with 277 names opposing the sale of the utility.387
The Alaska Rural Utility Collaborative (ARUC), a water and wastewater collaborative, provides
assistance to 28 communities in Alaska to provide a greater economy of scale. Developed in 2004 by
Alaska Native Tribal Health Consortium (ANTHC), ARUC has shown that a regional entity can
successfully improve the operations and management of small, rural utilities and confer benefits to
communities and the State. ARUC management assistance improved collection rates in member
communities from 73% to 96-98%. By improving pay and benefits, operator turnover was reduced
from over 50% to 7%.388 The cost of energy in ARUC communities dropped by 27% from FY12 to FY14
through improved operations, efficiency, and renewable energy projects. The life of infrastructure
built through State and federal grants are expected to last longer than in non-participating
communities.389 These benefits are gained through less direct control than electric cooperative.390 In
2014, $1.1 million in federal and ANTHC grants helped to fund the financial, managerial, and technical
assistance.391
In Chapter 5, it was shown that standalone village and city utilities were significantly more likely to
need assistance from AEA’s Electrical Emergency Assistance programs. Larger consolidated utilities
have greater capacity to respond to emergencies without State assistance and/or ensure that
emergencies do not happen.
Additionally, it is assumed that larger consolidated utilities are more capable of accessing non-State
financing opportunities. Consolidation can also offer greater access to technical capacity and lead to
greater generation efficiency and longer effective life of infrastructure and/or other similar benefits.
3. Reduce the amount of bad debt—Anecdotally, it has been noted that many utilities have difficulties
in collecting customer payments, and this leads to significant bad debt. An analysis of the PCE filings
to the RCA for almost 80 utilities did not find any systemic problem with bad debt. Across all
385 Foster and Townsend, 2017.
386 James Brooks. “Yakutat sells its power company to statewide cooperative.” Juneau Empire. October 24, 2016.
http://m.juneauempire.com/state/2016-10-24/yakutat-sells-its-power-company-statewide-cooperative#gsc.tab=0
387 James Brooks. “Yakutat power sale draws ample opposition.” Juneau Empire. November 18, 2016.
http://juneauempire.com/state/2016-11-18/yakutat-power-sale-draws-ample-opposition
388 John Nichols, personal communication, February 18, 2015.
389 Alaska Rural Utility Collaborative. “2014 Report on Activities.” https://anthc.org/wp-content/uploads/2015/12/2014-ARUC-
Report-on-Activities-v2_02.09.15_email.pdf
390 John Nichols, personal communication, February 18, 2015.
391 ARUC 2014
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 188
communities, the savings from reducing bad debt appears to be minimal–at maximum a few hundred
thousand dollars across the study area–but it could be important for specific utilities.
It is possible that some utilities do not report debt that has been written off or that it is more an issue
of cash flow with payments being sporadic. It is not known what issues are created by sporadic cash
flow, but at a minimum, it would require careful planning and an adequate cash reserve to ensure
that a sufficient cushion is available to deal with commonly recurring operating payments.
4. Reduce non- or under-productive investments—Although utilities and their ratepayers in the AkAES
study area do not generally bear the cost of non-productive investments, as most large capital
investments have been made through State and federal programs, all non- and under-productive
investments have an opportunity cost in terms of time and money spent.
It is difficult to quantify the opportunity cost of non-productive infrastructure investments, but
Chapter 4 showed that many risks and barriers existed that could lead to non - or under-productive
investments.
There are only a limited number of cases in which communities or utilities have had to pay for risky
projects. However, in at least one case, this led to the bankruptcy of the utility.392
5. Training and longevity—Given the importance of having competent operators, training is vital for
effective utility operations.393 Improved operations and maintenance (O&M) will increase the usable
life and performance of infrastructure. Adequate training is one of the factors that can improve O&M.
6. Operational and managerial efficiencies—Across the nation, it is common for rural and small utilities
to have operational and managerial challenges.394 Operating under the assumption that nearly all
entities can be run more efficiently, a generic 5% reduction in the non-fuel costs was modeled against
the communities that receive PCE. A reduction of this magnitude could return a total savings of over
$5.3 million, with approximately $3.7 million going to consumers and $1.7 million saved in reduced
PCE expenditure.
Another way to address the operational and managerial costs would be to develop a maximum
allowable non-generation cost. Figure 100 presents the range of non-generation operating costs.
392 Wesley Loy. “Electric co-op seeks bankruptcy after well cost overruns.” Alaska Dispatch News. October 16, 2010.
https://www.adn.com/alaska-news/article/electric-co-op-seeks-bankruptcy-after-well-cost-overruns/2010/10/17/
393 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
394 USDA & EPA. “Rural and Small System Guidebook to Sustainable Utility Management.” 2016.
https://www.epa.gov/sustainable-water-infrastructure/rural-and-small-systems-guidebook-sustainable-utility-management
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 189
Figure 100: Range of non-generation operating costs by organization type395
Figure 100 includes all non-fuel costs that are not related to generation, essentially the overhead
costs. A case could be made that the range of acceptable values could be somewhere within the boxed
area. Further study would be needed to justify the exact boundaries , but this line of inquiry could
provide a method for determining a reasonable cap on these types of expenses.
Ironically, improving utility management, particularly the reporting of expenses, could have the
unintended side effect of increasing the reporting of non-fuel costs for some communities. Since it is
difficult to know which utilities underreport their expenses, the increase is unknown.
CONSUMER ELECTRICITY CONSUMPTION
Reducing electricity consumption through efficiency and conservation can be, because of the distributed
nature of the opportunity, more challenging than improving generation infrastructure. That being said,
demand-side reductions have been successful in reducing consumer costs in Alaska.396 The 2012
Southeast Integrated Resource Plan (SEIRP) identified energy efficiency and demand-side management as
395 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
396 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
0
50,000,000
100,000,000
150,000,000
200,000,000
250,000,000
$0.05 $0.10 $0.15 $0.20 $0.25 $0.30 $0.35Cumulative kWh by cost binNon-generation utility cost ($/kWh) by organization type
Source: Foster analysis of RCA data
Local IOU
Village
City / Borough
Local co-op
Regional IOU
Regional co-op
Most utilities are
in this range
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 190
top priorities for the region397, and energy efficiency has been identified as the least-cost solution for most
rural Alaska communities.398
1. Residential efficiency—Even without any direct intervention by the State, Alaska’s residential
electricity consumption is currently declining. Many utilities in the state have seen reductions in
consumption per residential customer. Since there have not been any State requirements or programs
that have targeted residential electricity consumption and the reduction has been maintained
through the recent drop in oil prices, the most likely reason for this reduction is the greater saturation
of energy efficient products—LED and CFL lighting, refrigerators, etc.—resulting from federal
regulations and technology development.
There have been limited programs in Alaska that have targeted electricity consumption. Because
heating a residence is generally much more expensive than the electricity, and the PCE program
lowers electricity costs for rural residents, focusing on electric energy efficiency and conservation
savings has not been a high priority. The examples, including RurAL CAP’s Energy Wise, Golden Valley
Electric Association’s Hom$ense program399, and Sitka’s Energy Star program did not yield sufficient
data to adequately model the opportunity in the AkAES study area, although they appear to be
successful at reducing electric and heating costs.400, 401
Vermont Energy Investment Corporation’s (VEIC) “Energy Efficiency Program Evaluation and
Financing Needs Assessment” investigated Alaska’s energy efficiency programs, primarily those
focused on reducing thermal loads. The report provided some guidance on ways to reduce electricity
consumption as well. Many states have requirements for their utilities to reduce consumption, an
Energy Efficiency Resource Standard (EERS), for instance, and significant research has been done to
evaluate the different methods of mandating energy consumption reduction. Another example
provided by VEIC include requirements for consumer product efficiency, such as requiring Energy Star
compliant products and/or providing incentives at the retail or distributor level to lower the additional
cost of the energy efficient choice.402 Residential building energy codes, covered later in this chapter,
are another method to reduce electricity consumption in residential buildings.
Non-residential—Non-residential buildings in the AkAES study area come in many shapes and sizes
and have a variety of uses. Of the approximately 10,000 non-residential buildings in the study area,
397 Black & Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
http://www.akenergyauthority.org/Content/Publications/SEIRP/SEIRP-Vol1-ExecSumm.pdf
398 Riley Allen, Donna Brutkoski, David Farnsworth, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.’ December
2015. https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
399 http://www.gvea.com/resources/energysense
400 Brian Saylor & Associates. “Energy Impacts of the RurAL CAP Energy Wise Program from Program Years 2009-201 and 2011-
2012.”
401 Juliet Agne. “Energy Star Rebate Program: Final Report”. 5/20/2013.
http://www.cityofsitka.com/government/departments/electric/documents/EnergyStarRebateProgramFinalReportwithAppendi
ces.pdf
402 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 191
AEA was able to find some information (the use, size, and/or energy consumption) for about 60% of
them. Without energy consumption data for a higher percentage of buildings, there is uncertainty for
the costs and benefits estimated in this section. When values for buildings were not available, AEA
used known averages for the building size and the heating oil and electricity consumption per square
foot (adjusted for climate).
Audits performed through state and federal programs have shown an average of 26% in cost-effective
energy savings for heat and electricity at an average cost of approximately $7 per square foot.403
In addition to the modeling based on these audits, VEIC also recommended the same suite of
programs (minimum product requirements, building energy codes, and incentive programs) as
referenced in the residential section previously. The results included in Table 26 are based on a 15-
year economic life.
Table 26: Non-residential efficiency opportunity404
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-
effective
projects
Net benefit
of cost-
effective
projects
Gallons of
heating oil
displaced
yearly
kWh
saved
yearly
Copper
River/Chugach 23 21 $42,977,000 $79,682,000 1,557,000 37,250,000
Bristol Bay 30 19 $36,034,000 $67,597,000 991,000 17,041,000
Lower Yukon-
Kuskokwim 53 27 $82,329,000 $59,492,000 2,079,000 21,645,000
Kodiak Region 12 6 $47,136,000 $43,102,000 1,205,000 48,340,000
Southeast 43 25 $112,538,000 $42,719,000 2,728,000 98,949,000
Aleutians 12 8 $28,509,000 $39,542,000 644,000 12,724,000
Yukon-
Koyukuk/Upper
Tanana
55 26 $17,537,000 $12,355,000 502,000 4,043,000
Northwest Arctic 12 11 $22,888,000 $10,325,000 718,000 5,763,000
Bering Straits 16 8 $22,552,000 $8,785,000 659,000 7,292,000
North Slope 8 0 $0 $0 - -
Total AkAES
study area 264 151 $412,503,000 $363,602,000 11,087,000 253,051,000
Non-residential efficiency appears to be cost-effective in the majority of communities in the AkAES
region. It would be difficult to capture all of the opportunity for non -residential efficiency, but it is
clear there is the potential for significant reduction. Within each community there are likely cost-
effective projects for individual buildings. The borough-wide energy subsidies in the North Slope are
responsible for non-residential energy efficiency not being cost-effective.
403 Richard Armstrong. “White Paper on Energy Use in Alaska’s Public Facilities.” For AHFC. October 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
404 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 192
Aside from new infrastructure, the 2012 “White Paper on Energy Use in Alaska’s Public Facilities”
identified that decisions on design, conservation, and operations dramatically affected energy use and
costs in non-residential buildings.405
CONSUMER HEATING FUEL COST
Heating fuel costs are the primary energy expense for both residential and non-residential consumers.
LIHEAP/AKHAP directly addresses the idea of affordability for residential customers as an income-based,
direct consumer subsidy program. As seen in Chapter 5, federal funding has been between $21 and $40
million and State funding from $1.4 to $5.7 million per year since AKHAP was instituted in 2009. A 2013
ISER study did not recommend any changes to the AKHAP program, particularly citing the dilution of
benefits to the lowest income households if the income cap was raised.406
In the same 2013 report, ISER analyzed a potential “PCE-like” program for heating fuel. Using a limit of
500 gallons for the 62,000 eligible households and a $2/gallon reimbursement level, ISER estimated the
program would cost $62 million per year.407
Other options, such as a system that follows more closely the logic of PCE, where the base rate is
determined as a weighted average cost of Alaska’s largest cities, would have even higher costs. Extending
this logic to try to equalize the residential heating fuel rates equivalent to those in Anchorage on unit-of-
energy cost basis would require a subsidy of more than $150 million per year, which is four times more
than the current PCE program.
CONSUMER HEATING FUEL RATE
The earlier section outlining the cross-cutting opportunities for electricity and heating cost reduction are
also applicable to this section. LNG and propane are unlikely to be economically viable for the AkAES study
area and there might be regional fuel depots on the Upper Kuskokwim and at the Dalton Highway bridge
over the Yukon that could provide benefits to some communities.
1. Infrastructure capital subsidies—The State and federal government have contributed significantly to
subsidizing the cost of diesel and heating oil in communities through the Bulk Fuel Upgrade (BFU)
program. A number of communities have been identified as needing to upgrade deteriorating
facilities. The estimated average annual capital expenditures to replace bulk fuel facilities as they
reach the end of their useful life is $17 million. The BFU has reduced retail cost by approximately
$0.50/gallon by removing the need to repay the capital costs of the storage facilities.
2. In addition to heating oil, LNG, and propane, there are other heat sources. What follows are the
analyses of the potential of biomass cordwood, biomass pellets, and air-source heat pumps (ASHP)
for heat in residential and non-residential buildings.
405 Richard Armstrong. “White Paper on Energy Use in Alaska’s Public Facilities.” For AHFC. October 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
406 Steve Colt, Ginny Fay, Matt Berman, Sohrab Pathan. “Energy Policy Recommendations Draft Final Report.” January 25, 2013.
http://www.iser.uaa.alaska.edu/Publications/2013_01_25-EnergyPolicyRecommendations.pdf
407 Colt et al, 2013
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 193
Biomass, cordwood–Only non-residential buildings were accounted for in this analysis, as it is
assumed that residential consumers would have converted to wood heat given the long -standing
tradition of using firewood (the more commonly used term for cordwood) for heat in Alaska. A 2010
survey by the U.S. Forest Service found that a market price between $4.00 and $5.00 was needed for
respondents to choose to convert to wood heating, a price point that was reached in much of the
study area over the past decade.408
The cordwood potential for each community was estimated by analyzing the GIS data available
through the Alaska Energy Data Inventory and assumed that 1% of the biomass available in a 5-mile
radius could be harvested each year. The costs and benefits of cordwood use a conversion of 30% of
the non-residential square footage to biomass heat. The results in Table 27 are over the expected 20-
year economic life of the projects.
Table 27: Biomass (cordwood) opportunity409
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for cost-
effective
projects
Net benefit of
cost-effective
projects
Yearly heating
oil displaced of
cost-effective
projects
Yukon-
Koyukuk/Upper
Tanana
50 19 $12,439,000 $5,427,000 417,000
Kodiak Region 11 4 $13,860,000 $3,955,000 564,000
Northwest Arctic 11 4 $2,843,000 $2,337,000 108,000
Bering Straits 16 2 $1,777,000 $1,034,000 62,000
Southeast 40 2 $533,000 $311,000 22,000
Lower Yukon-
Kuskokwim 47 2 $710,000 $62,000 20,000
Copper
River/Chugach 21 1 $177,000 $37,000 9,000
Aleutians 12 0 $0 $0 -
Bristol Bay 27 0 $0 $0 -
North Slope 8 0 $0 $0 -
Total of AkAES
study area 243 34 $32,341,000 $13,165,000 1,204,000
Based on the assumptions of the model, more than 1.2 million gallons of heating oil could be displaced
by cordwood annually in the AkAES study area, with more than two-thirds of this potential in the
Southeast region. The opportunity is centered in Southeast because of the greater availability of
biomass and the larger regional population.
Biomass, pellets–The method for evaluating the opportunity for biomass pellets was nearly the same
as for cordwood, except that the availability of pellets was determined by access to roads or the State
408 David Nicholls, Allen Brackley, and Valerie Barber. “Wood Energy for Residential Heating in Alaska: Current Conditions,
Attitudes, and Expected Use.” July 2010. https://www.fs.fed.us/pnw/pubs/pnw_gtr826.pdf
409 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 194
ferry to allow for consistent delivery of pellets to the communities. The costs and benefits included in
Table 28 are over the expected 20-year economic life of the projects.
Table 28: Biomass (pellet) opportunity410
AEA energy region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-
effective
projects
Net benefit of
cost-effective
projects
Yearly
heating oil
displaced
by cost-
effective
projects
Yukon-Koyukuk/Upper
Tanana 50 11 $3,981,000 $1,972,000 277,000
Copper River/Chugach 21 2 $300,000 $155,000 20,000
Southeast 40 1 $90,000 $3,000 6,000
Aleutians 12 0 $0 $0 -
Bering Straits 16 0 $0 $0 -
Bristol Bay 27 0 $0 $0 -
Kodiak Region 11 0 $0 $0 -
Lower Yukon-Kuskokwim 47 0 $0 $0 -
North Slope 8 0 $0 $0 -
Northwest Arctic 11 0 $0 $0 -
Total of AkAES study
area 243 14 $4,372,000 $2,131,000 304,000
Given the similarity in parameters between the cordwood and pellet modules, it is not surprising that
the results are relatively similar. Once again, the Southeast region is the primary beneficiary of this
potential opportunity, and it was identified as one of the top recommendation in the Southeast
Integrated Resource Plan for reducing electric loads in Southeast communities with high electric heat
penetration.411
Air-source heat pumps—More efficient than other types of thermal energy sources, air-source heat
pumps can deliver up to four units of energy for every unit of electricity consumed. This ratio is
generally referred to as the coefficient of performance (COP). While air-source heat pumps (ASHP)
can be very efficient in delivering heat, their performance and costs are exceptionally sensitive to
climate and electricity price.
The modeling that is used to develop Tables 31 and 32 is based on the fact that the COP and output
of the ASHPs is temperature dependent. The COP and output both drop as the temperature drop.
ASHPs require a backup heat source in most regions: ASHP do not work well below 0 Fahrenheit,
requiring either a biomass or heating oil heating appliance.412 It is assumed that the ASHP is replacing
410 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
411 Black & Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
http://www.akenergyauthority.org/Content/Publications/SEIRP/SEIRP-Vol1-ExecSumm.pdf
412 Vanessa Stevens, Colin Craven, Robbin Garber-Slaght. “Air Source Heat Pumps in Southeast Alaska: A review of the
literature, a market assessment, and preliminary modeling on residential air source heat pumps in Southeast Alaska.” April
2013. http://www.cchrc.org/sites/default/files/docs/ASHP_final_0.pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 195
an existing system, which could remain in place for the coldest times of the year, so this redundancy
is not included as a cost in this analysis.
Although ASHPs can likely be effective in a number of communities, there is a huge obstacle for
implementing them in many communities. As the last column in Table 29 and 30 show, there needs
to be significant excess electricity generation capacity for the ASHPs to be viable. If there is insufficient
excess capacity, there will not be enough power available in the community to run the heat pumps.
Especially since the heating season corresponds with the lowest levels of hydropower availability in
most communities413, there are distinct limitations to the applicability of ASHPs in many regions. The
cost of the increased generation capacity is not included as a cost in Table 29 or 30. In some
circumstances if ASHPs replace existing electric resistance heating, it would free up generation
capacity and potentially avoid or delay capital expenditures to increase capacity.
Non-residential ASHPs: Table 29 assumes that 30% of the non-residential square footage in a
community can be converted to ASHPs. The costs and benefits of the projects are over the 15-year
expected economic life of the projects.
Table 29: Non-residential ASHP opportunity414
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-effective
projects
Net benefit of
cost-effective
projects
Heating
oil
displaced
yearly
Excess
capacity
needed
(kW)
Southeast 40 12 $74,493,000 $66,645,000 4,281,000 7,400
Kodiak Region 11 7 $10,161,000 $18,120,000 684,000 950
Copper
River/Chugach 21 1 $7,608,000 $1,156,000 457,000 800
Aleutians 12 3 $1,930,000 $579,000 111,000 150
Lower Yukon-
Kuskokwim 47 1 $579,000 $281,000 19,000 50
Yukon-
Koyukuk/Upper
Tanana
50 1 $300,000 $17,000 7,000 30
Bering Straits 16 0 $0 $0 - -
Bristol Bay 27 0 $0 $0 - -
North Slope 8 0 $0 $0 - -
Northwest
Arctic 11 0 $0 $0 - -
Total of AkAES
study area 243 25 $95,072,000 $86,801,000 5,562,000 9,000
The results here are very similar to biomass, with most of the benefits seen in the Southeast region
where there are communities with low cost power in a temperate climate . Other areas, with lower-
413 Leila Kheiry, “KPU back on hydro after warm, wet weekend.” KRBD. January 17, 2017.
http://www.krbd.org/2017/01/17/kpu-back-on-hydro-after-warm-wet-weekend/
414 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 196
cost power, including where cost reductions are available through local subsidies, and maritime
climates, also see some significant benefits.
Residential ASHPs assume that all residential buildings are converted to ASHPs using the same logic
and performance parameters as the non-residential ASHPs. The costs and benefits in Table 32 are
over the expected economic life of 15 years.
Table 30: Residential ASHP opportunity415
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-
effective
projects
Net benefit
of cost-
effective
projects
Heating
oil
displaced
yearly
Excess
capacity
needed
(kW)
Southeast 40 7 $414,484,000 $173,736,000 15,204,000 26,000
Kodiak Region 11 7 $43,437,000 $65,715,000 2,491,000 3,400
Aleutians 12 3 $3,114,000 $830,000 173,000 240
Lower Yukon-
Kuskokwim 47 1 $327,000 $134,000 10,000 20
Bering Straits 16 0 $0 $0 - -
Bristol Bay 27 0 $0 $0 - -
Copper
River/Chugach
21 0 $0 $0 - -
North Slope 8 0 $0 $0 - -
Northwest Arctic 11 0 $0 $0 - -
Yukon-
Koyukuk/Upper
Tanana
50 0 $0 $0 - -
Total for AkAES
study area 243 18 $461,364,000 $240,417,000 17,879,000 30,000
As with the non-residential ASHPs, the opportunity is clustered in Southeast, with its low cost
electricity and maritime climate. Although ASHPs may decrease the consumption of heating oil in
communities, it could increase the consumption of diesel to produce the electricity to power the
ASHPs, if the electricity in not generated by a renewable source. Tables 29 and 30 assume that
communities have the excess generation capacity needed to power the ASHPs.
Heat recovery, otherwise known as combined heat and power (CHP), is the concurrent production of
electricity or mechanical power and useful thermal energy from a single source of energy. In diesel
generating systems, approximately 30% of the fuel is transformed into electrical energy and 70% of
the fuel is transformed into heat. Some of the heat energy normally wasted can be recovered and
used directly for space heating, domestic hot water, or for tempering municipal water supplies to
prevent freezing and facilitate treatment.
415 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 197
There are currently more than 90 communities in rural Alaska that use recovered heat from the diesel
generators for space heating needs. During the last 10 years, 41 heat recovery systems have been
updated or newly installed in rural Alaska. Approximately 33 communities have completed studies
that show a heat recovery system is technically feasible.416 Table 31 shows the costs and benefits for
the evaluated projects over their expected 20-year economic lives.
Table 31: Heat recovery opportunity, includes communities with an existing study417
AEA energy region
Number of
communities
in region
Number of
cost-effective
projects
identified
Investment
needed for
cost-
effective
projects
Net benefit
of cost-
effective
projects
Heating oil
displaced
yearly
Yukon-Koyukuk/Upper
Tanana 50 3 $10,351,000 $12,849,000 39,000
Aleutians 12 2 $364,000 $2,100,000 31,000
Lower Yukon-
Kuskokwim 47 7 $2,733,000 $1,841,000 57,000
Bristol Bay 27 2 $710,000 $673,000 18,000
Bering Straits 16 1 $617,000 $551,000 14,000
Northwest Arctic 11 2 $877,000 $58,499 9,000
Copper River/Chugach 21 0 0 0 0
Kodiak Region 11 0 0 0 0
North Slope 8 0 0 0 0
Southeast 40 0 0 0 0
Total of AkAES study
area 243 17 $15,654,000 $18,073,000 370,000
Table 31 includes only projects that had at least one feasibility study. Other communities may have a
viable project, but AEA lacked the data to do an analysis. With the expansion of marine manifolds to
Detroit Diesel 60 engines, the number of communities that will be able to increase their use of heat
recovery is expected to expand.418
3. Potential non-infrastructure solutions: Over the years, there have been calls to regulate fuel
distributors—companies such as Crowley, Petro Star, and others—with the belief that high retail
prices were due to price gouging by these companies. With this as a target, several academic studies
by ISER were unable to find that unusually high profits were being realized by fuel distributors.419
Additionally, an investigation by the Alaska State attorney general, which had access to proprietary
416 AEA Heat Recovery Fact Sheet. December 2016. http://www.akenergyauthority.org/Publications
417 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
418 Devany Plentovich, Steve Stassel, Bill Thompson, Mark Bryan. “Enhancing Heat Recovery by Using Marine Manifolds with
Detroit Diesel Series 60 Engines.” May 2016.
419 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 198
information, did not find any indication of excess profits from the distributors.420 It does not appear
that regulating fuel distributors would provide much benefit to communities.
Both the ISER studies and an investigation by the attorney general found large, unaccountable
differences in the local markups by the retailers, even in communities that were geographically close.
Multiple studies were unable to ascertain the cause of the differences in local retail markups.421, 422 As
was shown in Chapter 3, local retail pricing decisions can be an important driver for consumers’ cost
of energy. Because of these unaccountable differences and the de facto monopoly on fuel sales in
many communities, it is possible that regulation of local fuel retailers could be warranted. Both the
previous ISER studies and the attorney general’s report determined that the cost of regulation and
enforcement would have a net increase fuel costs.
The attorney general’s investigation also provided another novel, non-regulatory solution to the
conundrum of local markups. Instead of creating a regulatory structure to limit the markups, the
retailer would be required to be transparent about the various components of the final retail cost—
product, labor, capital, and profit. While it would not necessarily reduce the cost, the retail customers
would have a better understanding of the final cost. This would require statutory approval, as it would
create a unique class of retail products. It is difficult to know how retail fuel prices would respond to
this requirement.
CONSUMER HEATING FUEL CONSUMPTION
1. Building energy codes: Recommended by a number of previous studies and policy papers, building
energy codes for both the residential and non-residential sectors can assist in reducing future energy
costs for consumers. Given the long life of buildings, 50 to 100 years is not uncommon for a residence;
the initial design and construction can lock in the energy consumption for decades. For a relatively
minimal increase in initial cost, decades of operational costs can be reduced significantly more cost -
effectively than through retrofits.
Even in Alaska, the housing market tends to be made up of older structures. In many communities, a
sizeable percentage of the housing stock is more than 30 years old.423 Based on data available through
the Alaska Department of Labor and Workforce Development, new construction in communities does
not appear to be tied to population but is a function of budgets and funding availability.424
420 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
421 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
422 Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. Components of Delivered Fuel Prices in Alaska. June
2008. http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
423 Nathan Wiltse, Dustin Madden, By Valentine, Vanessa Stevens. “2014 Alaska Housing Assessment.” Cold Climate Housing
Research Center report for the Alaska Housing Financing Corporation. April 2014. https://www.ahfc.us/efficiency/research-
information-center/housing-assessment/
424 AEA analysis of DOL&WD housing starts and population data
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 199
In many parts of the state, particularly within the AkAES region, housing authorities are the primary
builders of new buildings, with the private sector playing a very small role in new construction.
Assuming that the rates for new construction hold steady, as shown in Table 32, this places limits on
the effectiveness of strategies like residential building codes for new construction.
Table 32: Rate of housing construction in AkAES study area425
Number of occupied units 45,000 residences
New units 2000-2014 6,500 residences
Average new units/year 430 residences/year
Number of years to turnover
housing at current rate 100 years
Building energy codes cannot be the only strategy used for reducing residential energy consumption,
because, it will take more than 100 years at the current rate of housing construction to replace the
current housing stock.
Related to building energy codes, the State could institute minimum product requirements, e.g. for
boilers/furnaces, water heaters, etc., as recommended by the VEIC report commissioned for the
AkAES.426
2. Residential energy efficiency is the primary strategy for reducing residential energy costs for existing
structures. Through the State and federal low-income Weatherization Assistance Program and the
State Home Energy Rebate program, thousands of residential buildings have been weatherized across
the state. The data collected by these programs are invaluable in understanding the additional
opportunity across the AkAES study area. Weatherization will be used generically in this section to
indicate all residential thermal energy efficiency activities, even if they are not performed under the
auspices of the Weatherization Assistance Program. The costs and benefits displayed in Table 33 are
over the expected 15-year life of the projects.
425 Data accessed from the Department of Labor and Workforce Development. 2015.
426 Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing Needs Assessment.” July
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancingAssessment.pdf?ver=2016-
08-08-135352-107
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 200
Table 33: Residential energy efficiency opportunity427
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-effective
projects
Net benefit
of cost-
effective
projects
Heating oil
displaced
yearly
Southeast 40 25 $192,538,000 $69,066,000 4,087,000
Lower Yukon-
Kuskokwim 47 44 $74,468,000 $50,676,000 1,231,000
Copper
River/Chugach 21 20 $29,805,000 $43,226,000 972,000
Yukon-
Koyukuk/Upper
Tanana
50 40 $21,191,000 $31,689,000 478,000
Bering Straits 16 15 $45,469,000 $27,527,000 866,000
Northwest Arctic 11 11 $21,523,000 $21,290,000 429,000
North Slope 8 2 $24,557,000 $19,427,000 20,000
Kodiak Region 11 9 $24,402,000 $16,926,000 540,000
Bristol Bay 27 17 $16,101,000 $12,821,000 364,000
Aleutians 12 9 $20,657,000 $6,200,000 445,000
Total of AkAES
study area 243 192 $470,715,000 $298,852,000 9,436,000
Building energy codes would take a very long time to improve the efficiency of the residential building
stock in Alaska. There is a very large opportunity for weatherization to reduce Alaskans’ energy costs.
Even though the Weatherization Assistance Program and Home Energy Rebate programs have been
successful, there are still thousands of residences that need to be weatherized. Though the total
investment is large--nearly half a billion dollars total—every individual investment is relatively small.
Based on a 2010 survey by the U.S. Forest Service, homeowners were willing to spend $250-$1,000
per year for increased energy efficiency.428
Residential efficiency appears to be cost-effective in almost all AkAES communities. While the
opportunity is substantial–over 9 million gallons of heating fuel saved per year—it is less than the 11.1
million gallons in potential savings in the non-residential sector seen in Table 26. The relatively lower
amount of residential heating fuel savings is from the greater number of heat sources for residences,
including firewood and electricity, and the work already done to weatherize m ore than 10,000
residential buildings and the new housing built by housing authorities to high standards in the AkAES
region.
Residential efficiency will also help to protect Alaskans from the fluctuations in the price of heating
oil. Figure 101 shows the expected yearly savings of a weatherized home. The figure assumes the
427 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
428 David Nicholls, Allen Brackley, and Valerie Barber. “Wood Energy for Residential Heating in Alaska: Current Conditions,
Attitudes, and Expected Use.” July 2010. https://www.fs.fed.us/pnw/pubs/pnw_gtr826.pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 201
average energy savings from weatherization in western Alaska and uses historical prices to estimte
savings.
Figure 101: Example of residential savings from weatherization429
Based on the changes in the world oil market over the past 15 years, the amount of savings the
resident could expect varied from approximately $2,000 to nearly $4,000 per year.
3. Non-residential weatherization was included in the previous section on reducing electricity
consumption. See Table 28 for the results. The estimated savings in heating oil are slightly more than
those for the residential sector. This may be due to a number of factors, including a greater diversity
of heating fuels for residential buildings, greater total square footage of non-residential buildings,
higher intensity use in some non-residential building types, and/or a disconnect between who
operates the building and who pays the energy bills.430
4. Water and wastewater efficiency can include efficiencies in the use of both electricity and heat.
Savings can be found through improved operations, lowering set points for water temperatures,
replacing water heaters and inefficient pumps, and installing more efficient lighting . A common
misconception is that the water and wastewater systems are primary consumers of energy in most
communities. Based on the greater amount and quality of data developed through the AkAES, it is
clear that water and wastewater systems are important consumers in many communities, but
generally a small percentage of the overall consumption.
The Alaska Native Tribal Health Consortium (ANTHC) has performed more than 60 energy audits on
community water and wastewater systems over the past several years. This data, along with modeled
consumption data when actuals were not available, were used to estimate the costs and benefits of
water and wastewater efficiency opportunities over the expected 15-year life of the project.
429 AEA analysis of multiple sources
430 Richard Armstrong. “White Paper on Energy Use in Alaska’s Public Facilities.” For AHFC. October 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
$-
$1,000
$2,000
$3,000
$4,000
2000 2005 2010 2015Dollars Saved per YearExample of residential savings from weatherization
Assumes 2000-2016 Average Brent Crude Prices
Source: AEA analysis
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 202
Table 34: Water & wastewater efficiency opportunity431
AEA energy
region
Number of
communities
in region
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-
effective
projects
Net
benefit of
cost-
effective
projects
Heating
oil
displaced
yearly
kWh
saved
yearly
Lower Yukon-
Kuskokwim 47 33 $2,682,000 $10,050,000 99,000 777,000
Yukon-
Koyukuk/Upper
Tanana
50 26 $2,675,000 $6,735,000 89,000 518,000
Bering Straits 16 12 $2,404,000 $5,129,000 81,000 319,000
Northwest Arctic 11 8 $1,710,000 $4,655,000 27,000 536,000
Bristol Bay 27 17 $1,317,000 $3,211,000 35,000 299,000
Aleutians 12 9 $650,000 $1,280,000 17,000 135,000
Kodiak Region 11 6 $272,000 $600,000 9,000 75,000
Southeast 40 6 $292,000 $565,000 10,000 81,000
Copper
River/Chugach 21 2 $101,000 $353,000 5,000 44,000
North Slope 8 0 $0 $0 - -
Total of AkAES
study area 243 119 $12,106,000 $32,583,000 377,000 2,786,000
Improvements to the efficiency of water and wastewater systems can represent locally important
savings opportunities with excellent returns on investment. Although the total estimated savings is
less than some other project types, the energy cost savings would be distributed across the entire
community.
ARUC reported in 2013 that infrastructure improvements were expensive but easy, one-time fixes
that were expected to benefit the community. Without changes to the operations and maintenance
practices, which are less expensive but more difficult, new infrastructure, and the concurrent benefits,
could not be expected to be maintained over time.432
5. Non-infrastructure solutions for reducing heating fuel consumption exist. While building occupant
behaviors can have a marked impact on the building’s electricity consumption (lights can be turned
off, TVs unplugged, etc.), the energy needed to keep a building warm is more fixed by the physical
constraints of the building and the climate. Certain occupant behaviors, such as the set point for the
interior temperature, turning the thermostat down when the building is unoccupied, and if doors and
windows are left open, will affect consumption considerably. Given that behavioral changes are often
low- to no-cost actions, informing people on how their behavior can impact their energy costs is an
important part of any energy education and outreach program.
431 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
432 John Nichols. “Lessons Learned: Rural water systems & operational efficiency.” Presentation to the Alaska Rural Energy
Conference. April 30, 2013. http://www.uaf.edu/files/acep/2013_REC_Lessons%20Learned-
Rural%20Water%20Systems%20&%20Operational%20Effciency_John%20Nickels.pdf
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 203
COMPARISON OF OPPORTUNITIES
The infrastructure opportunities presented in this chapter are compared in Table 37. The project types
are arranged by the amount of diesel and heating oil that could be offset. In reading the table, it is
important to remember the caveats and limitations of each project-type analysis. For instance, residential
and non-residential ASHP rank high on the table, but the results do not include an analysis of if there is
sufficient excess capacity in the communities to run the ASHPs. If new capacity must be built, the
economics of ASHPs would change and would likely end up being uneconomic in most communities.
Annually, study area communities consume approximately 90 million gallons of heating oil and 30 million
gallons of diesel for electricity generation. The table shows that around half of the heating oil could be
displaced through a combination of project types, but there is overlap between projects within
communities that is not addressed in the table, overstating the possible total savings.
Table 355 does not rule out potential double counting of energy cost reductions. Some of the savings
identified by the AkAES project are mutually exclusive—cordwood, pellets, and non-residential ASHPs are
displacing the heating oil for non-residential buildings in most of the same communities. There is also
some overlap between non-residential efficiency and these previous three opportunities. Similarly, some
overlap between the residential ASHP and residential weatherization exists. A number of communities
had cost-effective wind and hydro resources, but only one of the resources would likely be developable.
All of the generation projects are compared against existing grant-funded projects under the assumption
that they are debt-financed. Under the current assumption, few new generation infrastructure projects
will decrease communities’ energy costs. As existing infrastructure reaches the end of its useful life, it will
be important to evaluate the options within the community to provide the necessary service at the lowest
possible cost.
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 204
Table 35: Comparison of infrastructure opportunities433
Type
Number of
communities/
interties
Number of
communities
with cost-
effective
projects
Investment
needed for
cost-effective
projects
Lifetime net
benefit of
cost-effective
projects
Annual diesel
offset by
generation
&/or efficiency
(gallons)
Annual heating
oil displaced
(gallons)
Extra capacity
needed/offset
(kW)
Non-residential
efficiency 264 151 $412,503,000 $363,602,000 5,440,000 11,087,000 -17,000
Residential ASHP 243 18 $461,364,000 $240,417,000 17,879,000 30,000
Residential
efficiency 243 192 $470,715,000 $298,852,000 9,436,000
Hydro 397 16 $362,432,000 $191,459,000 5,900,000
Non-residential
ASHP 243 25 $95,072,000 $86,801,000 5,562,000 9,000
Wind 225 11 $127,961,000 $52,779,000 4,440,000
Biomass--
cordwood 243 34 $32,341,000 $13,165,000 1,204,000
Water/wastewater
efficiency 243 119 $12,106,000 $32,583,000 214,000 377,000
Heat recovery 243 17 $15,654,000 $18,073,000 370,000
Biomass--pellets 243 14 $4,372,000 $2,131,000 304,000
Powerhouse
replacement 186 1 $17,528,000 $1,919,000 288,000
Solar 160 6 $127,000 $37,000 1,800
Interties 186 1 $614,000 $588,000
433 Alaska Affordable Energy Model version model 0.24.1, data 0.24.0
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 205
Based on AEA’s analysis of the best available data, non-residential, residential efficiency, and
water/wastewater efficiency projects are cost-effective in the largest number of communities and
residential and non-residential efficiency have the two highest net benefits.
Thermal projects—biomass, ASHPs, and heat recovery—are the next tier of opportunity. Each of these
project types has a somewhat limited geographic area of where they are cost-effective, and there is
overlap between them. Additionally, the analysis does not include the costs associated to provide the
excess generation capacity needed (39MW) to capture the full ASHP opportunity.
The cost-effectiveness of generation projects is very site specific. Replacing the status quo generation
systems with new hydro, wind, powerhouse replacements, solar, and interties each have locally significant
applications, but none of them are applicable in more than 10% of communities in the AkAES study area.
For generation projects, the greatest identified benefit is from hydro, although this includes projects that
may not be possible because of permitting restrictions and overlap with projects currently under
construction or recently finished. Also note that the net benefits of hydro are over the 50 -year expected
life of the projects, which accounts for its relatively high net benefit.
Technology and costs will likely change, and cost-effective opportunities may be different in the future. It
will be important to continue to update and provide communities with the best available data about
expected cost and performance.
A number of new technologies have not been included in this analysis, including tidal, water, in-river, and
other technologies. The application of these future technologies to Alaska will require that the technical
potential is carefully and realistically vetted to limit the amount of non-productive investments by the
State and communities.
Table 36: Comparison of non-infrastructure opportunities
Potential Opportunity Expected Benefit
Consolidation of utilities $15M/year in non-fuel cost savings
Operational and management
efficiencies $5.3M, overlap with consolidation
Generation efficiency 2.1M gallons of diesel saved per year
Line loss reduction 1.0M gallons of diesel saved per year
Fuel transportation improvements <$1M in operational savings per year
Fuel co-ops Uncertain, but potentially viable
Training Uncertain, but likely viable
Residential electricity efficiency Uncertain, but likely viable
Regulate fuel distributors Does not appear to be viable
Regulate fuel retailers Does not appear to be viable
Switch to LNG, propane Does not appear to be economically viable
Based on the AEA’s data and analysis there appears to be significant cost savings that could be gained
through consolidating utilities and/or improving the operational and management efficiency of utilities.
February 2017 CHAPTER 6: Affordable Energy Opportunities Page | 206
Reducing the retail costs of fuels is more complicated. Although a couple of potential sites for increased
bulk fuel storage were identified, the other potential strategies for reducing retail costs were either
uncertain or did not appear to be viable. Even though the local decisions on the retail price of fuel is an
important driver of cost, AEA could not identify an effective way to influence this.
The potential savings from improving generation efficiency (over 2.1 million gallons of diesel or $4.7
million/year) and reducing line losses (over 1.0 million gallons of diesel or over $2 million/year) is sizeable
and very likely cost-effective.
February 2017 CHAPTER 7: Plan and Recommendations Page | 207
CHAPTER 7: PLAN AND RECOMMENDATIONS
Previous chapters have looked at the factors that impact energy affordability. Chapter 7 applies this
research to develop a practical, achievable plan and actionable recommendations for the “design,
development, construction, [and] financing of required infrastructure.”
The plan and recommendations focus on six strategies:
1) use data to assist communities, program administrators and policy-makers in making more informed,
data-driven decisions;
2) strategically target opportunities that are most likely to reduce the cost of energy in communities;
3) evaluate all projects as if they will be financed by loans;
4) increase access to federal and private funding, particularly loans;
5) increase accountability for the State, utilities, and communities; and
6) create a source of stable and sustainable funding.
The AkAES plan and recommendations will reduce the total need for State funding. Though implementing
the plan may increase State operating costs, these will be offset by a reduction in State capital spending
on energy projects in the AkAES study area achieved through a combination of data-driven decision
making, diversification of financing sources, and improved accountability. Even if State revenues recover
sufficiently to provide a stable source of funds, the plan will help improve coordination, provide greater
accountability for State agencies and recipients of State funding, and increase the return on the State’s
community energy investments.
PLAN TO ADDRESS KEY BARRIERS TO AFFORDABLE ENERGY
It is difficult to reduce the cost of energy dramatically for communities in the AkAES study area without
significant subsidy, as was shown in Chapter 6. Too many barriers exist that the State cannot meaningfully
influence. The plan developed through the AkAES can provide for incremental improvement by connecting
the research findings to potential policies. In addition to strategies for reducing energy costs for both heat
and electricity, new strategies are needed to diversify project financing while ensuring sufficient State
funds to implement the energy programs and projects.
Each of the following sections — “Energy costs for heat and electricity”, “Transition from state grants to
increased debt financing”, and “Sustainable State energy funding” — summarizes research presented in
this report on the cost drivers the State can and cannot influence. Recommended policy mechanisms are
included for each of the sections. Footnotes provide references to other reports that have included similar
recommendations.
ENERGY COSTS FOR HEAT AND ELECTRICITY
Energy costs are driven by complex variables. Some can be influenced by State actions; most cannot. For
both electricity and heating fuels, energy cost is determined by two factors: the market rates paid by
energy consumers and the amount of energy consumed by the end user.
February 2017 CHAPTER 7: Plan and Recommendations Page | 208
AEA estimates that more than 120 million gallons of diesel and heating oil are consumed in the AkAES
study area annually. Since these fuels must be imported into communities, a significant amount of the
money spent on energy leaves Alaska communities.
At 2016 prices, AEA estimates total electricity costs at about $300 million per year for the study area, with
diesel fuel accounting for about 20% of that cost. Since the largest consumers of electricity (Juneau, Sitka,
Ketchikan and Kodiak) generate nearly 100% of their electricity from renewable resources, the percentage
spent on imported diesel is much higher than 20% in the balance of the study area. Chapter 6 identified
potential electric cost savings of approximately 10% through a combination of infrastructure and non-
infrastructure changes.
At 2016 prices, AEA estimates that annual heating oil costs are about $330 million in the AkAES study
area. The retail price of heating oil is more closely tied to global oil prices than electric rates are. Firewood
is an important secondary heating fuel that accounts for as much as 40% of residential thermal loads in
some regions, offsetting the total consumption of heating oil in these regions. Other heating fuels, such
as propane, natural gas, and coal, are used significantly less across the study area.
Given the preponderance of petroleum fuel consumption as a driver of energy costs, the following
sections on heat and electricity primarily focus on how to reduce costs associated with heating oil and
diesel generation. Although there are many similarities across communities, there is no one-size-fits-all
solution. Strategies deployed to increase access to affordable energy must be tailored to the specific
resources, needs and capacity of the community and/or utility they are intended to benefit.
HEAT ENERGY COSTS
Heating residential and non-residential buildings account for approximately 75% of all non-transportation
petroleum fuels consumed in the AkAES study area. Particularly in PCE communities where the cost of
electricity is subsidized, heating oil constitutes the majority of consumers’ energy costs.
Rates: In 2016, the retail price of heating oil ranged from a low of $1.40 in the North Slope Borough where
the borough subsidizes residential heating fuel costs, to a high of $10 per gallon. The median was $4.55
per gallon.
Cost drivers the State cannot influence:
1. The international market price for oil.
2. Many of the delivery cost drivers, including:
a. the large distances from refineries which increases the transportation component of fuel
costs;
b. the relatively shallow draft required to reach many coastal and riverine communities, which
limits the volume of fuel that can be barged at one time; and
c. the limited season that northern ports are ice-free and rivers are navigable. The short delivery
window leads to lower utilization of capital for barge carriers, driving costs up.
3. The extra risks and costs of purchasing fuel one or two times per year. The retail price will only respond
to changes in commodity costs very slowly, which could be beneficial or detrimental depending on
February 2017 CHAPTER 7: Plan and Recommendations Page | 209
whether the price of oil is rising or falling. Regardless of price fluctuations, storing a year’s worth of
fuel ties up a significant amount of capital that cannot be used for other community purposes.
4. The availability of local alternative energy resources.
Cost drivers the State can influence:
1. Efficiencies in fuel delivery by supporting:
a. local infrastructure improvements such as marine headers and moorings
b. nonprofit fuel distributors
c. regional bulk fuel facilities (locations on the upper Kuskokwim and upper Yukon have been
found to be potentially cost-effective)
2. Economies of scale for fuel purchasing through regional organizations
3. The cost of storage (e.g. through improvements in infrastructure and management through the Bulk
Fuel Upgrade program)
4. The identification of cost-effective alternative energy sources and fuels, such as air-source heat
pumps (ASHPs), biomass and heat recovery
5. The risk local retailers face of not selling all the purchased fuel during the heating season and/or being
unable to collect payment
6. The profit earned by fuel distributors and local retailer, neither of which are currently regulated (local
retail markups are highly variable and sometimes exceed $3/gallon)
7. Energy efficiency standards for building and heating appliances
Recommended policy mechanisms the State can use to influence these cost drivers:
1. Strengthen data collection and analysis of alternate heating choices
2. Provide assistance in identifying, comparing, scoping and accessing financing for cost-effective
alternative energy or energy efficiency projects
3. Provide assistance in rate setting434, 435
4. Provide assistance for regional organizations interested in providing fuel services to communities436,437
5. Provide access to financing for regional and/or site-specific bulk fuel storage438
6. Provide access to loans for bulk non-petroleum fuels (e.g. biomass)
Consumption: Average community residential heating oil consumption ranges from 500 gallons to more
than 2,500 gallons per year in the AkAES study area. There are stark differences across regions and
communities due to climate, building size, and building quality. Some consumers have chosen to use
firewood and electricity as their primary heat source where it is cost-effective; this includes 40% of
434 Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s gasoline pricing
investigation”, 2010. http://www.law.state.ak.us/pdf/civil/021810RuralFuelPricinginAlaska.pdf
435 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
436 Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. “Components of Delivered Fuel Prices in Alaska.”
June 2008. http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
437 Alaska Attorney General 2010.
438 Wilson et al, 2008.
February 2017 CHAPTER 7: Plan and Recommendations Page | 210
residences in the Yukon-Koyukuk/Upper Tanana that use wood as their primary heat source, and 20% of
residences in Southeast that use electricity. Even with these exceptions, heating oil remains the
predominant heating fuel in homes across the AkAES study area.
Non-residential buildings in the study area almost universally heat with heating oil. The exceptions are
areas with local natural gas (Barrow and Nuiqsut) and some communities in Southeast with very low -cost
hydropower. Of the approximately 10,000 non-residential buildings in the AkAES study area, less than 150
are known to use an alternative to heating oil for space heat. These include recovered heat from diesel
generators, biomass, air-source and ground-source heat pumps, and secondary loads from renewable
energy projects.
Cost drivers the State cannot influence:
1. Alaska’s cold climates
Cost drivers the State can influence:
1. Building efficiency for new and existing residential and non-residential buildings
2. Consumer behaviors to conserve energy
3. Distribution of state funding and financial incentives for energy efficiency projects
Recommended policy mechanisms the State can use to influence the cost drivers:
1. Fulfill the intention of AS 44.99.115 and enact residential and non-residential building energy
codes439,440 ,441 ,442 ,443
2. Extend residential energy efficiency program services to renters444, 445
3. Provide greater transparency of energy consumption data446
4. Assist communities to identify, compare, scope and access financing for cost-effective projects
5. Support regional entities interested in assisting communities with efficiency projects447, 448
6. Provide technical assistance for building audits and retrofits
439 Walker/Mallot Transition Team Conference. “Team Report”. Consumer Energy. November 21-24, 2014.
https://gov.alaska.gov/Walker_media/transition_page/combined-report_final.pdf
440 Cady Lister, Brian Rogers, and Charles Ermer. “Alaska Energy Efficiency Program and Policy Recommendations.” June 5,
2008. http://www.cchrc.org/sites/default/files/docs/EE_Final.pdf
441 John Davies, Nathaniel Mohatt, Cady Lister. “Alaska Energy Efficiency Policy and Programs Recommendations: Review and
Update.” June 27, 2011. http://www.cchrc.org/sites/default/files/docs/Interim_EE_Policy_Report.pdf
442 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
443 Richard Armstrong. “White Paper on Energy Use in Alaska’s Public Facilities.” For AHFC. October 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
443 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
444 Steve Colt, Ginny Fay, Matt Berman, Sohrab Pathan. “Energy Policy Recommendations Draft Final Report.” January 25, 2013.
http://www.iser.uaa.alaska.edu/Publications/2013_01_25-EnergyPolicyRecommendations.pdf
445 Walker/Mallot Transition Team Conference. “Team Report”. Consumer Energy. November 21-24, 2014.
https://gov.alaska.gov/Walker_media/transition_page/combined-report_final.pdf
446 Allen et al. 2016
447 Colt et al, 2013.
448 Allen et al. 2016
February 2017 CHAPTER 7: Plan and Recommendations Page | 211
7. Provide funding for low income residential weatherization assistance program449, 450, 451, 452, 453, 454
8. Provide statutory authority for utilities, communities and boroughs to allow on-bill and/or property
assessed financing options455
9. Require a measurable reduction in fuel consumption456
ELECTRICITY ENERGY COSTS
The drivers of electricity costs are more complex than for heating fuels. The retail rate of a kWh of
electricity is broadly divided into fuel costs and non-fuel costs. Fuel costs are determined by the unit cost
of the fuel (free for renewables), generation efficiency and line losses. Non-fuel costs include personnel,
overhead and operations and maintenance (O&M).
Setting aside data from the five large utilities in the study area that produce nearly 100% of their electricity
with hydro and wind power (Juneau, Sitka, Kodiak, Ketchikan/Petersburg/Wrangell, Metlakatla), diesel
used for electric generation accounts for nearly 50% of all non-transportation petroleum fuel consumed
in communities. Total spending on electricity (including fuel and non-fuel costs) across the study area
accounts for a little less than half of energy costs paid for by consumers and through government
subsidies.
Power Cost Equalization provides $30 million to $40 million in subsidies to residential and qualifying
community facility customers, representing about 28% of all sales in PCE-eligible communities. The
subsidy is covered by investment income from the PCE Endowment, a savings fund established by the
legislature.
Rates: The lowest electric rates in the AkAES study area—approximately $0.10/kWh—are in Southeast
communities with access to State-financed hydropower. Outside of these communities, rates range from
$0.15 to $1.80/kWh, with a median in PCE-eligible communities of $0.62/kWh. A number of communities
and the North Slope Borough provide a direct subsidy to consumers to reduce the impact of high electric
rates.
The cost of fuel as a percentage of the residential rate varies by community. Across the AkAES study area,
the median value is 55%, but some communities have nearly no fuel costs, while in others the residential
rates do not cover the full fuel costs either through intentional subsidy or poor rate setting.
449 Lister et al, 2008.
450 Davies et al, 2011.
451 Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An Analysis of the Market
Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
452 Alaska Arctic Policy Commission. “Final Report of the Alaska Arctic Policy Commission.” January 30, 2015.
http://www.akarctic.com/wp-content/uploads/2015/01/AAPC_final_report_lowres.pdf
453 Colt et al, 2013.
454 Allen et al. 2016.
455 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
456 Walker/Mallot Transition Team Conference, 2014.
February 2017 CHAPTER 7: Plan and Recommendations Page | 212
Cost drivers the State cannot influence:
1. The drivers of the delivered cost of fuel as outlined in the “Heat Energy Costs” section above
2. The population size of communities and resulting economies of scale for generation and distribution
3. The availability of local renewable resources
4. The availability of local or borough taxes to provide local subsidies
Cost drivers the State can influence:
1. The efficiency of diesel transportation and delivery, as outlined above in “Heat Energy Costs”
2. The identification of cost-effective alternative energy sources and fuels
3. The efficiency and performance of existing infrastructure including generation efficiency and line loss
4. The economic life of infrastructure
5. Improvements in utility management, such as
a. accurate and full reporting for eligible expenses to PCE
b. effective rate setting
c. encouraging virtual economies of scale by consolidating utility management functions
d. identifying other revenue sources, such as heat sales
6. Distribution of capital and direct consumer subsidies
7. Requirements for accessing State funding
Recommended policy mechanisms the State can use to influence the cost drivers:
1. Assist communities to identify, compare, scope, and access financing for cost-effective projects457, 458
2. Assist regional organizations in providing energy services (financial, managerial, and/or technical
assistance) to communities459, 460, 461
3. Prioritize State capital subsidies based on community financial need
4. Fund generation, transmission, and distribution projects, with performance, financial, and
management standards to extend the economic life of energy infrastructure
5. Align incentives to maintain infrastructure462
6. Provide technical assistance to meet financial, managerial, and performance standards463, 464
457 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
458 Mark Foster & Northern Economics. “Alaska Rural Energy Plan, Initiatives for Improving Energy Efficiency and Reliability.”
April 2004. https://alaskastateenergy.files.wordpress.com/2007/12/2002ruralenergyplanaea-northernecon.pdf
459 Holdman et al, 2016.
460 Foster & Northern Economics, 2004.
461 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
462 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
463 Colt et al, 2003.
464 Holdman et al, 2016
February 2017 CHAPTER 7: Plan and Recommendations Page | 213
7. Support best practices and requirements to meet financial, managerial, and performance
standards465, 466, 467, 468, 469
8. Establish requirements to cost-effectively reduce diesel consumption through improvements to
generation and line loss efficiency, demand side efficiency and/or integration of renewables470
Consumption: Residential electric bills in the AkAES study area average approximately $100/month. In
the lowest-cost communities (rates under $0.15/kWh), average monthly consumption is approximately
1,000 kWh. In the highest-cost communities (rates after subsidies above $0.60/kWh), the average is closer
to 200 kWh/month. This indicates that targeting communities with low rates will be more effective in
reducing electric consumption than targeting communities with higher rates, where high prices already
provide a strong incentive to conserve energy. Many electric utilities have already experienced reduced
per capita sales for residential electricity, in part due to federal energy efficiency standards for lighting
and other consumer electronics.
In a typical AkAES community, the residential sector accounts for approximately half of all electric sales,
but across the whole study area the percentage of residential sales relative to all sales ranges from 8% to
70%. With such great variation, it is clear that it will be important to target programs and projects by
sector to achieve effective reductions in electricity consumption community-wide.
As many consumers lack perfect information to identify the value of efficiency and/or lack access to
capital, it is widely recognized that there is a failure in the market for consumers to make choices that are
in their own best interest. The State has limited mechanisms to mitigate this market failure, nine of which
are outlined below.471
Cost drivers the State cannot influence:
1. Population changes in communities—which can reduce sales and spread fixed costs over fewer
consumers and kWhs
2. Consumer appliance and technology changes—generally to be more efficient, but some new
purchases increase consumption (bigger TV screens, for example)
Cost drivers the State can influence:
1. Non-residential and residential energy efficiency
465 Allen et al, 2016.
466 Colt et al, 2003.
467 Foster & Northern Economics, 2004
468 Riley et al, 2016.
469 Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible Communities.” January 20,
2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergyServicesAlternatives%20final.
pdf
470 Commonwealth North. “Energy for a Sustainable Alaska: The Rural Conundrum.” February 2012.
http://www.commonwealthnorth.org/download/Reports/2012_CWN%20Report%20-
%20Energy%20for%20a%20Sustainable%20Alaska%20-%20The%20Rural%20Conundrum.pdf
471 Jim Lazar. “Electricity Regulation in the US: A Guide.” Second Edition. The Regulatory Assistance Project. 2016.
http://www.raponline.org/wp-content/uploads/2016/07/rap-lazar-electricity-regulation-US-june-2016.pdf
February 2017 CHAPTER 7: Plan and Recommendations Page | 214
2. State standards for consumer product energy efficiency
3. Consumer subsidies that affect energy consumption
4. Availability and interest rates on loans for energy efficiency
5. Distribution of grant funds for energy efficiency and conservation
Recommended policy mechanisms the State can use to influence the cost drivers:
1. Assist communities to identify, compare, scope, and access financing for cost-effective projects472, 473
2. Fulfill the intention of AS 44.99.115(1)(A) and enact residential and non-residential building energy
codes474,475 ,476 ,477 ,478
3. Assist regional organizations interested in providing energy efficiency services to communities
4. Provide funding and flexible financing for energy projects
5. Prioritize State capital subsidies based on community financial needs
6. Institute energy efficiency standards to be met by utilities and facility owners that receive PCE
7. Use utility rate setting to offset any negative impacts of decreased kWh sales479
8. Require a measurable reduction in energy consumption480, 481
9. Enforce AS 42.45.130 and require utilities to pursue energy efficiency and demand-side management
before increasing capacity482
TRANSITION FROM STATE GRANTS TO INCREASED DEBT FINANCING
Because the State has less money available for capital appropriations than it has historically, more projects
will need to be financed through some combination of state loans, federal grants and loans, and private
loans. The State can assist communities in making the transition from grants to loans by facilitating
changes to the business models of the State, utilities, and communities. There are distinct barriers to
472 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
473 Mark Foster & Northern Economics. “Alaska Rural Energy Plan, Initiatives for Improving Energy Efficiency and Reliability.”
April 2004. https://alaskastateenergy.files.wordpress.com/2007/12/2002ruralenergyplanaea-northernecon.pdf
474 Walker/Mallot Transition Team Conference. “Team Report”. Consumer Energy. November 21-24, 2014.
https://gov.alaska.gov/Walker_media/transition_page/combined-report_final.pdf
475 Cady Lister, Brian Rogers, and Charles Ermer. “Alaska Energy Efficiency Program and Policy Recommendations.” June 5,
2008. http://www.cchrc.org/sites/default/files/docs/EE_Final.pdf
476 John Davies, Nathaniel Mohatt, Cady Lister. “Alaska Energy Efficiency Policy and Programs Recommendations: Review and
Update.” June 27, 2011. http://www.cchrc.org/sites/default/files/docs/Interim_EE_Policy_Report.pdf
477 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
478 Richard Armstrong. “White Paper on Energy Use in Alaska’s Public Facilities.” For AHFC. October 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
478 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
479 John Davies, Nathaniel Mohatt, Cady Lister. “Alaska Energy Efficiency Policy and Programs Recommendations: Review and
Update.” June 27, 2011. http://www.cchrc.org/sites/default/files/docs/Interim_EE_Policy_Report.pdf
480 Walker/Mallot Transition Team Conference, 2014.
481 Davies et al, 2011.
482 Commonwealth North. “Energy for a Sustainable Alaska: The Rural Conundrum.” February 2012.
http://www.commonwealthnorth.org/download/Reports/2012_CWN%20Report%20-
%20Energy%20for%20a%20Sustainable%20Alaska%20-%20The%20Rural%20Conundrum.pdf
February 2017 CHAPTER 7: Plan and Recommendations Page | 215
accessing debt financing for communities, utilities, and building owners that are different from project-
level barriers. As with other basic infrastructure—roads, airports, sanitation systems, landfills, health
clinics, telecommunications—energy is necessary to a community’s health, safety, and general well-being,
yet not all communities have the rate or tax base to support the full cost of critical infrastructure or to
secure a private-sector loan under market terms. Some combination of State funding and policies to
reduce barriers to debt financing is needed to address energy affordability in these communities.
Cost drivers the State cannot influence:
1. The population size of communities, which strongly influences whether they have a sufficient rate or
tax base to afford the full cost of energy infrastructure
2. The risk tolerance of private-sector investors, who typically require a higher return on investment or
are less willing to invest in communities lacking strong financials and traditional collateral
3. Other financing decisions by non-State lenders
Cost drivers the State can influence:
1. The bankability of entities by strengthening their financial, management and technical capacity to
reduce the financial and operational risks of projects
2. The bankability of projects by identifying cost-effective and risk-appropriate projects
3. The allocation of grant funds based on the ability to pay
4. Lowering the transaction costs for lenders/investors and borrowers
5. Building flexibility in funding opportunities to address utilities’ and communities’ needs
6. Developing or adopting financial instruments to help communities and utilities secure private-sector
investments
7. Promoting knowledge of investment opportunities in rural Alaska
8. Permitting a return on equity to be an allowable expense for PCE reimbursement
Recommended policy mechanisms the State can use to influence the cost drivers:
1. Provide technical assistance to identify and scope bankable projects483
2. Assist regional entities to help communities, utilities, and facility owners to identify and scope
bankable projects484, 485
3. Develop utility financial, managerial, and technical capacity standards486, 487
4. Create financial instruments to mitigate financial risk for private investors488
483 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
484 Holdman et al, 2016.
485 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
486 Allen et al, 2016.
487 Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management, Maintenance and
Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm.
488 Allen et al, 2016.
February 2017 CHAPTER 7: Plan and Recommendations Page | 216
5. Provide funding flexibility to address community needs489
6. Focus grant funding on project phases, technologies, and communities that are least able to secure
conventional financing490
7. Maintain online resources with transparent, reliable, and up-to-date data and analysis to inform
communities and investors of project potential491
8. Expand the types of financing to include on-bill financing and commercial property assessed clean
energy (C-PACE)492
SUSTAINABLE STATE ENERGY FUNDING
Lack of sustainable program funding is a major barrier to the success of all current State energy programs,
with the exception of PCE. Identifying “a source of rent, royalty, income or tax” is a requirement of the
AkAES enabling legislation.
State energy programs have experienced large year-to-year variability—increases when State revenue is
high and sharp declines when revenue is low. Since 2000, more than $1 billion has been spent in federal
and state capital funding of energy programs and projects in the study area; more than three-quarters of
which was federal spending. It appears unlikely that this level of funding will return in the foreseeable
future. With fewer government grant dollars available, it is important to consider community energy costs
in comparison with a less subsidized future, rather than a past with significant government subsidy.
Recommended policy mechanisms the State can use to fund energy programs and projects:
1. Future State revenue generated by the proposed North Slope gasline, as designated in the Alaska
Affordable Energy Fund493
2. Use current State endowments to fund specific energy programs494
3. Universal service charge on the sale of electricity, heating oil and natural gas495, 496, 497
489 Allen et al, 2016.
490 Holdman et al, 2016.
491 Holdman et al, 2016.
492 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
493 AK Stat § 37.05.610 (2015)
494 Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for Private Investment in
Rural Alaska Energy Projects.” December 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver=2016-12-19-124505-280
495 Cady Lister, Brian Rogers, and Charles Ermer. “Alaska Energy Efficiency Program and Policy Recommendations.” June 5,
2008. http://www.cchrc.org/sites/default/files/docs/EE_Final.pdf
496 Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May 2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecommendations2012.pdf
497 Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for Rural Alaska.” April 2016.
https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
February 2017 CHAPTER 7: Plan and Recommendations Page | 217
RECOMMENDATIONS
The 20 recommendations that follow represent the most promising of the mechanisms identified above—
those with the greatest potential to impact energy affordability in the AkAES study area. The
recommendations begin with a new State energy goal, which is followed by 19 proposed changes in
statute or regulation that will assist the State in achieving the goal. The recommendations build on the
direct experiences of Alaska’s energy programs within the study area, as well as research of best practices.
STRENGTHEN STATE GOALS
Given the critical importance of sustainable community energy systems that are safe, stable and reliable,
it is recommended that the State energy goals be enhanced to include:
All communities will have safe, stable, reliable, and affordable energy by 2030.
Barrier(s) addressed: State energy goals do not explicitly address the basic, underlying energy needs of
communities. Current State goals speak to increasing renewable energy, efficiency, natural gas
distribution, use of a loan program, and that the state should remain a leader in petroleum and natural
gas production and become a leader in renewable and alternative energy development. None of these
speak to the development and maintenance of basic, critical energy infrastructure.
Connections to other recommendations: All other recommendations aim to achieve this goal.
February 2017 CHAPTER 7: Plan and Recommendations Page | 218
THE FOUR PILLARS OF THE ALASKA AFFORDABLE ENERGY STRATEGY
The AkAES proposes an evidence-based
management framework to guide decision-
making. Each recommendation aims to address
barriers to achieving affordable energy in the study
area. Implementation of the recommendations
requires changes to statute, regulation and/or
policy. The recommendations are organized into
four categories, or pillars, that support the goal of
delivering safe, reliable, stable, and affordable
energy:
A. Identification of cost-effective projects
B. Financing cost-effective projects
C. Accountability and sustainability
D. Funding State energy programs
The State has a limited number of levers to influence its energy policy objectives. Since the State very
rarely owns or operates energy infrastructure, it must use indirect measures to convince independent
entities to achieve State energy goals. To this end, the recommendations proposed by the AkAES employ
at least one of the following levers:
direct financing (e.g. grants, loans, incentives)
technical assistance (e.g. the collection and sharing of data, information, analysis/evaluation,
consultation)
requirements (e.g. mandates, regulations, performance standards)
To be most effective, policy objectives need to be addressed using more than one lever. Each policy
objective is supported by a combination of direct financing, technical assistance, and requirements. While
each individual recommendation would achieve benefits if implemented as a standalone action, the
greatest benefit would come from implementing the recommendations together.
It is important that the State does not create unfunded mandates for communities, utilities, and facility
owners that are affected by the recommendations. In cases where the recommendations are
requirements, funding, whether as loans, grants, or technical assistance, should also be made available.
Safe, Reliable, Stable &
Affordable Energy
A. Identification B. Financing Projects C. Accountability & Sustainability D. Funding Programs Collaboration, stakeholder engagement &
comprehensive research
February 2017 CHAPTER 7: Plan and Recommendations Page | 219
A. IDENTIFICATION OF COST-EFFECTIVE PROJECTS
As shown in Chapter 6, there are a limited number of
ways to reduce the cost of energy in AkAES
communities. A one-size-fits-all approach to creating
affordable energy does not work for Alaska, and
particularly not for the diverse communities in the
study area. One way to improve decision-making and
thereby reduce energy costs is to improve the quality
and availability of community-level data needed to
inform strategic decisions about energy projects and
programs. Improved decision-making for programs and
projects will benefit communities while also helping to
safeguard the State’s investments.
The AkAES has identified many infrastructure and non-infrastructure opportunities for reducing the cost
of energy in communities. A greater variety of performance, financial, and managerial data, as well as
specific types of community-level data, will need to be collected and analyzed in order to adequately
evaluate these opportunities and identify the most cost-effective.
A1. IMPROVE DATA COLLECTION AND ANALYSIS
Collect and make publicly accessible community-level energy data for all of Alaska’s communities
that receive PCE or have populations greater than 50.
Collect and make publicly accessible data regarding State energy programs for the purpose of
improving their cost-effectiveness.
Maintain a regularly updated online reconnaissance-level analysis tool, the Alaska Affordable
Energy Model, to provide guidance on the cost-effectiveness of energy opportunities in Alaska
communities.
Benefits: High-quality energy data and analysis are important planning tools for communities, the State,
and other investors. This data could help deliver savings through better project identification, risk
management, and program design. Future data collection and analysis can build on tools developed for
the AkAES like the Alaska Affordable Energy Model.
Barriers addressed: Communities and potential investors, both public and private, lack data and data-
driven decision-support tools to identify potential infrastructure and non-infrastructure opportunities.
Community energy data is not systematically captured and analyzed to help support the direction of
energy programs. When the risks associated with community energy projects are not clearly understood,
the result can increase costs and impede investment.
Connections to other recommendations: An energy data program, coordinated with the State’s existing
energy data initiatives, would collect and analyze data generated through the implementation of other
Safe, Reliable, Stable &
Affordable Energy
A. Identification B. Financing Projects C. Accountability & Sustainability D. Funding Programs Collaboration, stakeholder engagement &
comprehensive research
February 2017 CHAPTER 7: Plan and Recommendations Page | 220
recommendations. The data program would help identify projects for financing (Recommendations B2
and B4) and create efficiency in assisting communities (Recommendations A2, C1, and C2) through new
data and analytic tools. The data collected could assist communities in meeting regulatory requirements
(Recommendation C3).
A1.1: Community-level energy data
1. Basic community and utility data
Table 37: Recommendation A1—Basic community and utility data to be collected
Data need Attribute Frequency
Electricity
Rates Yearly
PCE rates Yearly
Fixed customer charges Yearly
Consumption by sector Yearly
Generation by source Yearly
Diesel price ($/gal) Yearly
Diesel price forecast Every two years
Heat
Source—heating oil, propane, natural
gas, biomass, etc. Yearly
Rates Yearly
Fixed customer charges Yearly
Consumption by sector Yearly
Heating fuel price forecast Every two years
Other Population—historical & forecast Every five years
February 2017 CHAPTER 7: Plan and Recommendations Page | 221
2. Current community infrastructure
Table 38: Recommendation A1—Current community infrastructure data to be collected
Infrastructure
type Attribute Frequency
Petroleum bulk
fuel
Tank capacity Every five years
Tank ownership Every five years
Tank age & condition Every five years
Code compliance Every five years
Non-petroleum
bulk fuel
Type Every five years
Storage capacity Every five years
Storage ownership Every five years
Storage age & condition Every five years
Code compliance Every five years
Power systems
Type Yearly
Age Every five years
Condition Every five years
Diesel efficiency Yearly
Line loss Yearly
System balance Yearly
Frequency stability Yearly
Reliability Yearly
Regulatory/code compliance Yearly
Building
infrastructure
Housing—number, size, types, consumption, Wx status Every five years
Water/wastewater—size, types, consumption, Wx
status
Every five years
Non-residential buildings— number, size, types, use,
consumption, Wx status
Every five years
February 2017 CHAPTER 7: Plan and Recommendations Page | 222
3. Utility business management data
Table 39: Recommendation A1—Utility business management data to be collected
Utility
standard Attribute Frequency
Financial
Revenue—sources Yearly
Expenses—fuel/non-fuel Yearly
Debt & savings Yearly
Managerial
Business plan Yearly
Regulatory/code compliance Yearly
Best practices Yearly
Technical
Training certification Yearly
Performance Yearly
4. Local energy goals, such as the goals that have been identified through the Regional Energy Planning
process (for example, local job creation, the elimination of diesel, reducing the local contribution to
climate change, among others). The State should engage communities to reconfirm or update their
goals at least every five years.
A1.2: State energy program data
Table 40: Recommendation A1—State energy program data to be collected
State
programs Attribute Frequency
Infrastructure
programs
Administrative costs Yearly
Project costs Yearly
Project reports Yearly
Infrastructure performance Yearly
O&M data Yearly
Lessons learned/risks Every two years
Non-
infrastructure
programs
Savings—energy, cost Yearly
Administrative costs Yearly
Metrics associated with program success Yearly
A1.3: Reconnaissance-level project analysis tool
The Alaska Affordable Energy Model (AAEM), developed as part of the AkAES, provides simplified access
to and analysis of energy data from many state and federal sources. The tool, which was developed by
AEA and coded by the University of Alaska’s Geographic Information Network of Alaska (GINA), should
continue to be updated and improved.
February 2017 CHAPTER 7: Plan and Recommendations Page | 223
The usefulness of the model will increase over time as data and other analytic tools are added. The AAEM
provides a high-level assessment of opportunities based on numerous data sources, including the Alaska
Energy Data Gateway, the Alaska Retrofit Information System, the Alaska Energy Data Inventory, AEA’s
Renewable Energy Fund program, work performed by the Alaska Center for Energy and Power, Institute
of Social and Economic Research, the Department of Energy, national laboratories, and numerous other
sources.
The AAEM uses historical and status quo data on energy costs, consumption, generation, and
infrastructure to create a snapshot of energy use and costs in a community. These data inputs should be
updated yearly.
Forecasts are developed for the factors that will lead to changes in the consumption, generation and costs
of energy in a community. These factors include the prices of diesel, heating oil and electricity, community
population, and trends in consumption. Diesel and heating oil price forecasts should be updated every
two years. Population forecasts should be updated every five years. Consumption trends are calculated
by the model and do not need to be updated.
The most recent and best data on resource availability (including wind, hydro, solar, residential and non-
residential efficiency, diesel efficiency, and heat pumps) are captured from multiple sources in the AEEM.
If a study has estimated the costs and generation for a proposed project, those values can be incorporated
into the model, otherwise average values will be used. Data from individual projects should be updated
upon project completion. Generic resource data, such as the wind map, should be updated when sufficient
new data warrants it. The costs and expected generation or savings from potential projects should be
updated every three years or as warranted by the rate of technology change.
A community-level economic analysis is performed by integrating the status quo, forecasted and resource
data for all potential resources in a community. A reconnaissance-level analysis is provided for each
potential resource, which allows a community or potential investor to compare opportunities available to
the community and identify the best, most cost-effective opportunities to pursue.
Metrics for success:
1. Up-to-date data
2. Access data and model
a. number of communities, agencies, etc.
A2. CLARIFY STATE’S ROLE IN WORKING WITH COMMUNITIES ON PROJECT IDENTIFICATION, PLANNING,
AND FINANCING
Enacting this recommendation would clarify the policy under AS 44.99.115(2)(C) to establish a process for
providing community assistance outside of grant fund management. The State can designate a sole agency
to work with communities to identify, plan and secure financing for improvements to generation
efficiency, line losses, fuel storage, use of renewable energy, residential and non -residential energy
efficiency, and improvements to bulk fuel or utility management, operations and maintenance. Although
February 2017 CHAPTER 7: Plan and Recommendations Page | 224
AEA performs this function through multiple programs in support of the organization’s mission, there is
no clear mandate to provide ongoing assistance to communities in identifying cost-effective projects with
the potential to reduce their energy costs. This should be formalized as a core responsibility of the State
energy office as the need is currently larger than existing programs can deliver.
Benefits: Reduced cost to communities through improved project selection and operation. Savings to the
State through reduced PCE expenditures. Savings for participants in the Alaska Heating Assistance
Program are also possible.
Barriers addressed: A clear process for communities engaging the State regarding energy projects outside
of grants and loans does not exist. The selection of a State agency or program for this specific purpose
creates responsibility, accountability and continuity for communities working on energy projects outside
of the management of specific grant funds.
Connections to other recommendations: This recommendation would help utilities fulfill the cost-
effective fuel reduction target under Recommendation C6 and the efficiency requirement outlined in
Recommendation C4. By being involved early on in project development, project risks can be reduced and
least cost solutions can be identified. Provide assistance with technical scoping for all phases of project
development under the auspices of the Community Energy Fund for Alaska (Recommendation B2).
Additional info: For many communities, technical assistance is required for understanding both the
potential consequences of integrating new projects into existing energy systems and the economic
analysis of that opportunity. By combining the latest resource data with the latest technology, community,
and project risk data, a reliable economic analysis is possible, which can be used as the basis for
comparisons between projects. It is only with this sort of cross-sectional analysis that opportunities
available to communities can adequately be identified and evaluated.
The State, along with its public- and private-sector partners, can provide valuable technical assistance to
help communities discover and develop cost-saving energy opportunities from conception to completion.
Given the risks associated with energy projects, improving project identification and development
through technical assistance can be an important way to reduce risks for the State and private lenders
while easing the burden on communities.
The State and its partners can provide different tiers of assistance and oversight. This could range f rom
help developing Request for Proposals (RFPs) for communities to access services from Independent Power
Producers (IPPs) to directly managing a project, as is done for most Rural Power System Upgrade projects.
Clear standards, clearly communicated at each project stage can help ensure high-quality work is
performed. Some entities may not need any assistance, but third party oversight or review can mitigate
project financing risks.
Metrics for success:
1. Communities assisted
a. Analyses performed
February 2017 CHAPTER 7: Plan and Recommendations Page | 225
b. Projects pursued or determined to be uneconomic
2. Non-State financing accessed
3. Money saved
a. Community
b. State
4. Energy saved (efficiency)
5. Energy delivered (generation, storage)
A3. ESTABLISH RESIDENTIAL AND NON-RESIDENTIAL BUILDING ENERGY CODES FOR NEW CONSTRUCTION
AND MAJOR RENOVATIONS
Recall 134 statutory references to building codes back into one section of State statute.
Grant authority for code administration to one or two agencies.
Authorize a code commission through a public regulation process to determine and update
building and energy codes.
Benefits: By enacting the intention of AS 44.99.115((1)(A), building to a higher standard is cost-effective
and less expensive than retrofitting a poorly built building later. There are direct savings to the Power Cost
Equalization and Alaska Heating Assistance programs as well as potential benefits to public health, safety
and the environment. Alaska Housing Finance Corporation has already compiled all instances of building
codes in statute and drafted options in regard to a methodology to incorporate and update future code
changes, along with a model for enforcement.
Barriers addressed: Buildings consume the most energy in communities. New buildings that are not built
to an efficient standard have higher operational and lifetime costs. Currently, building codes are
referenced in more than 134 Alaska statutes with authority for enforcement spread throughout six state
agencies. Consolidation of these codes and agency responsibilities will create cost savings for the State
and clarity for communities and builders.
Connections to other recommendations: Building energy codes will reduce the need for some services in
the future, such as energy retrofit programs and PCE (Recommendations B5 and D4).
Metrics for success:
1. Measurement and verification standards available through the US Department of Energy for building
codes including:
a. Compliance with new codes
b. Energy and cost savings relative to status quo
February 2017 CHAPTER 7: Plan and Recommendations Page | 226
B. STATE ASSISTANCE IN FINANCING COST-EFFECTIVE PROJECTS
After the identification of cost-effective projects,
money must be available for implementation, either
in the form of grants or loans. With a constrained
State budget, it is likely that State-backed loans will
be more prevalent in the future. Research from the
AkAES demonstrated a need for greater flexibility in
financing options that align with community needs.
The reality is that as loan-funded infrastructure
replaces grant-funded infrastructure, it is likely
unavoidable that consumer energy costs will rise. In
this funding climate, it becomes even more
important that communities pursue the most cost-
effective project that suits their needs.
Constrained budgets make it more difficult for the State and federal governments to grant funds at the
rate seen over the past fifteen years. The State must now leverage its funds more effectively by reducing
transaction costs for both potential investors and recipients, encouraging more debt financing and
assisting in the transition from grants to loans. Grants should be targeted to bring a project or utility to a
bankable position (e.g. partial subsidy to allow for financing).
The recommendations under this pillar provide mechanisms to reduce loan transaction costs for
borrowers and lenders, match communities with appropriate funding, create incentives for project
performance, and improve financial outcomes for project owners and their lenders.
B1. ALLOW BULK FUEL LOAN PARTICIPANTS TO PURCHASE NON-PETROLEUM FUELS
Communities in the State’s Bulk Fuel Loan Program could use loans to purchase alternative fuels,
such as cordwood, pellets and liquefied natural gas (LNG).
Benefits: Extends the same financial risk reduction for communities that use non -petroleum fuels as the
State provides for communities using petroleum fuels.
Barriers addressed: Some energy infrastructure projects use non-petroleum fuels. There is currently no
State-funded loan that allows for the purchase of those fuels. Inclusion of other fuels in the Bulk Fuel Loan
program resolves this issue.
Connections to other recommendations: Alternative fuel sources may be identified through mechanisms
created by other recommendations; communities that currently rely on the Bulk Fuel Loan program would
need similar financial risk reduction for these fuels.
Metrics for success:
1. Number of non-petroleum fuel loans issued
Safe, Reliable, Stable &
Affordable Energy
A. Identification B. Financing Projects C. Accountability & Sustainability D. Funding Programs Collaboration, stakeholder engagement &
comprehensive research
February 2017 CHAPTER 7: Plan and Recommendations Page | 227
B2. CREATE A ONE-STOP-SHOP FUND FOR COMMUNITIES THAT ALLOWS FOR SEGREGATED STATE,
FEDERAL, AND PRIVATE GRANTS AND LOANS TO BE BLENDED TO DEVELOP ENERGY PROJECTS
Communities often face a similar set of barriers and opportunities when seeking energy project funds.
The State can create cost efficiencies by consolidating funding information in one location and reducing
lines of repetitive inquiry and overlap by multiple agencies.
The Community Energy Fund for Alaska (CEFA) would:
be a one-stop-shop for communities to access funding options.
be utilized as a broad service, offering public and private funding sources.
offer assistance in accessing existing grants and loans for energy projects.
be accessible to utilities, municipalities, boroughs, cities, Tribes and non -residential facility
owners to the extent allowed for by the original funding source.
be available for generation, distribution, transmission, and energy efficiency projects.
require that the State make a determination that the project represents a cost-effective strategy
for meeting a community energy need.
NOTE: For utility-scale generation projects, the use of CEFA funds would require adherence to the
proposed management, financial, and performance standards (Recommendation C3).
Benefits: This recommendation reduces the need for State grant funds and increases involvement of non-
State investors. The CEFA has potential to reduce transaction costs for borrowers and investors. Existing
State energy infrastructure grant and loan programs could be consolidated under CEFA to create cost-
efficiencies. New financial products with greater flexibility would be added to allow communities to more
easily pursue a greater range of cost-effective projects than is currently possible.
Barriers addressed:
Lack of administrative capacity can be the limiting factor in accessing funding needed to complete
a project.
Fewer State grant opportunities are available for energy projects, and communities may have
difficulty identifying and securing alternative funding/financing sources.
Funding sources are not always available for identified community needs. As a result,
communities develop sub-optimal projects based on the type of funding available.
Transaction costs for projects in communities with small populations can negatively impact the
project’s economics and create barriers to achieving a financing deal.
Enacting this recommendation would allow communities to focus on identifying and developing
the best project options rather than pursuing myriad funding options.
Many current programs provide insufficient incentives for communities and utilities to maintain
new energy infrastructure.
Incomplete financing plans stall and cancel projects.
Connections to other recommendations: Taken together, the recommendations related to project
identification could create a pipeline of projects for this new fund. The proposed utility standards
February 2017 CHAPTER 7: Plan and Recommendations Page | 228
[Recommendation C3] would help to reduce risk for State and other investors. CEFA could be accessed by
regional organizations assisting communities (Recommendations C2) or as a source of financing for
residential and non-residential efficiency programs (Recommendation B4). Recommendation B3 is a
subset of this recommendation.
Additional information: The Community Energy Fund for Alaska would make it easier for projects to
connect with multiple funding sources, allowing the State to better leverage its resources. To the extent
that other public and private entities also desire to leverage their investment (or benefit from the financial
risk mitigation that the leveraging represents), the CEFA represents a win-win for investors and
communities.
Use of multiple funding sources can increase administrative burden; the State can assist by reducing the
transaction costs of accessing federal and private loans and grants. This can be done by shifting some of
the burden to the State and/or simplifying the processes for applicants.
By focusing on the opportunities in communities, greater flexibility in financing, such as is needed for non-
residential energy efficiency projects, can be achieved for communities. This will also allow State expertise
to be leveraged by interested investors to expand into currently underserved markets, such as commercial
energy efficiency.
For investors, several means would be available to mitigate project and financial risks. Match
requirements could be flexible to account for a community’s ability to pay and the project phase.
Preliminary resource evaluations are the highest risk portion of any project. It would be appropriate that
the State take on more financial responsibility for the higher risk phases of project development, requiring
greater levels of match as projects move toward construction.
Greater levels of accountability for applicants would also increase the likelihood of the project achieving
its long-term goals.
In funding projects, a stepwise approach with clear go/no-go decision points is imperative. Fatal flaws are
sometimes identified only after significant study, and it is easy for project participants to be ensnared by
the sunk-cost fallacy—that shutting down a project would constitute a waste of the money already spent
on previous phases. Clear guidelines for what is necessary for a project to move forward would be
developed for each project type and phase.
Early in the new funding paradigm, it may be necessary to provide incentives for private financing to enter
the market, in addition to loan products that reduce the risks for private lenders, such as loan-loss reserves
or similar financial risk mitigation products.
Metrics for success:
1. Number of “at risk”/high-cost communities served
2. Financing leveraged
a. Federal grants
b. Federal loans
February 2017 CHAPTER 7: Plan and Recommendations Page | 229
c. Private loans
d. Private grants
3. Money saved by communities
4. Energy saved
5. Financial risks
a. Defaults, late payments
B3. CREATE A LOAN PROGRAM WITH REFUND PROVISIONS THAT REWARDS PROJECT PERFORMANCE
The loan provisions, as a financing product available through the Community Energy Fund for
Alaska, will allow for partial annual reimbursements over the economic life of the project to
incentivize meeting performance and reporting objectives.
Benefits: The opportunity to receive a refund creates an additional incentive for communities to maintain
infrastructure, achieve energy project objectives, and meet reasonable performance standards. The State
will experience savings through reduced need for PCE, fewer emergency technical calls to repair
equipment, and less frequent capital grant requests for infrastructure repair and replacement. The
increased performance and life of the infrastructure will also reduce costs for consumers.
Barriers addressed: Once a project is completed, it is difficult to ensure good maintenance protocols are
followed. Without proper equipment maintenance, communities will not receive the full economic benefit
from energy infrastructure projects, resulting in increased costs for the community through higher O&M
costs and shorter infrastructure lifespans.
Connections to other recommendations: This recommendation is a key financial product of the
Community Energy Fund for Alaska (Recommendation B2). It also directly ties in with the goals associated
with accountability and sustainability. The enhanced business and financial assistance to utilities being
proposed (Recommendation C3) will ensure that utilities are able to meet performance standards.
Additional information: The refund provisions would only apply to State contributions, unless specifically
agreed upon by other financial partners. Depending on specific contractual elements, multiple metrics
could be tracked, with specific measurable goals, resulting in partial reimbursement for achieving each
standard. The refund could apply to interest and/or principal payments, depending on the nature of the
loan.
Metrics for success:
1. Participation
2. Reporting
3. Within performance
4. Current/default
February 2017 CHAPTER 7: Plan and Recommendations Page | 230
B4. STATUTORILY ALLOW VOLUNTARY ON-BILL FINANCING AND COMMERCIAL PROPERTY ASSESSED
CLEAN ENERGY
Benefits: On-bill financing and Commercial Property Assessed Clean Energy (C-PACE) are voluntary
programs that allow financing of building-level renewable energy and efficiency projects to be bound to
the property rather than the property owner, removing as a barrier to investment the number of years
the owner expects to keep the property. C-PACE was introduced in 2016 and has been reintroduced in
2017.
C-PACE financing is a voluntary loan for qualifying energy efficiency measures that is placed on the
property tax bill. Since not all communities in the AkAES study area have property taxes, it would not be
available to all consumers. The repayment obligation is transferred with the property upon sale.
On-bill financing allows for a voluntary loan for qualifying energy efficiency measures that can be paid
back through a customer’s utility bills. The utility can act as the source of funds or just a mechanism for
paying back the loan.
Both on-bill financing and C-PACE can also be tools in a demand-side management program to extend the
time before a utility needs to invest in new generation capacity. Each of these financial mechanisms can
allow for extended loan terms and off-book debt, easing cash flow restraints and concerns about limiting
future access to debt financing.
Barriers addressed: The length of time a building stays in the same hands is variable and sometimes
difficult to predict. Individuals and organizations, therefore, may not fully recoup their energy efficiency
or renewable energy investments through lower energy bills. If the payback period is longer than their
planned tenure as owner, they will be reluctant to address needed efficiency measures or integrate
renewable energy systems into building design or renovations. Commercial property owners want to
minimize how much debt is booked.
Connections to other recommendations: The CEFA (Recommendation B2) could act as a funding source
for on-bill financing or C-PACE. Either of these financing mechanisms could assist large public facilities in
financing the cost-effective retrofits required in Recommendation C4. Regional entities, supported under
Recommendation C2, could provide services needed for making these financial instruments available in
communities.
Metrics for success:
1. Percent of eligible communities using either of the financing tools
2. Number of loans
3. Default rate
4. Money saved
5. Energy saved
February 2017 CHAPTER 7: Plan and Recommendations Page | 231
B5. STABILIZE THE STATE’S FUNDING FOR RESIDENTIAL EFFICIENCY PROGRAMS
Ensure a $10M per year baseline for the low-income weatherization assistance program.
Modify rules of the Home Energy Rebate (HER) program to expand weatherization services if the
program receives new funding. Develop income-based match requirements to better leverage
State investment in residential efficiency and allow participation by households whose incomes
are too high for low-income weatherization but may be too low for the Home Energy Rebate
program as it is currently structured.
Benefits: The recommendation allows households above maximum income limits for the Weatherization
Assistance Program to receive residential efficiency services. The new match approach for the Home
Energy Rebate program effectively leverages greater private investment, while stabilizing funding for the
Weatherization Assistance Program secures a well-trained workforce and provides services to those with
the highest need.
Barriers addressed: Funding uncertainty jeopardizes the maintenance and reduces the capacity of energy
efficiency programs that serve consumers with the highest need. Low-income residents are least able to
access the efficiency savings that will have the most direct effect on their ability to afford energy. Existing
income limits are rigid, leaving many consumers without access to residential efficiency services. The
AkAES study area was underserved by the HER program; smaller rural communities especially need more
assistance to access weatherization services and increase participation in the HER program.
Connections to other recommendations: On-bill financing (Recommendation B4) could be used to assist
HER participants in financing the match requirement. CEFA (Recommendation B2) could be a source for
stable loan funding for improvements.
Additional information: Regional entities (Recommendation C2) could be leveraged and/or created to
assist with the delivery of residential efficiency services to make the revised HER program successful in
the AkAES study area.
Metrics for success:
1. Low Income Weatherization Assistance Program
a. Number completed
b. Energy saved
c. Money saved
2. Home Energy Rebate Program
a. Number completed in AkAES study area
b. Energy saved
c. Money saved
d. Private dollars leveraged
February 2017 CHAPTER 7: Plan and Recommendations Page | 232
C. ENSURING THE ACCOUNTABILITY OF PROJECT PARTICIPANTS AND ACHIEVING THE
SUSTAINABILITY NEEDED FOR BRINGING AFFORDABLE ENERGY TO COMMUNITIES
At both the state and local levels, the systems for
delivering affordable energy frequently lack the
incentives and requirements needed to create
accountability and sustainability. For instance, while
the PCE program has established technical standards
related to diesel efficiency and levels of line loss, there
are no standards related to utility operational
efficiency, e.g. proper maintenance and financial
management. Few State programs are required to
track or report the ongoing performance of the
systems they fund; often there are no external
incentives or disincentives for grantee performance
and reporting.
Greater accountability will improve project performance and foster the development of utilities with
greater internal technical, managerial and financial capacity. Poor performance often results in consumers
paying more than necessary for electricity due to excessive line loss, lower than expected generation,
and/or higher than average administrative costs. The State pays more on increased PCE payments,
technical assistance, and capital grants than would be necessary with greater utility accountability.
Greater accountability would improve access to non-State financing, creating a structure within which
utilities and communities become more financially healthy.
While government requirements are frequently viewed negatively, regulations and codes do not
necessarily impede development. They can be assets in developing new markets while providing needed
consumer protection. For example, the Department of Transportation and Public Facilities was required
to retrofit 25% of all State-owned facilities that are 10,000 square feet or larger by 2020. Having met this
requirement early, the State is saving $2.8 million per year in energy costs. By signaling the importance of
certain actions or behaviors, new codes and regulations can enable the private and public sectors to
capture cost savings that have been historically overlooked. However, if the overarching goal is to make
energy more affordable in the AkAES study area, the following recommendations must be paired with
access to sufficient technical assistance and funding so that the State does not burden communities and
utilities with unfunded mandates that offset any reductions in the cost of energy.
C1. STRENGTHEN BUSINESS AND FINANCIAL MANAGEMENT ASSISTANCE FOR PCE-ELIGIBLE UTILITIES
Benefits: Improving utility management and financial practices can reduce non-fuel costs, which average
approximately 40% of retail electric rates, saving millions of dollars for consumers and the State. Improved
business practices will also improve a utility’s ability to access financing.
Safe, Reliable, Stable &
Affordable Energy
A. Identification B. Financing Projects C. Accountability & Sustainability D. Funding Programs Collaboration, stakeholder engagement &
comprehensive research
February 2017 CHAPTER 7: Plan and Recommendations Page | 233
Barriers addressed: Research indicates that inefficient business operations increase consumer electricity
costs. Analysis also shows that many utilities actually underreport their PCE-eligible expenses, thereby
reducing their PCE payments, increasing financial risks and decreasing potential access to non-State
financing of energy projects.
Connections to other recommendations: Recommendation C3 will identify communities in need of
business and financial management assistance. The data compiled and analyzed in Recommendation A1
will facilitate this identification. The CEFA (Recommendation B2) would require better business and
financial management from participants.
Additional information: This recommendation will assist in implementing the requirements set out in AS
42.45.900. Assistance can be provided through the identification of key performance indicators (KPIs) that
will allow utilities to benchmark their own performance, assistance in data collection for the KPIs, the
creation of business management templates that provide guidance for achieving best practices, and direct
assistance for communities where needed.
Metrics for success:
1. Number of communities assisted
2. Effective rate for communities within 5 cents of the PCE floor
3. Reduction in utility non-fuel costs
4. Number of utilities with business plans, and number following plan successfully
5. Improved financial ratios
6. Increased percent of utilities attaining standards
7. Increased in additional revenue sources for utilities
C2. DRAW ON THE STATE’S PARTNERSHIPS WITH REGIONAL AND STATEWIDE ENTITIES TO MORE COST-
EFFECTIVELY PROVIDE NEEDED ASSISTANCE
Assistance could include: technical and managerial services such as utility financials; record
keeping and management; energy project management, bulk fuel and power systems operations,
maintenance, and technical services; and non-residential efficiency.
Benefits: Increasing the economy of scale of management could unlock millions of dollars of savings
through improved utility operations. Regional entities are likely to know more details about a local energy
provider and may be able to quickly identify and respond to a need. AEA’s relationships with regional
organizations, including the recent regional planning efforts, could be effectively leveraged to assist with
this recommendation.
Barriers addressed: Many communities do not have adequate capacity or the economy of scale to cost-
effectively manage local energy systems.
Connections to other recommendations: This recommendation will assist utilities in meeting the
standards proposed in Recommendation C3. The regional entity could help communities to access CEFA
February 2017 CHAPTER 7: Plan and Recommendations Page | 234
funds (Recommendation B2) to communities. Partnerships could also assist with non-residential efficiency
(Recommendation C4) and utility fuel reduction strategies (Recommendation C6).
Additional information: A number of regional entities, including regional co-ops, non-governmental
organizations, Tribes, boroughs, and Native corporations, could assist with this recommendation through
formal contracts and informal coordination. The types of activities that could result from this
recommendation encompass many ways to reduce the cost of energy in communities. These include:
1. Public purpose energy service companies (so-called PPESCOs),
2. Expansion of fuel and electric co-ops
3. Expand financial, managerial, and technical assistance for communities
4. Assistance to manage the technical and financial needs of efficiency programs
5. Shared use of high cost resources
Metrics for success:
1. Number of agreements between State and regional organizations
2. Effective rate for communities within 5 cents of the PCE floor
3. Increase in additional revenue sources for utilities
4. Reduction in utility non-fuel costs
5. Reduction in utility fuel costs
6. Energy saved
7. Number of utilities with business plans, and number following plan successfully
8. Increase in percent of utilities attaining standards outlined in C3
C3. DEVELOP A COST-EFFECTIVE REGULATORY SYSTEM TO ENSURE RURAL ELECTRIC UTILITIES CONTINUE
TO MEET STANDARDS TO BE “FIT, WILLING, AND ABLE”
Benefits: The recommendation will help reduce community energy costs and State expenditures for
energy programs through improved oversight of operations and access to non-State financing. The
recommendation will help improve the quality of utility services in communities and the efficiency of State
energy programs.
Barriers addressed: There are currently no requirements that unregulated electric utilities provide proof
of operational practices that provide safe, stable, reliable, and affordable energy after they have received
their Certificate of Public Convenience and Necessity (CPCN). Insufficient data is currently collected to
assess the ability of utilities to deliver the service required by the CPCN.
Connections to other recommendations: The data gathered from the periodic review of utility operations
could feed into the State Energy Data program (Recommendation A1). The recommendation will reduce
risk for investors and provide standards for participation in the CEFA (Recommendation B2).
Recommendations C1 and C2 aim to improve utility operations and would help to support this
recommendation.
Additional information: It is important that an unfunded mandate is not created without support, and that
this recommendation is not enacted without sufficient support for communities and utilities to be
February 2017 CHAPTER 7: Plan and Recommendations Page | 235
successful. The recommendation is in the public interest, both for the consumers of the utilities as well as
the state government, as one of the main sources of funding for many utilities.
To receive a CPCN, the RCA must determine that a utility is fit, willing, and able to perform the functions.
The RCA further defines these requirements as financial, managerial and technical fitness: these
definitions are provided in the metrics section for this recommendation.
Additional statutes and regulations provide guidance for utility operation:
1. AS 42.05.291. Standards of Services and Facilities. Requires public utilities to “furnish and
maintain adequate, efficient, and safe service and facilities.”
2. 3 AAC 52.470. Engineering standards; energy purchase contracts. Requires a utility to construct,
maintain and operate its plant to “assure service reliability, service quality, and the safety of
persons and property”.
3. 3 AAC 52.475. Maintenance and testing standards. Requires utilities to adopt and pursue a
maintenance program to “permit safe, adequate, and reliable service”.
These statutes and regulations do not include reporting requirements to ensure that utilities,
economically or non-economically regulated, meet the standards.
As the intent of the recommendation is to improve consumer protection and reduce the risk to investors,
a review could be triggered by:
1. An effective electric rate outside the normal range (within $0.10/kWh of the theoretical
calculated level) for more than two consecutive years
2. Underperformance on other standard measures, such as generation efficiency and line loss, for
more than two consecutive years
3. Inadequate reporting for two consecutive years
Metrics for success:
Factors used to determine if an electric utility is “fit, willing, and able” should be based on the following
definitions of “financial, managerial, and technical fitness.” The actual performance metrics would be
determined through a public process in which potentially impacted utilities participate.
Financial Fitness: The utility must be able to pay the expenses incurred in delivering service to its
customers.
Maintain the financial health of the utility
a. Accurately account for all utility expenses and revenues
b. Maintain adequate financial ratios—current account, debt and debt-equity ratios
c. Maintain a reserve account in case of accidents, fuel price spikes or other unforeseen events
Managerial Fitness: The utility must be able to plan for the current and future needs of d elivering
service to its customers.
February 2017 CHAPTER 7: Plan and Recommendations Page | 236
1. Encourage best practices
a. Independent performance-driven board of directors
b. Professional staff
c. Price, performance and management transparency
d. Clear mechanisms for evaluating performance
2. Maintain and follow an adequate business plan including updating and planning for repair and
replacement of utility assets, staff training, etc.
a. Sustainable management improvement plan
b. Capital improvement plan
Technical Fitness: The utility must have the technical capacity to maintain a level of service consistent
with the needs of its customers and to construct, operate and maintain needed infrastructure.
1. Set standards for operator training
2. Stability and reliability
a. Frequency and voltage stability
b. Acceptable number and duration of unplanned outages
c. Availability of generation infrastructure
3. Performance requirements
a. Generation efficiency (for example, minimum of 13 kWh/gallon)
b. Line losses (for example, maximum of 12%)
c. System balance (for example, maximum of 10% out of balance between phases)
C4. REQUIRE PCE-ELIGIBLE NON-RESIDENTIAL BUILDINGS LARGER THAN 5,000 SQ. FT. TO HAVE AN
ENERGY AUDIT AND PERFORM COST-EFFECTIVE RETROFITS
Public and/or community buildings greater than 5,000 square feet would be required to perform
energy retrofits resulting in net savings within 10 years.
Benefits: Reducing the amount of energy consumption in community facilities frees up funding for other
community needs and will help ensure that the State is not paying more to operate facilities than is
necessary.
Barriers addressed: Many large community facilities are not energy efficient, increasing their operating
costs and reducing funds available for other community needs.
Connections to other recommendations: The Community Energy Fund for Alaska (Recommendation B2)
provides a path to financing efficiency projects. Recommendation B4, to allow on-bill financing and C-
PACE, would provide instruments to finance these retrofits. Technical assistance provided by State and
regional entities, through Recommendations A2 and C2 respectively, would support this
recommendation.
Additional information: It is imperative that additional technical and financial assistance be available to
prevent this recommendation from becoming an unfunded mandate. The recommendation also supports
February 2017 CHAPTER 7: Plan and Recommendations Page | 237
AS 42.45.130(a)—Cost Minimization, which requires PCE-eligible utilities to “cooperate with appropriate
state agencies to implement cost-effective energy conservation measures and to plan for and implement
feasible alternatives to diesel generation.”
Metrics for success:
1. Money saved by community
2. Money saved by PCE
3. Energy saved
a. Electricity
b. Heat
C5. EMPOWER THE REGULATORY COMMISSION OF ALASKA (RCA) TO HAVE SITING AUTHORITY
OVER GENERATION AND TRANSMISSION FOR ECONOMICALLY REGULATED UTILITIES IN THE STUDY
AREA
Benefits: The recommendation provides a measure of oversight and consumer protection by reducing the
risk of building unnecessary infrastructure that must be paid for through increased rates. Low cost, but
less standard resources, such as efficiency and demand-side management, which are consistent with State
energy policy, would be more likely to be implemented. This recommendation also provides certainty that
utility investments will be recovered through rates.
Barrier(s) addressed: The identification and pursuit of least cost and low volatility resources, particularly
efficiency and demand-side management, by utilities has been historically underutilized in favor of
traditional generation projects. This potentially leads to greater costs and cost volatility for consumers.
The current ex post facto determination also complicates the achievement of the State’s non-binding
energy policy for efficiency and renewable energy by not including a formal process to consider this public
good in the implementation of the utilities’ plans.
The possibility that the RCA might not allow a utility to recover costs from a new generation plant is a
source of uncertainty for energy project investors and developers.
Connections to other recommendations: The recommendation could provide more certainty for investors
participating in the CEFA (Recommendation B2).
Additional information: Currently, the RCA makes a determination on the eligibility of energy
infrastructure to be included in the rate base after it has been built. Empowering the RCA with siting
authority would require that eligibility is determined prior to construction.
In many states, an initial review, through siting authority, is made to determine if infrastructure is
necessary, useful, and consistent with statutes and regulation. Post-construction, a second review or a
prudency review, is performed to ensure that the infrastructure was constructed and sized properly for
the customer base and the costs were reasonable. These factors determine if all or some of the
infrastructure can be included within the rate base.
February 2017 CHAPTER 7: Plan and Recommendations Page | 238
C6: REQUIRE A 1% PER YEAR FUEL REDUCTION TARGET FOR ELECTRIC UTILITIES UNTIL COST-EFFECTIVE
GAINS HAVE BEEN REALIZED
Measurement of the reduction will be on a per residential customer basis to avoid penalizing
utilities with load growth.
Benefits: Cost-effective gains will reduce costs to consumers through lower electric rates and to the State
through reduced PCE. It will increase the market for energy services to utilities and provides flexibility for
individual communities as the savings can be achieved through diesel efficiency, line loss reduction,
renewable energy installation and energy efficiency improvements.
Barriers addressed: The State has no requirement that utilities pursue cost savings through efficiency and
renewable energy projects. There is no requirement for continued improvement.
Connections to other recommendations: This recommendation helps spur the involvement of utilities in
all other recommendations.
Additional information: The recommendation will require a measurable and continuous improvement by
Alaska’s electric utilities and support the 2010 state energy policy of 50% renewable energy and 15%
improvement in energy efficiency. The recommendation also supports AS 42.45.130(a)—Cost
Minimization, which requires PCE-eligible utilities to “cooperate with appropriate state agencies to
implement cost-effective energy conservation measures and to plan for and implement feasible
alternatives to diesel generation.”
The reduction would be measured by the amount of fuel consumed to supply the residential sector. It
could start with a reasonable baseline year in order to give credit to utilities that have recently taken
actions to reduce their fuel consumption. At least 26 states have policies that could be useful in defining
the specific mechanisms by which this recommendation is implemented.
Reports of past, current and planned activities will be required every five years. The requirement will be
evaluated every five years to ensure that it continues to be cost-effective for consumers and the State. It
is important that the requirement not be an unfunded mandate, but that there is adequate access to
funds and technical assistance for utilities to be successful.
A number of potential methods for providing a financial incentive meeting the target could be provided
to utilities. Examples from other states include an increase on the return on equity allowed to the utility
or performance-based incentives that allow utilities to receive revenue based on actual savings. Potential
sources would be through rates and/or PCE payments.
Metrics for success:
1. Fuel saved
2. Money saved
a. By customer class
February 2017 CHAPTER 7: Plan and Recommendations Page | 239
b. By PCE
3. Types of measures used to achieve target
February 2017 CHAPTER 7: Plan and Recommendations Page | 240
D. SUSTAINABLE PROGRAM FUNDING
Identifying “a source of rent, royalty, income or tax”
is a requirement of the AkAES enabling legislation. In
the past fifteen years, the State has spent over $200
million in identified capital grants and $527 million in
direct consumer subsidies in the study area. The
federal government, through the Denali Commission
and USDA, provided an additional $880 million in
capital grants and over $200 million in direct
consumer subsidies in the study area. The needs that
were addressed by those appropriations will still
exist in the future. Although the AkAES
recommendations provide mechanisms to stretch
State dollars by using them more efficiently, new
sources of funding will still be required to ensure communities’ needs for safe, reliable, an d affordable
energy are met.
D1. USE THE ALASKA AFFORDABLE ENERGY FUND (AS 37.05.610) WHEN IT BECOMES AVAILABLE
Chapter 14, SLA 14 created a special account in the General Fund from which the Legislature could
appropriate money to develop energy infrastructure and programs in the areas of the state not
expected to have direct access to a North Slope natural gas pipeline.
AS 37.05.610 suggests that up to 20% of the revenue from the State’s royalty gas from an Alaska
LNG project (after the payment of rents and royalties to the Permanent Fund) may be placed in
this special account to assist with energy delivery in the AkAES target area.
Benefit: The Alaska Affordable Energy Fund could provide a sustainable source of funding.
Barrier addressed: Reduced State general fund dollars and reduced federal spending on energy
infrastructure in Alaska.
D2. PROVIDE FOR PAYMENT OF PCE ADMINISTRATIVE EXPENSES AND FUND SPECIFIC ENERGY
PROGRAMS WITH PCE FUNDS.
Benefit: This recommendation would reduce the need to draw on the Undesignated General Fund for
State PCE administration and those energy programs that have a direct impact on operations of PCE-
eligible utilities.
Barrier addressed: Reduced State general fund dollars and reduced federal spending on energy
infrastructure in Alaska.
Additional information: Given the importance of the PCE program to rural Alaska and the role that the
PCE Endowment has in ensuring the long-term viability of the program, it is only suggested that a small
portion of the earnings would be used to pay for administrative costs and directly related critical support
Safe, Reliable, Stable &
Affordable Energy
A. Identification B. Financing Projects C. Accountability & Sustainability D. Funding Programs Collaboration, stakeholder engagement &
comprehensive research
February 2017 CHAPTER 7: Plan and Recommendations Page | 241
services. Funding these services, such as circuit rider, operator training, and technical assistance, should
not reduce the amount of funding available to PCE communities and should not come directly from the
endowment or endanger the inflation-proofing of the fund.
D3. ESTABLISH A UNIVERSAL SERVICE CHARGE TO SUPPORT COMMUNITY ENERGY PROJECTS AND
PROGRAMS
Benefits: This recommendation could provide needed community energy projects with a sustainable
source of funding. It would also provide needed but currently unavailable data on heating oil
consumption.
Barriers addressed: Reduced State general fund dollars and reduced federal spending on energy
infrastructure in Alaska.
Connections to other recommendations: Creating a sustainable source of funding will allow for greater
benefit to Alaska’s energy consumers and a sustainable source of funding for the CEFA (Recommendation
B2) and Weatherization and the HER programs (Recommendation B5). Access to data on heating fuels
consumption would improve the quality of data compiled in Recommendation A1 for the analysis of
community energy projects.
Additional information: Previous energy policy reports have identified per unit energy surcharges as a
means by which other states generate receipts to fund their energy-related programs. In Alaska, this could
be accomplished by removing the existing tax exemption that applies to heating oil sales. Comparable
energy unit charges could be levied on the sale of other energy commodities to maintain parity among
major energy sources. Collection would be by the local utility or retailer from all communities within the
study area.
In the AkAES study area, at a rate of $0.07/gallon for heating oil, $0.06/ccf for natural gas, and $0.005/kWh
for electricity, approximately $13 million a year in revenue would be available for energy projects within
the study area.
D4. CONTINUE THE POWER COST EQUALIZATION PROGRAM & REVIVE THE ALASKA HEATING
ASSISTANCE PROGRAM
Benefits: The Power Cost Equalization and Alaska Heating Assistance Programs are proven programs that
help to underwrite the cost of energy in the AkAES study area.
Barrier(s) addressed: For those communities without access to cost-effective infrastructure, AEA was
instructed by the Legislature to identify a way to directly underwrite the cost of energy.
Additional information: The Power Cost Equalization program is the largest and most broad-based
consistent source of energy funding in the AkAES study area. The other AkAES recommendations and
identified opportunities for reducing the cost of energy in communities are expected to reduce costs but
not enough to eliminate communities’ need for the PCE program. It is also extremely important to
February 2017 CHAPTER 7: Plan and Recommendations Page | 242
maintain the integrity of the PCE Endowment fund to ensure the sustainability of the PCE benefit to
eligible consumers.
ADDITIONAL OPPORTUNITY FOR CONSIDERATION
CONSIDER GIVING A STATE ENTITY THE AUTHORITY TO CONSOLIDATE AND MANAGE STATE CONSUMER
ENERGY PROGRAMS
Benefits: A State entity with the authority to consolidate and manage consumer energy, to the extent that
it is reasonable, would increase efficiency of delivering State energy programs to communities. This would
assist in enacting State policy as expressed in AS 44.99.115(4)(B), to use one State office or agency “to
serve as a clearinghouse in managing the state's energy-related functions to avoid fragmentation and
duplication and to increase effectiveness.”
Barriers addressed: Forces outside of communities can create barriers to optimum project identification
and selection; many energy programs are governed by a multitude of State and federal agencies, and
evaluation criteria for projects are not always consistent across programs. Implementation of previous
recommendations may spread state energy programs over a half dozen agencies. This could create or
exacerbate institutional gaps and competing agency mandates. Developing a coordinated and strategic
plan to best assist communities is more difficult without a clear chain of command.
Connections to other recommendations: The State entity would coordinate almost all other aspects of
these recommendations, although the RCA would remain independent.
Housing all the supply, generation and efficiency programs under the same banner supports a more
comprehensive, holistic approach that will benefit communities. No individual agency has the breadth of
technical expertise needed, but across the relevant agencies, the State does have the current capacity to
implement the previous recommendations if they were less fragmented. Energy is an extremely important
issue, warranting representation by a high-level position within state government.
All loans, grants, and incentive programs would be administered by the new department. The Community
Energy Fund for Alaska would be the primary funding mechanism for community ene rgy projects and be
managed by the new department. Technical assistance for utilities and communities would leverage the
expanded technical and community knowledge available through the entity. Additionally, statewide,
regional, and community planning efforts could more easily tap into the larger pool of expertise and
knowledge.
Metrics for success:
1. Administrative cost savings
2. Energy savings
3. Communities served
February 2017 Resources Page | 243
REFERENCES AND RESOURCES
ENERGY PLANNING AND POLICY
1. Alaska Arctic Policy Commission. “Final Report of the Alaska Arctic Policy Commission.” January 30,
2015. http://www.akarctic.com/wp-content/uploads/2015/01/AAPC_final_report_lowres.pdf
2. Alaska Attorney General. “Rural Fuel Pricing in Alaska: A supplement to the 2008 Attorney General’s
gasoline pricing investigation”, 2010.
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http://www.akenergyauthority.org/Content/Publications/AKEnergyJan2009.pdf
5. Black & Veatch. “Southeast Alaska Integrated Resource Plan.” July 2012.
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6. Commonwealth North. “Energy for a Sustainable Alaska: The Rural Conundrum.” February 2012.
http://www.commonwealthnorth.org/download/Reports/2012_CWN%20Report%20-
%20Energy%20for%20a%20Sustainable%20Alaska%20-%20The%20Rural%20Conundrum.pdf
7. Dane and L Doris. “Alaska Strategic Energy Plan and Planning Handbook.” 2013. National Renewable
Energy Laboratory.
https://energy.gov/sites/prod/files/2014/05/f16/AKStrategicPlanningHandbook_v17.pdf
8. Environmental Protection Agency. “Energy and Environment Guide to Action: State Policies and Best
Practices for Advancing Energy Efficiency, Renewable Energy, and Combined Heat and Power.” 2015
Edition. https://www.epa.gov/sites/production/files/2015-08/documents/guide_action_full.pdf
9. Alaska Energy Authority. “Regional Energy Planning.”
http://www.akenergyauthority.org/Policy/RegionalPlanning
10. Information Insights & WHPacific. “Interior Alaska Regional Energy Plan.” December 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Interior%20Alask
a%20Regional%20Energy%20Plan.pdf?ver=2016-06-09-200432-767
11. Information Insights. “Aleutian and Pribilof Islands Regional Energy Plan.” December 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/AleutianPribilofIs
lands%20Regional%20Energy%20Plan.pdf?ver=2016-06-22-095050-343
12. Information Insights. “Bristol Bay Regional Energy Plan.” December 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Bristol%20Bay%
20Regional%20Energy%20Plan.pdf?ver=2016-06-22-095055-430
13. Information Insights. “Copper River Regional Energy Plan.” June 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Copper%20River
%20Regional%20Energy%20Plan.pdf?ver=2016-06-09-200431-897
14. Information Insights. “Kodiak Regional Energy Plan Volume 1.” March 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Kodiak%20Regio
nal%20Energy%20Plan%20Volume%201.pdf?ver=2016-06-20-141606-807
February 2017 Resources Page | 244
15. Information Insights. “Kodiak Regional Energy Plan Volume 2.” March 2015.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Kodiak%20Regio
nal%20Energy%20Plan%20Volume%202.pdf?ver=2016-06-20-141608-333
16. MAFA & Northern Economics. “Alaska Rural Energy Plan, Initiatives for Improving Energy Efficiency
and Reliability.” April 2004.
https://alaskastateenergy.files.wordpress.com/2007/12/2002ruralenergyplanaea-northernecon.pdf
17. National Association of State Energy Officials. “State Energy Planning Guidelines: A Guide to Develop
a Comprehensive State Energy Plan Plus Supplemental Policy and Program Options.”
https://www.naseo.org/data/sites/1/documents/publications/NASEO-State-Energy-Planning-
Guidelines.pdf
18. Riley Allen, David Farnsworth, Rich Sedano, and Peter Larsen. “Sustainable Energy Solutions for
Rural Alaska.” April 2016. https://emp.lbl.gov/sites/all/files/lbnl-1005097_0.pdf
19. Rural Energy Action Council. “Rural Energy Action Council. Findings and Action Recommendations
for Governor Frank Murkowski.” April 15, 2005. http://www.arlis.org/docs/vol1/60412439.pdf
20. Steve Colt, Ginny Fay, Matt Berman, Sohrab Pathan. “Energy Policy Recommendations Draft Final
Report.” January 25, 2013. http://www.iser.uaa.alaska.edu/Publications/2013_01_25-
EnergyPolicyRecommendations.pdf
21. Walker/Mallot Transition Team Conference. “Team Report”. Consumer Energy. November 21-24,
2014. https://gov.alaska.gov/Walker_media/transition_page/combined-report_final.pdf
22. WHPacific & Information Insights. “Prince William Sound Regional Energy Plan.” June 2016.
http://www.akenergyauthority.org/Portals/0/DNNGalleryPro/uploads/2017/1/25/PrinceWilliamSou
ndRegionalEnergyPlan.pdf
23. WHPacific “Northwest Arctic Regional Energy Plan.” June 2016.
http://www.akenergyauthority.org/Portals/0/Policy/RegionalPlanning/Documents/Northwest%20Ar
ctic%20Regional%20Energy%20Plan.pdf?ver=2016-06-27-135917-753
24. WHPacific. “North Slope Borough Energy Plan.” http://www.north-slope.org/information/north-
slope-regional-energy-plan
25. WHPacific. “Yukon-Kuskokwim Delta Regional Energy Plan.” June 2016. http://nuvistacoop.org/wp-
content/uploads/2016/08/080316_YK-Delta-Regional-Energy-Plan-web.pdf
STATE PROGRAMS
1. Alaska Energy Authority. “Bulk Fuel Inventory Assessment Report.” 2016
2. Alaska Energy Authority. “Emerging Energy Technology Fund Project Status Updates.” February
2016.
http://www.akenergyauthority.org/Portals/0/Programs/EETF/Documents/EETFProjectUpdatesFeb2
016.pdf?ver=2016-03-23-095100-640
3. Alaska Energy Authority. “Power Cost Equalization Program Guide.”
http://www.akenergyauthority.org/Content/Programs/PCE/Documents/PCEProgramGuideJuly2920
14EDITS.pdf
4. Alaska Energy Authority. “Renewable Energy Fund Round Status Report and Round IX
Recommendations.” May 2016.
http://www.akenergyauthority.org/Portals/0/Programs/RenewableEnergyFund/Documents/REFRou
nd9StatusRptPrintSpreads.pdf
February 2017 Resources Page | 245
5. Alaska Energy Authority. “Renewable Energy Fund.”
http://www.akenergyauthority.org/Programs/RenewableEnergyFund
6. David Hill, Chris Badger, Leslie Badger, Nikki Clace, and Molly Taylor. “Alaska Energy Authority:
Renewable Energy Grant Recommendation Program Impact Evaluation Report.” 2012.
https://www.veic.org/resource-library/alaska-energy-authority-renewable-energy-grant-
recommendation-program-process-and-impact-evaluation-reports
7. Rashah McChesney. KTOO Public Media. “In rural Alaska, loss of heating assistance hits hard.”
11/11/2016, http://www.ktoo.org/2016/11/11/rural-alaska-loss-heating-assistance-hits-hard/
8. Vermont Energy Investment Corporation. Renewable Energy Grant Recommendation Program
Impact Evaluation. 2012. https://www.veic.org/documents/default-source/resources/reports/veic-
alaska-energy-authority-rgrp-impact-and-process-evaluation-report.pdf?sfvrsn=2
END USE ENERGY AND ENERGY EFFICIENCY
1. Armstrong, Richard. “Measurement and Verification Review of 2010/2011 VEEP & EECBG Energy
Efficiency Retrofits.” December 17, 2013.
2. Brian Saylor & Associates. “Energy Impacts of the RurAL CAP Energy Wise Program from Program
Years 2009-2010 and 2011-2012.”
3. Cady Lister, Brian Rogers, and Charles Ermer. “Alaska Energy Efficiency Program and Policy
Recommendations.” June 5, 2008. http://www.cchrc.org/sites/default/files/docs/EE_Final.pdf
4. Alaska Energy Authority. “End Use Study: 2012” April 30, 2012.
http://www.akenergyauthority.org/Content/Efficiency/EndUse/Documents/AlaskaEndUseStudy201
2.pdf
5. Alaska Housing Finance Corporation. “2014 Alaska Housing Assessment.”
https://www.ahfc.us/efficiency/research-information-center/housing-assessment/
6. Cold Climate Housing Research Center, “Energy Efficiency Policy Recommendations for Alaska.” May
2, 2012.
http://www.akenergyauthority.org/Content/Efficiency/Efficiency/Documents/EfficiencyPolicyRecom
mendations2012.pdf
7. Cold Climate Housing Research Center. “Weatherization Assistance Program Outcomes.” August 6,
2012. http://www.cchrc.org/sites/default/files/docs/WX_final.pdf
8. Daniel Reitz, Art Ronimus, Carl Remley, Emily Black. “Energy Use and Costs for Operating Sanitation
Facilities in Rural Alaska: A survey.” October 2011.
9. Department of Transportation and Public Faculties. “Alaska Sustainable Energy Act: Annual Report.
2015 Progress Report.” January 2016
10. Golden Valley Electric. “Energy Sense Program.” http://www.gvea.com/resources/energysense
11. https://www.ahfc.us/efficiency/energy-programs
12. Information Insights, Inc. “Electric Energy Efficiency, Environmental Scan: Barriers & Opportunities”
October 7, 2011.
http://www.cchrc.org/sites/default/files/docs/Electric_EE_Environmental_Scan_Lit_Review.pdf
13. Jesse Jenkins, Ted Nordhaus, and Michael Shellenberger. “Energy Emergence: Rebound & Backfire
as Emergent Phenomena.” February 2011. http://thebreakthrough.org/blog/Energy_Emergence.pdf
14. John Davies, Nathaniel Mohatt, Cady Lister. “Alaska Energy Efficiency Policy and Programs
Recommendations: Review and Update.” June 27, 2011.
http://www.cchrc.org/sites/default/files/docs/Interim_EE_Policy_Report.pdf
February 2017 Resources Page | 246
15. Juliet Agne. “Energy Star Rebate Program: Final Report”. May 20, 2013.
http://www.cityofsitka.com/government/departments/electric/documents/EnergyStarRebateProgr
amFinalReportwithAppendices.pdf
16. Katie Conway. “Nightmute Whole Village Retrofit—then and now.” Alaska Energy Authority. January
15, 2015.
http://www.akenergyauthority.org/Content/Efficiency/Veep/Documents/NightmuteWVR20082014
FINAL11515.docx
17. Vermont Energy Investment Corporation. “Energy Efficiency Program Evaluation and Financing
Needs Assessment.” July 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESEEFinancing
Assessment.pdf?ver=2016-08-08-135352-107
18. Katie Spataro, Marin Bjork, Mark Masteller for AHFC, “Comparative Analysis of Prescriptive,
Performance-Based, and Outcome-Based Energy Code Systems,” 2011.
https://www.ahfc.us/files/9013/5754/5384/cascadia_code_analysis_071911.pdf
19. Building Codes Assistance Project for AHFC, “Alaska Gap Analysis,” 2012. http://bcapcodes.org/wp-
content/uploads/2016/01/Alaska-Gap-Analysis-Report.pdf
20. The Compliance Planning Assistance Program for AHFC, “Alaska Strategic Compliance Plan,” 2012.
http://energycodesocean.org/resource/alaska-strategic-compliance-plan
21. DOL&WD for AHFC, "Construction Cost Survey: 2014".
https://www.ahfc.us/files/7313/9664/6819/Const_Cost_2014.pdf.
22. “Energy Savers Tips for Rural Alaska.” 2014.
https://www.ahfc.us/files/4713/9327/8963/energy_saver_tips_2014.pdf
23. Richard Armstrong. “A White Paper on Energy Use in Alaska’s Public Facilities.” 2012.
https://www.ahfc.us/files/3313/5769/3854/public_facilities_whitepaper_102212.pdf
24. Northern Economics. “The AHFC Home Energy Rebate Program and Electric Consumption by
Chugach’s Residential Customers.” May 2013.
25. Kathryn Dodge, Nathan Wiltse, Virginia Valentine. “Home Energy Rebate Program Outcomes.” June
26, 2012. http://www.cchrc.org/docs/reports/HERP_final.pdf
26. David Nicholls, Allen Brackley, and Valerie Barber. “Wood Energy for Residential Heating in Alaska:
Current Conditions, Attitudes, and Expected Use.” July 2010.
https://www.fs.fed.us/pnw/pubs/pnw_gtr826.pdf
27. United States Census Bureau. “B25040: House Heating Fuel [10]”. 2008-13 U.S. Census Bureau’s
American Community Survey Office, 2013. Web. January 2015 <http://ftp2.census.gov/>.
FUEL COST DRIVERS
1. Dominique Pride, Matthew Snodgrass, Antony Scott. “Correlating Community Specific Rural Diesel
Fuel Prices with Published Indices of Crude Oil Prices, and Potential Price Projection Applications”
June 2015.
http://www.akenergyauthority.org/Content/Programs/RenewableEnergyFund/Documents/Round%
209/RuralFuelModelReportFinalDraft.pdf
2. Europe Brent Spot Price FOB (Dollars per Barrel), March 2, 2016.
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RBRTE&f=A
3. Ginny Fay, Ben Saylor, Nick Szymoniak, Meghan Wilson and Steve Colt. “Study of the Components of
Delivered Fuel Costs in Alaska January 2009 Update.” Prepared for: Alaska State Legislature, Senate
February 2017 Resources Page | 247
Finance Committee. January 2009.
http://www.iser.uaa.alaska.edu/Publications/fuelpricedeliveredupdate.pdf
4. Lisa Demer. “Bush Alaska locked into high gas prices for fuel delivered last summer and fall.” Alaksa
Dispatch News. May 31, 2016. https://www.adn.com/rural-alaska/article/bush-alaska-locked-high-
gas-prices-fuel-delivered-last-summer-and-fall/2015/01/01/
5. Meghan Wilson, Ben Saylor, Nick Szymoniak, Steve Colt, and Ginny Fay. “Components of Delivered
Fuel Prices in Alaska.” June 2008.
http://www.iser.uaa.alaska.edu/Publications/Finalfuelpricedelivered.pdf
6. Nick Szymoniak, Ginny Fay, Alejandra Villalobos-Melendez. “Component of Alaska Fuel Costs: An
Analysis of the Market Factors and Characteristics that Influence Rural Fuel Prices.” February 2010.
http://www.iser.uaa.alaska.edu/Publications/componentsoffuel3.pdf
7. Northern Economics. “Cost Assessment for Diesel Fuel Transition in Western and Northern Alaska
Communities.” December 2007. https://dec.alaska.gov/air/anpms/ulsd/cost_rpt.pdf
8. Real Petroleum Prices Crude Oil Brent Spot (Case Reference case),
http://www.eia.gov/forecasts/aeo/data/browser/#/?id=12-AEO2015
TRANSPORTATION OF FUELS
1. Jeannette Le Falsey. “Coast Guard: No spill in grounding of tanker carrying fuel to Southwest Alaska
villages.” Alaska Dispatch News. June 25, 2016. http://www.adn.com/alaska-
news/2016/06/25/coast-guard-no-spill-in-grounding-of-tanker-carrying-fuel-to-southwest-alaska-
villages/
2. Laurel Andrews. “New fuel barges deliver energy savings to rural Alaska.” Alaska Dispatch News.
May 6, 2013. https://www.adn.com/rural-alaska/article/new-barges-brought-energy-savings-rural-
alaska-electric-co-op-says/2013/05/07/
3. U.S. Corps of Engineers, Alaska District. “Alaska Barge Landing System Design Statewide Phase 1,
Various Locations Final Report.” January 2009.
http://www.poa.usace.army.mil/Portals/34/docs/civilworks/archive/alaskabargelandingsystemdesig
nstatewidephase1.pdf
4. U.S. Corps of Engineers, Alaska District. “Fuel Transportation Improvement Report.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AEAfueltransportat
ionreport101416.pdf
NATURAL GAS, LNG & PROPANE
1. Tobias Schwoerer and Ginny Fay. "Economic Feasibility of North Slope Propane Production and
Distribution to Select Alaska Communities." 2010. https://scholarworks.alaska.edu/handle/11122/4276
2. ACEP. "Screening Level Assessment of LNG for Alaska: SW and SE Alaskan Coastal PCE Communities."
Feb. 2, 2014. http://acep.uaf.edu/projects/alaska-micro-lng-market-assessment.aspx
3. Alaska Gasline Development Corp. "Greenfield Natural Gas (LNG) Economic Feasibility Study", June 8,
2011. http://www.arlis.org/thepipefiles/Record/1464950
4. Alaska Gasline Development Corp. In-State Propane Utilization Study for the Alaska Gasline
Development Corporation. July 1, 2011. http://www.arlis.org/thepipefiles/Record/1465394
5. Alex DeMarban. “Native Wildcatters push ahead with exploration at oil and gas projects.” Alaska
Dispatch News. November 17, 2016. https://www.adn.com/business-
February 2017 Resources Page | 248
economy/energy/2016/11/17/native-wildcatters-pushing-ahead-with-exploration-at-oil-and-gas-
prospects/
6. Bartz Englishoe and Associates. "Yukon-Kuskokwim Propane Demonstration Project Implementation
Report." 2009
7. Cardno Entrix. "IEP Natural Gas Conversion Analysis." 2014.
http://www.interiorenergyproject.com/Resources%20and%20Documents/IEP_Conversion_Analysis_Fi
nal.pdf
8. Ellis, Tim. “Utility officials: Test project shows LNG could help reduce cost of generating electricity in
Tok.” Nov. 4, 2016. http://fm.kuac.org/post/utility-officials-test-project-shows-lng-could-help-
reduce-cost-generating-electricity-tok
9. Fuhs, Paul. "Propane Production, Transportation and Utilization in Rural and Urban Alaska." Undated
presentation
10. Scott Goldsmith and Nick Szymoniak. "Propane from the North Slope: Could it Reduce Energy Costs in
the Interior?" 2009. https://scholarworks.alaska.edu/handle/11122/4305
11. MAFA. "Rural Alaska Natural Gas Study: A Profile of Natural Gas Energy Substitution in Rural Alaska."
1997. ftp://ftp.aidea.org/AlternativeEnergyPublications/RNGSExecutiveSummary.pdf
12. Northern Economics, Inc. “LNG Feasibility for Alaska Affordable Energy Strategy Communities.”
Prepared for Alaska Energy Authority. July 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/LNGFeasibilityStud
y2016.pdf?ver=2016-07-29-145517-400
13. Northern Economics. "In-state Gas Demand Study." 2010.
http://www.arlis.org/thepipefiles/Record/1465927
14. Northern Economics. "Memorandum: Estimated Natural Gas Demand for the NS LNG Project" 2013.
http://www.interiorenergyproject.com/Resources%20and%20Documents/Estimated%20Natural%20Ga
s%20Demand.pdf
15. Western Alaska Propane Conversion. Discussion Paper. 2010.
ftp://ftp.aidea.org/2010AlaskaEnergyPlan/2010%20Alaska%20Energy%20Plan/Propane%20Study/A
EA_Plan_Propane.pdf
GENERATION TECHNOLOGY
1. “Diesel Efficiency” Alaska Rural Energy Plan. 2004
2. Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development
Needs in support of the Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelo
pmentNeeds.pdf?ver=2016-08-08-152005-117
3. Alex DeMarban. “Department of Energy eyes hydropower to help Alaska.” Alaska Dispatch News.
October 16, 2016. http://www.adn.com/business-economy/energy/2016/10/16/department-of-
energy-eyes-hydropower-to-help-alaska/
4. Alex DeMarban. “Valdez hydropower project makes utility all-renewable in the summer.” Alaska
Dispatch News. October 14, 2016. http://www.adn.com/business-
economy/energy/2016/10/14/valdez-hydropower-project-makes-utility-all-renewable-in-summer/
5. Devany Plentovich, Steve Stassel, Bill Thompson, Mark Bryan. “Enhancing Heat Recovery by Using
Marine Manifolds with Detroit Diesel Series 60 Engines.” May 2016.
6. Elizabeth Jenkins, “Is hydropower renewable? One village in SE Alaska needs it to be.” January 6,
2017. KTOO Public Media. http://www.ktoo.org/2017/01/06/hydropower-renewable-energy-one-
village-se-alaska-needs/
February 2017 Resources Page | 249
7. Emily Kwong. KCAW. “Green Lake dam awaits replacement part to get back up and running.”
December 26, 2016. http://www.alaskapublic.org/2016/12/26/green-lake-dam-awaits-
replacement-part-to-get-back-up-and-running/
8. Leila Kheiry, “KPU back on hydro after warm, wet weekend.” KRBD. January 17, 2017.
http://www.krbd.org/2017/01/17/kpu-back-on-hydro-after-warm-wet-weekend/
9. National Renewable Energy Laboratory. PVWatts Calculator. http://pvwatts.nrel.gov/
10. US Army Corps of Engineers, Alaska District. “Alaska Hydropower Evaluation.” May 2014.
11. Vanessa Stevens, Colin Craven, Robbin Garber-Slaght. “Air Source Heat Pumps in Southeast Alaska: A
review of the literature, a market assessment, and preliminary modeling on residential air source
heat pumps in Southeast Alaska.” April 2013.
http://www.cchrc.org/sites/default/files/docs/ASHP_final_0.pdf
DATA SOURCES
1. Alaska Affordable Energy Model
2. Alaska Department of Commerce, Community, and Economic Development, Division of Community
and Regional Affairs. Alaska Community Database Online. Accessed September 2015.
https://www.commerce.alaska.gov/dcra/DCRAExternal
3. Alaska Energy Data Gateway (https://akenergygateway.alaska.edu/)
4. Alaska Energy Data Inventory. http://www.akenergyinventory.org/data
5. Alaska Energy Efficiency Map. http://www.akenergyefficiencymap.org/
6. Alaska Energy Statistics (2013)
http://www.akenergyauthority.org/Portals/0/Publications/2013DetailedSumTbl.xlsx
7. Department of Labor and Workforce Development Research and Analysis. Alaska Local and Regional
Information. http://live.laborstats.alaska.gov/alari/
8. Steve Colt and Tobias Schwoerer. “Alaska Village Energy Model.” 2013.
http://www.iser.uaa.alaska.edu/Publications/2013-07_Village_energy_model_notes.pdf
9. US Census Bureau. “American Community Survey 2009-2013 5-Year Estimates.” Accessed from
Division of Community and Regional Affairs Community Database Online.
https://www.commerce.alaska.gov/dcra/DCRAExternal/community/Details/5db73dd9-b52c-486a-
acf4-a323b8d8f3cf
CLIMATE CHANGE
1. Environmental Change (2008), http://climatechange.alaska.gov/aag/docs/O97F18069.pdf
2. General Accountability Office. GAO-09-551. “Alaska Native Villages: Limited Progress Has Been
Made on Relocating Villages Threatened by Flooding and Erosion.” 2009.
http://www.gao.gov/new.items/d09551.pdf
3. Peter Larsen, Scott Goldsmith, Orson Smith, Meghan Wilson, Ken Strezepek, Paul Chinowsky, Ben
Saylor. “Estimating future costs for Alaska public infrastructure at risk from climate change.” Global
Environmental Change. Vol. 18, Issue 3. August 2008, pp. 442-457.
http://climatechange.alaska.gov/aag/docs/O97F18069.pdf
FINANCING
1. Alaska Department of Commerce, Community, and Economic Development, Division of Community
and Regional Affairs. Alaska Taxable Database. Accessed September 2014.
https://www.commerce.alaska.gov/dcra/DCRARepoExt/Pages/AlaskaTaxableDatabase.aspx
February 2017 Resources Page | 250
2. Castalia Strategic advisors. Estimating WACC for Regulated Utilities in the United States. April 2014.
http://www.castalia-
advisors.com/files/updated_2014/TP_WACC_Sub_Attachment_B_Castalia_Estimating_WACC.pdf
3. DCRA, “Bulk Fuel Revolving Loan Program Annual Report 2014”
4. DCRA, “Bulk Fuel Revolving Loan Program Annual Report 2015”
https://www.commerce.alaska.gov/web/Portals/4/pub/BulkFuelAnnualReport.pdf
5. Dept. of Energy. Energy Investment Partnership: How state and Local Government Are Engaging
Private Capital to Drive Clean Energy Investment. Dec. 2015.
https://energy.gov/sites/prod/files/2016/01/f28/Energy%20Investment%20Partnerships.pdf
6. Gwen Holdman, Dominique Pride, John McGlynn, Amanda Byrd. “Barriers to and Opportunities for
Private Investment in Rural Alaska Energy Projects.” Alaska Center for Energy and Power. December
2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/BarriersReportFinal.pdf?ver
=2016-12-19-124505-280
7. K. Ardani, D. Hillman, and S. Busche. National Renewable Energy Laboratory. “Financing
Opportunities for Renewable Energy Development in Alaska.” April 2013.
http://www.nrel.gov/docs/fy13osti/57491.pdf
8. National Institute of Building Sciences. Financing Small Commercial Building Energy Performance
Upgrades: Challenges and Opportunities.
https://c.ymcdn.com/sites/www.nibs.org/resource/resmgr/CC/CFIRE_CommBldgFinance-Final.pdf
UTILITY MANAGEMENT
1. Alaska Rural Utility Collaborative. “2014 Report on Activities.” https://anthc.org/wp-
content/uploads/2015/12/2014-ARUC-Report-on-Activities-v2_02.09.15_email.pdf
2. Denali Commission Policy. “Rural Alaska Energy Infrastructure Criteria for Sustainability.” 2002.
3. Denali Commission. “Analysis of R&R Accounts as Highlighted in the FY2012 Second Half Semi-
Annual Report to Congress.” June 2013.
4. James Brooks. “Yakutat power sale draws ample opposition.” Juneau Empire. November 18, 2016.
http://juneauempire.com/state/2016-11-18/yakutat-power-sale-draws-ample-opposition
5. James Brooks. “Yakutat sells its power company to statewide cooperative.” Juneau Empire. October
24, 2016. http://m.juneauempire.com/state/2016-10-24/yakutat-sells-its-power-company-
statewide-cooperative#gsc.tab=0
6. James Layne. “Electric Utility Outage Reporting 2003 to 2013.” Presentation. Regulatory Commission
of Alaska. April 22, 2015.
7. Janine Migden-Ostrander. “Technical Conference: Alternative Cost Recovery Mechanisms.”
Presentation to Maryland Public Service Commission. October 20, 2015.
http://www.raponline.org/wp-content/uploads/2016/05/rap-jmo-mdpsc-altcostrecmech-2015-oct-
20.pdf
8. Jim Lazar. “Electricity Regulation in the US: A Guide.” Second Edition. The Regulatory Assistance
Project. 2016. http://www.raponline.org/wp-content/uploads/2016/07/rap-lazar-electricity-
regulation-US-june-2016.pdf
9. John Nichols. “Lessons Learned: Rural water systems & operational efficiency.” Presentation to the
Alaska Rural Energy Conference. April 30, 2013.
http://www.uaf.edu/files/acep/2013_REC_Lessons%20Learned-
Rural%20Water%20Systems%20&%20Operational%20Effciency_John%20Nickels.pdf
February 2017 Resources Page | 251
10. Mark Foster and Ralph Townsend. “Determinants of the Cost of Electricity Service in PCE Eligible
Communities.” January 20, 2017.
http://www.akenergyauthority.org/Portals/0/DNNGallery/uploads/2017/1/23/RuralAlaskaEnergySe
rvicesAlternatives%20final.pdf
11. Office of Inspector General, Denali Commission. Analysis of R&R Accounts as Highlighted in the
FY2012 Second Half Semi-Annual Report to Congress. June 12, 2013. http://oig.denali.gov/wp-
content/uploads/2015/01/SAR-2012-09.pdf
12. Regulatory Commission of Alaska. Order U-15-012(2) Order Denying Request for Expedited
Consideration; Approving Application for Certificate of Public Convenience and Necessity; Approving
Service Area Description, Tariff Sheets, and Power Sales Agreement; Requiring Filing; and Closing
Docket. http://rca.alaska.gov/RCAWeb/ViewFile.aspx?id=69f102f0-4fdb-4475-bfd8-471318c96bff
13. Steve Colt and Mark Foster. “True Cost of Electricity in Rural Alaska and True Cost of Bulk Fuel in
Rural Alaska.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/AKAESTrueCostElec
tricityFuel102616.pdf?ver=2016-10-27-083402-423
14. Steve Colt, Scott Goldsmith, Amy Wiita “Sustainable Utilities in Rural Alaska Effective Management,
Maintenance and Operation of Electric, Water, Sewer, Bulk Fuel, Solid Waste” July 15, 2003.
http://www.iser.uaa.alaska.edu/Home/ResearchAreas/RuralUtilities.htm
15. University of Alaska Center for Economic Development. “Utility Financial Analysis and Benchmarking
Study Draft.” October 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/Utilityfinancialanal
ysisandbenchmarkingstudy.pdf
16. USDA & EPA. “Rural and Small System Guidebook to Sustainable Utility Management.” 2016.
https://www.epa.gov/sustainable-water-infrastructure/rural-and-small-systems-guidebook-
sustainable-utility-management
17. Wesley Loy. “Electric co-op seeks bankruptcy after well cost overruns.” Alaska Dispatch News.
October 16, 2010. https://www.adn.com/alaska-news/article/electric-co-op-seeks-bankruptcy-
after-well-cost-overruns/2010/10/17/
18. Wikipedia. “Used and Useful Principle.” https://en.wikipedia.org/wiki/Used_and_Useful_Principle
POPULATION CHANGE
1. E Lance Howe, Lee Huskey, and Matthew Berman. “Migration in Arctic Alaska: Empirical evidence of
the stepping stones hypothesis.” Migration Studies (2014) 2 (1): 97-
123.doi: 10.1093/migration/mnt017
2. Matt Berman and Eddie Hunsinger, “Energy Cost and Rural Alaska Out-migration,” 2016.
3. Stephanie Martin, Mary Killorin, and Steve Colt, “Fuel Costs, Migration, and Community Viability”,
May 2008. http://www.iser.uaa.alaska.edu/Publications/Fuelcost_viability_final.pdf
4. United States Census Bureau. Table 1. General mobility, by race and Hispanic origin, region, sex, age,
relationship to householder, educational attainment, marital status, nativity, tenure, and poverty
status: 2014 to 2015. http://www.census.gov/data/tables/2015/demo/geographic-mobility/cps-
2015.html
February 2017 Appendix A: Relevant Statutory Language from SB138 Page | 252
APPENDIX A: RELEVANT STATUTORY LANGUAGE FROM SB 138
See http://www.legis.state.ak.us/PDF/28/Bills/SB0138Z.PDF
Sec. 75. The uncodified law of the State of Alaska is amended by adding a new section to
read:
PLAN AND RECOMMENDATIONS TO THE LEGISLATURE ON INFRASTRUCTURE
NEEDED TO DELIVER AFFORDABLE ENERGY TO AREAS IN THE STATE THAT DO NOT
HAVE DIRECT ACCESS TO A NORTH SLOPE NATURAL GAS PIPELINE. (a) The Alaska Energy
Authority, in consultation with the Alaska Gasline Development Corporation, the Alaska Industrial
Development and Export Authority, and the Department of Revenue, shall, after considering the state
energy policy under AS 44.99.115 and sec. 1, ch. 82, SLA 2010, develop a plan for developing
infrastructure to deliver more affordable energy to areas of the state that are not expected to have direct
access to a North Slope natural gas pipeline. The plan must identify ownership options, different energy
sources, including fossil fuels, hydro projects, tidal, and other alternative energy sources, and describe
and recommend the means for generating, delivering, receiving, and storing energy in the most cost-
efficient manner. For those citizens for whom there is no economically viable infrastructure available, the
plan must recommend the means for directly underwriting the energy costs of the citizens to make their
energy costs more affordable. The Alaska Energy Authority may consider the development of regional
energy systems that can receive and store bulk fuel in quantity and distribute that fuel as needed within
the region.
(b) The Alaska Energy Authority, in consultation with the Department of Revenue, shall
recommend a plan for funding the design, development, and construction of the required infrastruct ure
and may identify a source of rent, royalty, income, or tax received by the state that may be appropriated
by the legislature to implement the plan.
(c) The Alaska Energy Authority shall provide the plan and suggested legislation for the design,
development, construction, and financing of the required infrastructure to the legislature before January 1,
2017.
February 2017 Appendix B: Description of AAEM Page | 253
APPENDIX B: DESCRIPTION OF ALASKA AFFORDABLE ENERGY MODEL
Contents
Purpose ..................................................................................................................................................... 254
Data sources for model ............................................................................................................................. 254
Global model assumptions ....................................................................................................................... 256
Forecasts ................................................................................................................................................... 256
Energy demand forecast ....................................................................................................................... 256
Generation forecast .............................................................................................................................. 257
Energy cost forecast .............................................................................................................................. 257
AAEM modules .......................................................................................................................................... 258
Efficiency Modules ................................................................................................................................ 258
Generation Modules ............................................................................................................................. 260
Heating Projects .................................................................................................................................... 263
AAEM distribution, installation, and results ............................................................................................. 266
February 2017 Appendix B: Description of AAEM Page | 254
PURPOSE
The Alaska Affordable Energy Model (AAEM), an AEA-designed model built by the University of Alaska
Fairbanks’ (UAF) Geographic Information Network of Alaska (GINA), is used extensively in the Alaska
Affordable Energy Strategy report to evaluate energy infrastructure opportunities in study-area
communities. The AAEM uses the best data available for each community, including resource
assessments, residential and non-residential building audits, energy consumption information, and
generation infrastructure details. The AAEM integrates known information about communities with
modeled data to gain a deeper understanding of the challenges faced and opportunities available to bring
affordable energy to Alaska’s communities.
The AAEM, a community-based energy model and project evaluation tool, uses the best available
community and/or regional data to:
1. estimate and forecast heating and electricity consumption by sector,
2. compare the ability of energy infrastructure project types (efficiency, renewable energy, fuel
switching) to reduce the cost of energy in communities, and
3. determine the capital investment needed and the resulting energy savings to communities.
The Affordable Energy Model fulfills some of the legislative requirements to “describe and recommend
the means of generating, delivering, receiving, and storing energy in the most cost-efficient manner.” Also
in considering the state energy policy under AS 44.99.115 and sec. 1, ch. 82, SLA 2010, energy efficiency
for residential and non-residential facilities is included as a way to “achieve a 15% increase in energy
efficiency on a per capita basis between 2010 and 2020” and “institute a comprehensive and coordinated
approach to supporting energy efficiency and conservation.”
DATA SOURCES FOR MODEL
The model pulls data from databases, such as the Alaska Energy Data Gateway498 (Gateway); thus, model
results will be updated and expanded to remain current as new data is ingested.
Alaska has a number of existing sources of community-level energy data. The Gateway, a database
maintained by the University of Alaska Anchorage’s Institute for Social and Economic Research through
contracts with AEA, has been the primary repository for Alaska’s energy data. The scope of the Gateway
has increased due to the requirements of the Affordable Energy Model and the data collected through
AEA’s regional planning effort.
The Gateway has electricity data from the state’s Power Cost Equalization (PCE) and the federal Energy
Information Authority (EIA). Data includes generation and sales at varying levels of granularity, depending
on the data source and reporting requirements. The Gateway has residential electric rates reported for
the PCE program and residential and non-residential rates calculated from EIA sales and income reports.
498 Alaska Energy Data Gateway, developed by the Institute of Social and Economic Research, University of Alaska Anchorage, is
supported by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under EPSCoR Award # DE-
SC0004903 (database and web application development), and by Alaska Energy Authority (Renewable Energy Fund data
management and reporting). Database and web hosting is provided by the University of Alaska Fairbanks.
https://akenergygateway.alaska.edu/
February 2017 Appendix B: Description of AAEM Page | 255
To date, there has been no systematic collection of non -residential rates in PCE communities nor any
collection of other fees and/or demand charges.
The Gateway also maintains current and historical heating fuel prices (for heating oil, wood, and propane)
at a local level for more than 200 communities; this data was acquired through surveys performed by the
Alaska Housing Finance Corporation (AHFC) and the state’s Division for Community and Regional Affairs
(DCRA).
Another primary purpose of the Gateway is to store the data from the operational projects funded
through the Renewable Energy Fund (REF). As the best source for renewable energy performance data in
Alaska, the performance of several dozen renewable energy projects is available and will be updated as
more projects are developed and further operational experience is gained.
The US Census, particularly the American Community Survey, is the main source for the model’s
socioeconomic data. The decennial population is supplemented by estimates from the Alaska Department
of Labor and Workforce Development Research and Analysis section on a yearly basis. The Census also
collected data on the number and status of houses: the number inhabited and vacant, rented and owned.
The 5-year ongoing household survey from the American Community Survey (ACS) includes community
and regional estimates for heating fuel usage in residences.499 Because of the margin of error present in
the ACS at the community level in Alaska outside of major population centers for all data sets, regional
estimates are generally used. As one example, the Census Bureau’s estimate for MHI in Lime Village was
$145,313 with a margin of error of plus or minus $266,070 (183%).500
The Alaska Housing Finance Corporation’s Alaska Retrofit Information System (ARIS) is the primary source
of building information in the state, but the data is not publicly available. ARIS houses data for both
residential and non-residential buildings and facilities. The residential data comes from AHFC’s Home
Energy Rebate (HER) program, Weatherization Assistance Program (Wx), and the Building Energy
Efficiency Standard (BEES). The data is gathered on the household level by residential auditors that use
the AkWarm program (AkWarm is a residential building modelin g program specifically built for AHFC).
Little actual residential building consumption data is included in ARIS.
ARIS also includes non-residential building and facility data. Data includes the square footage of buildings,
the building use, some data on the building construction, and occasional data on electricity and/or heating
consumption. Additional building data was gathered from audits performed by the Alaska Native Tribal
Health Consortium energy program, AHFC building audit program, AEA’s Village Energy Efficiency Program
(VEEP), AEA-led regional planning501, AEA’s 2012 End Use Study502, and various other sources.
499 United States Census Bureau. “B25040: House Heating Fuel [10]”. 2008-13 U.S. Census Bureau’s American Community
Survey Office, 2013. January 2015 <http://ftp2.census.gov/>.
500 US Census Bureau. “American Community Survey 2009-2013 5-Year Estimates.” Accessed from Division of Community and
Regional Affairs Community Database Online.
https://www.commerce.alaska.gov/dcra/DCRAExternal/community/Details/5db73dd9-b52c-486a-acf4-a323b8d8f3cf
501 http://www.akenergyauthority.org/Policy/RegionalPlanning
502 http://www.akenergyauthority.org/Content/Efficiency/EndUse/Documents/AlaskaEndUseStudy2012.pdf
February 2017 Appendix B: Description of AAEM Page | 256
Other datasets are included in the description of each of the model’s modules.
GLOBAL MODEL ASSUMPTIONS
The AAEM uses the California Energy Commission’s Total Resource Cost Test, which is agnostic of where
money comes from or where the benefits go.503 It is assumed that when the AkAES legislative directive
states that infrastructure projects should be cost-effective, it means that the present value of the benefits
should outweigh the present value of cost of the project, independent of who is paying for the project or
receiving the benefits. This TRC test does not quantify or include other societal benefits of renewable
energy development.
The model is primarily based on the economic assumptions of the Round 9 Renewable Energy Fund (REF)
project evaluation model, developed by ISER.504 It uses the REF’s discount rate (3%), real dollars, the
assumed economic life of projects, O&M/R&R assumptions, fuel price forecasts, and technology
performance (where applicable).
State energy policy established by sec. 1, ch. 82, SLA 2010 instructs that the “power project fund serve as
the main source of state assistance of energy projects”. As a result, the Alaska Affordable Energy model
is built around the use of project financing (loans) and not grants. The loan terms are based on the
expected life of the project with an initial interest rate set at 5%.
The heating oil price premium, a premium on top of the cost of the forecasted price per gallon for diesel
to the utility, was calculated using an average of the regional differences between the yearly average cost
of heating oil and utility diesel.
The model does not assume any price elasticity for electricity and heating fuels.
Regional cost multipliers were adapted from a 2013 Alaska Department of Education and Early
Development cost estimating manual.505 Insufficient data has been found through analyzing AEA projects
to develop similar regional cost multipliers based on energy projects.
FORECASTS
ENERGY DEMAND FORECAST
Population projections at the community level were developed by a researcher at the University of Alaska
Anchorage Institute of Social and Economic Research (ISER) (unpublished except as part of the AAEM).
The population projections are integral to forecasting future electricity and heating fuel demand. The
future electricity demand, in kilowatt-hours per year (kWh/year), is forecasted by an equation developed
from separate regressions for the residential and non-residential sectors of the actual consumption and
population from 2003-2014 for each individual community. The population projections also impact the
heating fuel forecast by estimating the future residences and consumption in the water/wastewater
503 http://www.energy.ca.gov/pou_reporting/background/metrics.html and http://www.mwalliance.org/node/3032
504 http://www.akenergyauthority.org/Programs/RenewableEnergyFund
505 https://education.alaska.gov/facilities/pdf/cost_model_instructions.pdf
February 2017 Appendix B: Description of AAEM Page | 257
system. The population forecast does not currently affect the estimate of non-residential buildings in the
community, and thus the consumption of heating fuels.
The energy demand forecast was tested by compiling the total heating oil and diesel fuel consumed by
community. In 2016, AEA asked Crowley Maritime Corporation’s Alaska Fuel Sales and Distribution
division to provide feedback on the liquid fuels estimates for communities that they served. Of the
communities that AEA received feedback on, approximately 70 communities, most appeared to be within
a reasonable margin of error (10-20%). The process also allowed AEA to identify some programming and
data bugs that helped to improve the estimates in a few communities.
GENERATION FORECAST
To forecast the generation needed to meet the expected demand, the future line loss (as a percentage of
lost generation) and generation efficiency (in kWh/gallon) are assumed to be an average of the previous
three years’ line loss and generation efficiency, expected to remain constant in the future. For other
generation sources, the future generation is based on an average of the previous three years of reported
generation. This may cause some discrepancies for new renewable energy infrastructure.
In cases where excess hydro or wind capacity available in the community or intertie, the renewable energy
absorbs any growth before diesel is used to supplement any forecasted increase in required generation.
The renewable energy capacity is provided as a data input for each applicable community.
ENERGY COST FORECAST
One of the key aspects of estimating the benefits of projects is in forecasting the fuel prices, either for
what is being displaced or the replacement fuel. Where it is possible, the model retains the fuel price
forecasts from the REF. The utility diesel price forecast is based on the Energy information Authority mid-
price forecast for Brent crude, in the current case, from 2016.506 The community-specific conversion
factors are based on work performed by the Alaska Center for Energy and Power (ACEP).507 A carbon price
has historically been included in the price projection.
A number of entities, including AEA and ISER, have unsuccessfully investigated the mechanisms that lead
to the differences in heating oil costs between communities. Lacking this site-specific information, AEA
used regional averages of the difference between the retail price of heating oil (both #1 and #2) and the
diesel price reported to PCE to forecast the heating oil prices for the AAEM. The unit price of biomass is
assumed to remain flat in real terms based on 2015 vendor prices gathered from the federal Low Income
Heating Assistance Program (LIHEAP).
The retail electricity price forecast is developed by using the diesel price forecast, and assumes that the
status quo operation expenses of the utility remains constant in real dollars, and that the operational cost
506 Real Petroleum Prices Crude Oil Brent Spot (Case Reference case),
http://www.eia.gov/forecasts/aeo/data/browser/#/?id=12-AEO2015
507 Dominique Pride, Matthew Snodgrass, Antony Scott. “Correlating Community Specific Rural Diesel Fuel Prices with Published
Indices of Crude Oil Prices, and Potential Price Projection Applications” June 2015.
http://www.akenergyauthority.org/Content/Programs/RenewableEnergyFund/Documents/Round%209/RuralFuelModelReport
FinalDraft.pdf
February 2017 Appendix B: Description of AAEM Page | 258
is captured in an average of the observed difference between the retail rate and the cost of power for the
previous three years.
Future inflation is based on a 2.4% increase in the Consumer Price Index (CPI), which mirrors the REF
Evaluation Model.
AAEM MODULES
These modules use forecasts for unit prices, population, generation, and consumption. Individual
modules include other key data inputs and key assumptions to develop the key outputs.
Comparison is made primarily as existing grant-funded infrastructure to new debt-financed projects. The
benefits are generally based on the savings in fuel costs.
EFFICIENCY MODULES
RESIDENTIAL ENERGY EFFICIENCY IMPROVEMENTS
This module estimates the potential improvements to heating efficiency of residential buildings (homes).
Consumption and savings are based on the number of units that have not been retrofit, the performance
improvements as a percentage of the pre-retrofit consumption, and the forecasted price of offset heating
fuels. The cost to retrofit each home is also calculated.
KEY DATA INPUTS
1. ARIS AkWarm data for every community. Includes data from the Weatherization Assistance
program, Home Energy Rebate Program, and Building Energy Efficiency Standard (BEES)
compliant residences508
2. ACS residential heat source509
3. Community population and population forecast510
KEY OUTPUTS
1. Residential consumption of heating fuels
a. Forecasted volume of heating fuels consumed
b. Forecasted cost of heating fuels
2. Economic analysis of the potential cost effectiveness of residential efficiency to reduce heating
costs
KEY ASSUMPTIONS
1. Economic life of efficiency retrofit: 15 years
2. Population and households—maintain number of people per household
3. Unknown residential buildings in a community are most similar to the average of pre-retrofit
buildings
508 ARIS is not a publicly available database
509 United States Census Bureau. “B25040: House Heating Fuel [10]”. 2008-13 U.S. Census Bureau’s American Community
Survey Office, 2013. January 2015 <http://ftp2.census.gov/>.
510 Population forecasted by Mouhcine Guettabi of the Institute of Social and Economic Research for the AkAES in 2016.
February 2017 Appendix B: Description of AAEM Page | 259
4. Savings from weatherization based on average community savings, if it is statistically significant,
or the regional average
5. Unit cost—$11,000 modified by a regional multiplier
NON-RESIDENTIAL ENERGY EFFICIENCY IMPROVEMENTS
This module estimates potential improvements in heating and electrical efficiency to non-residential
buildings (commercial, education, health care, etc.). Consumption and savings are based on estimated
square footage per building that may be retrofit and prices of fuels (electricity, biomass, diesel, etc.). The
cost to retrofit each non-residential building is also calculated.
KEY DATA INPUTS
1. Non-residential building data (Sources: ARIS, ANTHC, End Use Study, regional plans, municipal
and borough tax assessors, others)
a. Available data was not consistent for all buildings, but could include the building use,
square footage, electricity consumption, and/or heating fuels consumption
b. Any building audits in the study area were included
2. Heating degree days for all communities
KEY OUTPUTS
1. Non-residential consumption of electricity and heating fuels
a. Forecasted volume of heating fuels (used in other modules) for non-residential buildings
b. Forecasted volume of electricity consumed for non-residential buildings
c. Forecasted cost of heating fuels for non-residential buildings
d. Forecasted cost of electricity for non-residential buildings
2. Economic analysis of module
KEY ASSUMPTIONS
1. Economic life of energy retrofit: 15 years
2. Population changes will not change the number or type of buildings or the consumption in non-
residential buildings
3. Assume that heating oil is the only fuel used for heating except if natural gas is available in
community
4. Savings in consumption
a. Electricity—28%
b. Heat—28%
5. Unit cost--$7/square foot, scaled by regional multiplier
6. If building size, electricity, and/or heating fuel consumption is not known, averages by building
type and community size are assumed.
7. Heating consumption estimates are scaled by heating degree days in community relative to
average that created dataset
WATER AND WASTEWATER EFFICIENCY IMPROVEMENTS
This module estimates potential improvements in heating and electrical efficiency to water and
wastewater systems. Consumption and savings are calculated based on system type, population, and
February 2017 Appendix B: Description of AAEM Page | 260
heating degree days per year for a community. Project costs are based on audits, or estimated by the
community size.
KEY DATA INPUTS
1. Reported consumption data from ARIS, Alaska Native Tribal Health Consortium (ANTHC), the
Alaska Rural Utility Collaboration (ARUC), and the 2012 AEA-funded End Use Study
2. Approximately 60 audits of water/wastewater systems are included from ANTHC
3. The type of water/wastewater system is from the Division of Community and Regional Affairs
Community Database Online.
4. Heating degree days for each community
KEY OUTPUTS
1. Heating and electricity consumption for the water/wastewater system
2. Economic analysis of module
KEY ASSUMPTIONS
1. Economic life of efficiency improvements: 15 years
2. If the electricity and heating fuels consumption is not known, the electricity and heating oil
consumption is estimated based on the community size, the local heating degree days, and the
type of water/wastewater system
3. Savings 25% for electricity and 35% for heating fuels
4. An estimated capital cost based on the number of people in the community ($400-650/person)
GENERATION MODULES
DIESEL EFFICIENCY IMPROVEMENTS
This module estimates the potential reduction in diesel fuel use from improvements to the efficiency of a
community's diesel generation systems. Financial savings are from an assumed decrease in diesel oil used
in generation. Costs of the improvements are based on the assumed capacity of the improved system.
KEY INPUTS
1. Electric generation and consumption data in kWh
2. Generation efficiency and line loss
KEY OUTPUTS
1. Economic analysis
KEY ASSUMPTIONS
1. Economic life of improvements: 30 years
2. 10% savings in fuel over the economic life of the powerhouse
3. Generation capacity needed is based on a five times multiplier of the average community load
4. The estimated unit cost is based on the assumed generation capacity. The equation is derived
from the costs of AEA- and Denali Commission-funded rural powerhouses
February 2017 Appendix B: Description of AAEM Page | 261
WIND POWER INFRASTRUCTURE
This module estimates potential reduction in diesel fuel use from the installation of wind power systems.
Proposed wind generation is from existing projects or estimated from a proposed capacity. Financial
savings result from decrease in diesel used in generation due to wind systems. The cost to build or improve
wind infrastructure are also estimated.
KEY DATA INPUTS
1. If available, data from Renewable Energy Fund projects (cost, generation, secondary loads) is
used
a. If no project-specific data is available, the highest wind class within one mile of
community/intertie is used. Data is from the NREL wind map511 or local anemometers
KEY OUTPUTS
1. Generation in kWh per year
2. Economic analysis of module
KEY ASSUMPTIONS
1. Economic life of infrastructure: 20 years
2. Generation capacity is 150% of the average community/intertie load
3. The capacity factor per wind class
4. 15% of the electricity generated is expected to be excess
5. If the existing powerhouse has heat recovery installed, the loss of waste heat from the diesel
generator is included.
6. Capital cost is based on work performed by ACEP512
7. Operational cost is expected to be 1% of the capital cost
SOLAR POWER INFRASTRUCTURE
This module estimates the potential reduction in diesel fuel use from installation or improvement of
photovoltaic (PV) solar generation systems. Proposed solar generation is based on an estimated capacity
per community. Costs associated with the installation of panels and necessary power-house
improvements are also estimated.
KEY DATA INPUTS
1. Expected generation from a 10-kW solar panel PVWatts513 was collected for 30 communities
with solar data. Communities without data substituted data from the nearest community
KEY OUTPUTS
1. Generation in kWh
511 Available from Alaska Energy Data Inventory (http://www.akenergyinventory.org/)
512 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
513 http://pvwatts.nrel.gov/index.php
February 2017 Appendix B: Description of AAEM Page | 262
2. Economic analysis of module
KEY ASSUMPTIONS
1. Economic life: 20 years
2. Performance degradation of 1% per year514
3. Generation size limited to 15% of the average load515
4. 15% of the electricity generated is expected to be excess
5. Capital cost is $6,000/kW, which is currently optimistic based on work performed by ACEP516
6. Operational cost is expected to be 1% of the capital cost
HYDROPOWER INFRASTRUCTURE
This module estimates the potential reduction in diesel fuel use from installation of hydropower projects.
Proposed hydro generation is from proposed projects around the state. Financial savings result from
decrease in diesel used in generation due to hydropower projects. Cost estimates for building hydropower
infrastructure are also calculated.
KEY DATA INPUTS
1. When available, Renewable Energy Fund pre-construction project data is included for cost and
generation
2. Data collected for over 400 projects through US Army Corps of Engineers cataloging of
hydropower studies
a. Include some modeling based on regional output and costs
KEY OUTPUTS
1. Generation in kWh
2. Economic analysis of module
KEY ASSUMPTIONS
1. Economic life of hydropower infrastructure: 50 years
2. 15% of the electricity generated is expected to be excess
3. Operational cost is expected to be 1% of the capital cost
TRANSMISSION AND INTERTIE INFRASTRUCTURE
This module estimates the potential reduction in diesel fuel use from installation of transmission lines to
another community with better generation infrastructure. Savings result from difference in generation
514 Dirk Jordan and Sarah Kurtz. “Photovoltaic Degradation Rates — An Analytical Review.” 2012.
http://www.nrel.gov/docs/fy12osti/51664.pdf
515 Based on: Mueller Stoffels M 2014 Adding PV Capacity – Initial Assessment And Recommendations For Galena Alaska,
available at: http://acep.uaf.edu/media/127271/Mueller-Stoffels-M-2014-Adding-PV-Capacity-%E2%80%93-Initial-
Assessment-and-Recommendations-for-Galena-Alaska.pdf
516 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 Appendix B: Description of AAEM Page | 263
costs between communities. The costs of new transmission lines are estimated based on distances
between communities.
KEY DATA INPUTS
1. Distance to nearest community with lowest cost power
KEY OUTPUTS
1. Economic analysis of the module
KEY ASSUMPTIONS
1. Economic life of infrastructure: 30 years
2. Generation efficiency remains constant
3. Unit cost of transmission lines of $200,000 per mile with road access and $500,000/mile without
a road.517
HEATING PROJECTS
Except for heat recovery projects, which uses data only from previous pre-construction studies, the
heating projects share a common method for estimating the required capacity of the heating appliances.
The estimated heating oil consumption for non-residential buildings is apportioned by binned weather
data by month, assuming there is a direct relationship between the heating degree days and the amount
of fuel consumed in the month. The required sizing of the heating appliance(s) (in MMBtu/hour) is
estimated by converting the gallons of heating oil consumed in the coldest month into energy equivalent
per hour (Btu/hour). This assumes that a secondary heat source, generally heating oil, is available to
supply the peak load.
BIOMASS FOR HEAT (CORDWOOD) INFRASTRUCTURE
This module estimates the potential reduction in heating fuel use from installation cordwood boilers in
non-residential buildings. Reduction in fuel used is based on estimated output of hypothetical boilers.
Savings result from difference in fuel prices between diesel and cordwood. The costs of the biomass
projects are estimated from number of installed boilers and their size. Fuel use from improvements to
heat recovery systems is based on existing projects. Reduction of heating fuel used results from improved
recovery of heat during electrical generation
KEY DATA INPUTS
1. A Boolean on if sufficient biomass available within a 5-mile radius
2. Data from non-residential model on heating oil consumption
KEY ASSUMPTIONS
1. General assumptions for heating projects, as explained above
2. Economic life of infrastructure: 20 years
517 Alaska Center for Energy and Power. “Documentation of Alaska-Specific Technology Development Needs in support of the
Alaska Affordable Energy Strategy.” 2016.
http://www.akenergyauthority.org/Portals/0/Policy/AKaES/Documents/Reports/TechnologyDevelopmentNeeds.pdf?ver=2016-
08-08-152005-117
February 2017 Appendix B: Description of AAEM Page | 264
3. 30% of square footage of non-residential buildings are included
4. Unit cost is based on AEA analysis of REF-funded projects
KEY OUTPUTS
1. Economic analysis of the module
2. Consumption of biomass
BIOMASS FOR HEAT (PELLET) INFRASTRUCTURE
This module estimates the potential reduction in heating fuel use from installation of pellet boilers in non-
residential buildings. Reduction in fuel used is based on estimated output of hypothetical boiler. Savings
result from difference in fuel prices between diesel and pellets. The costs of the biomass projects are
estimated from number of installed boilers and their size. Communities must have access to road
system.
KEY DATA INPUTS
1. A Boolean on if the community is on the road system or marine highway system
2. Data from non-residential model on heating oil consumption
KEY ASSUMPTIONS
1. General assumptions for heating projects, as explained above
2. Economic life of infrastructure: 20 years
3. 30% of square footage of non-residential buildings are included
4. Unit cost is based on AEA analysis of REF-funded projects
KEY OUTPUTS
1. Economic analysis of the module
2. Consumption of biomass
RESIDENTIAL AIR SOURCE HEAT PUMP (ASHP) INFRASTRUCTURE
This module estimate the potential reduction in heating fuel use from installation of Air Source Heat
Pumps in residential buildings. Reduction in fuel used is based on coefficient of power in hypothetical
ASHP system and heat energy produced per year. Savings result from differential heating fuel costs and
ASHP operation costs. The costs of the ASHP infrastructure projects are based on the number of homes
in the community and the cost of AHSP systems themselves.
KEY DATA INPUTS
1. Input from Residential efficiency module
2. ACS residential heat source
KEY ASSUMPTIONS
1. General assumptions for heating projects, as explained above
2. Economic life of infrastructure: 20 years
3. Coefficient of performance is dependent on the outdoor temperature
February 2017 Appendix B: Description of AAEM Page | 265
4. Output in Btu/hour is dependent on the outdoor temperature518
5. Electricity prices do not change with increased demand
6. No new generation is needed to power ASHPs
7. Unit cost based on national averages519, modified by Alaska regional multipliers
KEY OUTPUTS
1. Increase in electricity consumption
2. Excess generation capacity necessary to power ASHPs
3. Economic analysis of the module
NON-RESIDENTIAL AIR SOURCE HEAT PUMP (ASHP) INFRASTRUCTURE
This model estimates the potential reduction in heating fuel use from installation of Air Source Heat
Pumps in Non-residential buildings. Reduction in fuel used is based on coefficient of power in hypothetical
ASHP system and heat energy produced per year. Savings result from differential heating fuel costs and
ASHP operation costs. The cost of the ASHP infrastructure projects are based on the number of non-
residential buildings in the community and the cost of AHSP systems themselves
KEY DATA INPUTS
1. Input from Non-residential efficiency module
KEY ASSUMPTIONS
1. General assumptions for heating projects, as explained above
2. Economic life of infrastructure: 20 years
3. Coefficient of performance is dependent on the outdoor temperature
4. Output in Btu/hour is dependent on the outdoor temperature520
5. Electricity prices do not change with increased demand
6. No new generation is needed to power ASHPs
7. Unit cost based on national averages521, modified by Alaska regional multipliers
KEY OUTPUTS
1. Increase in electricity consumption
2. Excess generation capacity necessary to power ASHPs
3. Economic analysis of the module
518 Richard Faesy & Jim Grevatt, Energy Futures Group, Brian McCowan & Katie Champagne, Energy & Resource Solutions,
Ductless Heat Pump Meta-Study: Final Report Presentation, November 13, 2014.
519 Faesy & Grevatt, 2014.
520 Richard Faesy & Jim Grevatt, Energy Futures Group, Brian McCowan & Katie Champagne, Energy & Resource Solutions,
Ductless Heat Pump Meta-Study: Final Report Presentation, November 13, 2014.
521 Energy Information Authority. “Residential & Commercial Building Technologies Appendix A.” 2016.
https://www.eia.gov/analysis/studies/buildings/equipcosts/pdf/appendix-a.pdf
February 2017 Appendix B: Description of AAEM Page | 266
HEAT RECOVERY INFRASTRUCTURE
Insufficient data was available on a community-level to model the costs and benefits of heat recovery.
Because of this, the module only includes analysis of projects that have pre-construction studies.
KEY DATA INPUTS
1. Pre-construction project data from the Renewable Energy Fund and the Rural Power System
Upgrade program
KEY OUTPUTS
1. Economic analysis of module
AAEM DISTRIBUTION, INSTALLATION, AND RESULTS
AAEM is built in the Python programming language and is platform independent. The model is stored in
a Git repository hosted at GitHub. As of January 2017, the AAEM is run from a command line interface
(CLI), uses input data that is packaged with the model, and is installed locally. Users will need to use a
Mac/Unix, Windows, or Linux terminal window and a familiarity with CLIs may be helpful.
Visualizations of the model output, and further documentation are available from
http://www.akenergyinventory.org/energymodel.
Please contact AEA for the latest version of the model, accompanying input data, and model output.
Neil McMahon, Program Manager: Energy Planning
907-771-3981, nmcmahon@aidea.org