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Galena REF Attachments
City of Galena Renewable Energy Fund Application Summary of Attachments Attachment Page Capital Budget Summary 2 Team Resumes 3 Aerial Maps for Siting Options 9 Letters of Support 10 •Sustainable Energy for Galena Alaska (SEGA) •Tanana Chiefs Conference •United States Fish and Wildlife – Galena office •Gana-A’Yoo, Limited •Galena School District •Ruby Marine Alaska Native Renewable Industries’ Price Quote 1 Alaska Native Renewable Industries’ Production Estimate 1 Solar Energy Prospecting in Remote Alaska 2 Coffman Engineers Feasibility Study 5 National Renewable Energy Laboratory Feasibility Study 6 USDA High Energy Cost Award and Extension Letter 10 B/C Ratio Model – Separate Excel file Tesla Feasibility Study – Separate PDF Galena Community Scale Solar PV and Battery Project Capital Budget Summary Budget By Project Phase Total Budget AEA HECG Unidentified or Cost Savings In-kind Site Selection/Engineering 370,000$ 370,000$ 3,000$ Solar Panels 800,000$ 800,000$ Solar Balance of Plant 1,000,000$ 1,000,000$ Solar Install 750,000$ 750,000$ Battery Equipment 1,000,000$ 1,000,000$ Battery Install 460,000$ 460,000$ Commissioning 80,000$ 40,000$ 40,000$ Project Management/Procurement 40,000$ 40,000$ Grant Management 6,000$ 3,000$ Total 4,506,000$ 2,000,000$ 1,500,000$ 1,000,000$ 6,000$ City of Galena REF Capital Budget 2 Shanda Huntington City Manager /City Clerk I was hired in July 2008 as City Clerk and in February 2014 I was promoted to City Manager. My primary duties included: Prepare the annual budge and submit estimates to the City Council for approval. Monitor the budge and report to the City Council on the financial condition and the needs of the municipality. Prepare annual financial and administrative reports. Develop capital and short range project plans, and prioritizes and assign projects to optimize budget funds. Assure the financial soundness and integrity of the city to assure its capability to meet commitments and to maximize the delivery of services to citizens. Carmen Jackson (CPA) has been working for the City since 2015 Her primary duties include: o Provide training to staff on accrual accounting o Provide training to staff on QuickBooks software o Review or complete various business operational documents including : 1. Grant applications 2. Budgets 3. Employment forms 4. Employment related benefits 5. Insurance documents Audit preparation services of reviewing and adjusting the general ledger in accordance with accounting principles generally accepted in the USA on a modified accrual basis of accounting as governmental fund financial statements are reported and presented. 3 5 6 8 Potential Solar PV Array Sites in Galena Site #1 Site #2 9 10 122 1st Avenue Fairbanks, AK 99701 907-452-8251 www.tananachiefs.org January 6th 2022 Alaska Energy Authority Renewable Energy Fund 813 West Northern Lights Blvd. Anchorage, AK 99503 RE: City of Galena REF Application for Solar Photovoltaic and Battery Construction Dear Alaska Energy Authority: Please accept this letter of support from Tanana Chiefs Conference (TCC) regarding the City of Galena’s application to Round 14 of the AEA Renewable Energy Fund for final design and construction of a solar photovoltaic (PV) and battery hybrid system. The proposed system— approximately 1.2 MW of solar PV and 800 kWh of battery storage—would result in substantial fuel and cost savings for the community and provide for over 600 hours of diesel-off operation and save about 70,000 gallons of fuel annually. TCC has worked extensively with the community in Galena—both the Louden Tribe and the City of Galena—on numerous energy-related activities. These projects include their biomass and district heating project, extensive energy efficiency upgrades through the US Department of Energy’s Remote Alaskan Communities Energy Efficiency (RACEE) program, various solar energy projects, and powerplant upgrades to replace outdated switchgear and diesel gen-sets funded through the EPA DERA program and a loan from AEA. The AEA REF project described here is a logical and necessary progression of these ongoing energy improvements being made by the community to enhance energy security and save substantial amounts of diesel fuel. Tanana Chiefs Conference is the inter-tribal consortium representing 37 federally recognized tribes across Alaska’s interior. For the past 40 years, TCC has been a voice advocating for the priorities of interior villages and providing essential technical assistance to implement communities’ visions. Our program has significant and specialized experience working with rural energy projects in this region including assisting communities with several EPA DERA projects and solar PV design-builds over the past 8 years. With this letter we commit to providing technical assistance to Galena and help with the proposed solar PV, battery project. Galena is setting the standard in rural Alaska for cooperation among stakeholders as well as innovative energy projects that improve the local economy, enhance energy security and resiliency. As such, we strongly support this project. Sincerely, Dave Messier TCC Rural Energy Coordinator Dave.pm@tananachiefs.org 11 12 13 GALENA CITY SCHOOL DISTRICT P.O. Box 299 GALENA, ALASKA 99741 PHONE (907) 656-1205 FAX (907) 656-1368 SUPERINTENDENT Jim Merriner January 15, 2022 Alaska Energy Authority Renewable Energy Fund 813 West Northern Lights Blvd Anchorage, AK 99503 Re: Support Letter for City of Galena Solar Photovoltaic and Battery Energy Storage System Project Application Dear Alaska Energy Authority: This letter is to express the Galena City School District’s confidence and support for the City of Galena in its application to the Renewable Energy Fund program to complete final design and construction of an approximately 1.2 MW solar PV and 800 kWh battery energy storage system. The Galena City School District (GCSD) has participated in many Solar Committee meetings in support of this project. Our school cooperates with the City on many levels and maintains dozens of buildings and facilities in Galena for both the local school and the boarding school which serves students from many communities throughout Alaska. Many of our staff and teachers are long-term residents of Galena and are strong supporters of the community. It benefits GCSD tremendously to have a reliable, stable, and affordable electric utility. This project should benefit us all by increasing the long-term sustainability of the community and the utility. As one of the City’s largest customers, we support this type of infrastructure improvement. AEA's support for this project will further enhance the overall community effort. We sincerely hope that AEA can continue to contribute to our community’s success by partnering with Galena on this project. Thank you for the opportunity to express GCSD’s full support for the Galena Sewer Repair Project. Please feel free to contact me at 907-656-1205 if you have any questions. Respectfully yours, Jim Merriner, GCSD Superintendent Email: jim.merriner@galenanet.com 14 15 PO Box 33 Huslia, Alaska 99746 Phone: 907-829-2248 edwin@anr-industries.com January 11, 2022 City of Galena PO Box 149 Galena, Alaska 99741 Dear Shanda: Happy new year 2022! I hope 2021 was a safe and successful year for you and the City of Galena. I wanted to take some time to introduce both myself and my organization. My name is Edwin Bifelt and I am the Founder/CEO of Alaska Native Renewable Industries, LLC (ANRI). We are an Alaska licensed General Contractor (GC license # 135016) focused on EPC (engineering, procurement and construction) of utility-scale Solar PV + Battery Energy Storage System (BESS) projects in rural Alaska and U.S. Indian Country. ANRI has designed and installed the 3 largest Solar PV systems in Rural Alaska: • 2021: Shungnak 223.5 kW Solar PV Ground Mount + 384 kWh Lithium-Ion Battery Storage • 2020: Kotzebue 576 kW Solar PV Ground Mount (2nd largest Solar PV project in Alaska) • 2019: Hughes 120 kW Solar PV Ground Mount Our goal for 2022 is to increase our project sizes into the megawatt (MW) range. Our solar PV arrays are very scalable so we can design and install projects ranging from 100 kW – 10 MW. 16 2 Some rural Alaska communities have the highest electricity rates in the U.S. ANRI designs and installs ground-mount solar PV arrays and Battery Energy Storage Systems (BESS), lowering the operating costs of utilities and retail electricity rates. Based on our research, • The cost of diesel to Galena is about $1.1 million a year (430,000+ gallons based on 2020 PCE report) • ANRI can work with the city to help lower these costs by designing & installing Solar PV systems that will save the city money for the next 25-30 years. • Solar PV + Battery Storage can possibly allow the communities power plants to be 'diesels off' in spring/summer months Attached please find some early-stage preliminary feasibility design concepts that we have drawn up for the community of Galena. Attached you will find material about our company and below are links to news articles about our recent projects. Kotzebue 576 kW Solar PV Project https://www.alaskasnewssource.com/content/news/Largest-state-rural-solar-project-almost-finished- in-Kotzebue-571456471.html http://kotz.org/2020/06/23/states-largest-rural-solar-project-nears-completion-in-kotzebue/ Shungnak & Kobuk 223.5 kW Solar PV & Battery Storage Projects https://www.alaskapublic.org/2020/12/16/solar-project-in-northwest-arctic-villages-set-to-break- ground-next-spring/ Hughes 120 kW Solar PV Project https://www.energy.gov/indianenergy/articles/can-solar-work-alaska-hughes-village-says-yes If you need any additional info please contact me anytime, and we would be excited to assist the City of Galena with renewable energy in 2022 and beyond! Best Regards, Edwin Bifelt, Founder/CEO - ANRI 17 3 Attachment 1: City of Galena Galena, Alaska Draft Design Concept Below you will find information on an early-stage design concept we have put together for the community of Galena, Alaska as well as a cost proposal. For this draft we have sized a 1.105 (kW) DC array with the following design characteristics. Total estimated project cost is $4,495,050.92. With current global logistical supply fluctuations, this quote will be valid for 30 days. • 1.105 MW DC o 12 sub-arrays at 92.15 kilowatts (kW) each o 485-Watt BiFacial Solar Panels (or similar) o 190 solar panels per sub-array o 2,280 solar panels total o (fencing not included) • 900 kW AC • 6 SMA Sunny Highpower Peak3 (3-phase) 150 kW string inverters • Construction of an inverter and battery building • 800 kWh of Lithium-Ion Battery Energy Storage System • Estimated 1,145,000 kWh (1.145 GWh) of energy production (see included Helioscope production report) • 20-25% renewable energy power generation • Would be the 2nd largest solar project in the State of Alaska! Figure 1. Side-view of potential 1.105 MW Galena project 18 4 Figure 2. Top view of potential 1.105 MW Galena project. Figure 3. 576 kW Solar project completed by ANRI in 2020 in Kotzebue, Alaska (for Kotzebue Electric Association). 19 Annual Production Report produced by Edwin Bifelt © 2022 Folsom Labs 1/2 January 12, 2022kWhJanFebMarAprMayJunJulAugSepOctNovDec 0 50k 100k 150k 200k Shading: 3.7%Shading: 3.7% Reflection: 3.0%Reflection: 3.0% Soiling: 2.0%Soiling: 2.0% Irradiance: 1.2%Irradiance: 1.2% Mismatch: 3.5%Mismatch: 3.5% Wiring: 0.3%Wiring: 0.3% Clipping: 0.0%Clipping: 0.0% Inverters: 1.0%Inverters: 1.0% AC System: 0.5%AC System: 0.5% 20 Annual Production Report produced by Edwin Bifelt © 2022 Folsom Labs 2/2 January 12, 2022 21 Solar Energy Prospecting in Remote Alaska An Economic Analysis of Solar Photovoltaics in the Last Frontier State by Paul Schwabe, National Renewable Energy Laboratory U.S. Department of Energy | Office of Indian Energy 1000 Independence Ave. SW, Washington DC 20585 | 202-586-1272 energy.gov/indianenergy | indianenergy@hq.doe.gov 22 Solar Energy Prospecting in Remote Alaska ii NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available electronically at SciTech Connect http:/www.osti.gov/scitech Available for a processing fee to U.S. Department of Energy and its contractors, in paper, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831-0062 OSTI http://www.osti.gov Phone: 865.576.8401 Fax: 865.576.5728 Email: reports@osti.gov Available for sale to the public, in paper, from: U.S. Department of Commerce National Technical Information Service 5301 Shawnee Road Alexandra, VA 22312 NTIS http://www.ntis.gov Phone: 800.553.6847 or 703.605.6000 Fax: 703.605.6900 Email: orders@ntis.gov energy.gov/indianenergy | indianenergy@hq.doe.gov DOE/IE-0040 • February 2016 Cover photo from Alamy EPC220. Credit to Design Pics Inc / Alamy Stock Photo. 23 Solar Energy Prospecting in Remote Alaska iii Acknowledgements This work is made possible through support from the U.S. Department of Energy’s Office of Indian Energy Policy and Programs. The author would like to thank Christopher Deschene, Givey Kochanowski and Douglas Maccourt for their support of this work. The author would also like to thank the following reviewers for their insightful review comments: Robert Bensin of Bering Straits Development Company; Brian Hirsch of Deerstone Consulting; David Lockard of Alaska Energy Authority; Ingemar Mathiasson of Northwest Arctic Borough; David Pelunis-Messier of Tanana Chiefs Conference; and Erin Whitney of Alaska Center for Energy and Power. The author also wishes to thank Elizabeth Doris, Sherry Stout, and Jared Temanson of the National Renewable Energy Laboratory (NREL) for their strategic guidance throughout this effort as well as Jeffrey Logan and David Mooney, of NREL, for their insightful review of the document. The author is grateful for the technical editing of Heidi Blakley, Karen Petersen, and Rachel Sullivan of NREL. Finally the author also wishes to thank Jared Wiedmeyer for assistance with development of the analytical model and Pilar Thomas for her guidance and support early in this work. The author is solely responsible for any remaining errors or omissions. 24 Solar Energy Prospecting in Remote Alaska iv List of Acronyms AEA Alaska Energy Authority Btu British thermal unit kW kilowatt kWh kilowatt-hour LCOE levelized cost of energy m2 square meter MW megawatt NREL National Renewable Energy Laboratory O&M operations and maintenance PCE Power Cost Equalization PV photovoltaic W watt 25 Solar Energy Prospecting in Remote Alaska v Table of Contents Introduction ..................................................................................................................................... 1 Analysis Description and Limitations ............................................................................................ 7 Analysis Limitations ........................................................................................................................ 8 Data Input Assumptions: Diesel Generation Costs, Solar Costs, and Solar Resource Estimates ............................................................................................................................... 11 Input Parameters for Diesel Generation Costs .......................................................................... 11 Input Parameters for Solar Electricity Generation ..................................................................... 13 Summary of Input Assumptions .................................................................................................. 17 Analysis Results ........................................................................................................................... 20 Conclusion ................................................................................................................................... 22 References ................................................................................................................................... 23 Appendix A. Model Overview and Description ........................................................................... 27 Appendix B. Levelized Cost of Energy Results ........................................................................... 28 26 Solar Energy Prospecting in Remote Alaska vi List of Figures Figure 1. Solar resource comparison of Alaska and Germany .................................................... 2 Figure 2. Annual solar production percentage across four regions in Alaska by month ........... 3 Figure 3. Solar PV installations at water treatment facilities in the remote villages of Ambler, Shungnak, Deering, and Kobuk, Alaska ................................................................... 5 Figure 4. The seasonal sun paths of Kotzebue, Alaska, and Denver, Colorado .......................... Figure 5. Villages included in solar analysis ................................................................................. 7 Figure 6. PV Installations in Nome and Galena .............................................................................. Figure 7. Average wholesale diesel prices in $/gal for the 11 villages tested in 2013 and 2014 ............................................................................................................................... 12 Figure 8. Screenshot and callout of diesel fuel purchases in Anaktuvuk Pass, Alaska ......... 13 Figure 9. PVWatts solar resource estimate tool screenshot for Adak, Alaska ........................ 14 Figure 10. PVWatts solar resource estimate tool for a 100-kW PV system in Adak, Alaska .. 15 Figure 11. Indexed diesel and solar PV prices from 2002 to 2015 ............................................. Figure 12. Servicing a PV system in remote Alaska .................................................................. 17 Figure 13. Cost of electricity comparison between solar PV and diesel generation .............. 21 Figure 14. Schematic of LCOE model used in this analysis ..................................................... 27 List of Tables Table 1. Cost Estimates for a 100-kW PV System .................................................................... 17 Table 2. Annual Solar Energy Estimates .................................................................................... 18 Table 3. Wholesale Diesel Fuel Costs for Electricity Generation ............................................. 19 Table 4. Solar PV LCOE Modeling Results ................................................................................. 28 27 Solar Energy Prospecting in Remote Alaska 1 Introduction Exploitation and utilization of energy resources within the state of Alaska has predominantly and historically centered on its abundance of fossil-fuel deposits including oil, natural gas, and coal. Within the last decade, however, renewable energy technologies have been deployed across the state for both demonstration purposes and commercial ventures (REAP 2016). This diversification of energy sources has been driven from at least three primary factors: (1) the economic exposure of many Alaskan communities to oil price fluctuations and other petroleum market influences (2) technological advancements and reductions in the cost of renewable energy equipment, and (3) efforts to improve self-sufficiency for remote Alaskan communities. Due to these factors and more, renewable energy resources are increasingly being considered to meet Alaska’s energy needs (Foster et al. 2013). Renewable energy technologies used in Alaska have included small and large hydroelectric facilities, utility- scale and distributed wind generation, geothermal and air heat pumps, and woody biomass for electricity and heating (REAP 2016, CCHRC 2016). In addition to these endemic natural resources, a previously dismissed but pervasive form of renewable energy is also increasingly being analyzed and deployed in Alaska: solar electricity generated from photovoltaic (PV) panels. The lack of historical solar energy development in Alaska is due to a multitude of factors, but not surprisingly starts with one fundamental problem: minimal to no sunlight in the winter months, particularly for the northern latitudes. Of course, Alaska also experiences prolonged and sunlight rich summer days, but many of the biggest energy needs arise during the cold and dark months of winter. Despite this seemingly obvious barrier for solar electricity in Alaska, upon deeper examination there are several factors that may support the deployment of solar energy in particular locations across the state. First, Alaska is an immense state with a large geographic range along both the north-to-south and east-to-west directions. Many Alaskans will proudly and dryly note that if one was to hypothetically cut the state into two, Texas would be only the third largest state in the Union. This expansive and diverse geographic range means that there are significant differences in both the amount and seasonal variation of the solar resource across the state. Additionally many of the meteorological conditions experienced in certain regions of Alaska can actually be beneficial to solar energy production, including low ambient temperatures that improve the efficiency of solar modules and the reflectivity of sunlight off of snow cover on the ground. As shown in Figure 1, the solar resource (i.e., the amount of solar insolation received in kilowatt-hours (kWh)/square meters (m2)/day) in some regions of Alaska is at-least comparable to that of Germany, which leads the world in PV installations with more than 38,500 megawatts (MW) of solar installed as of October 2015 (Wirth 2015).1 1 To put 38,500 MW in perspective, with a population of roughly 80 million, Germany has installed approximately 480 watts (W) of PV per capita, or roughly two average-sized 250-W PV panels for every person in the country. 28 Solar Energy Prospecting in Remote Alaska 2 Figure 1. Solar resource comparison of Alaska and Germany 2 Source: Billy J. Roberts, National Renewable Energy Laboratory (NREL) Second, both the expected monthly solar production and the seasonal load profile of communities can vary significantly across Alaska, meaning some communities may be better suited for solar production than others. Figure 2 shows the percentage of expected annual solar production by month across the Arctic, Interior, Southwest, and Southeast geographic regions of Alaska.3 The Arctic and Interior regions of Alaska could 2 This map was produced by NREL for the U.S. Department of Energy. Annual average solar resource data are for a solar collector oriented toward the south at tilt equal to local latitude. The data for Alaska is derived from a 40-km satellite and surface cloud cover database for the period of 1985 to 1991. The data for Germany was acquired from the Joint Research Centre of the European Commission and is the average yearly sum of global irradiation on an optimally inclined surface for the period of 1981 to 1990. 3 For comparison to Figure 1, each region’s specific solar insolation measure is also shown in the figure heading. 29 Solar Energy Prospecting in Remote Alaska 3 expect high solar production predominantly from March through August, with a steep drop off in the shoulder months and little to no production in the winter. The Southeast and Southwest regions of Alaska show a more gradual transition of solar production levels from the sunlight rich spring and summer months to the shortening days of fall and winter. Although the electricity load peaks for many Alaska Native villages in the winter months when solar is minimally producing, these villages are also often running primarily on diesel- based generation during summer months for basic electricity needs such as lighting, refrigeration, cooking, and electronics when solar PV energy could offset fossil-fuel consumption. Furthermore, despite the cold and dark winters in Alaska that result in high energy demands, some Alaska communities have summer-peaking energy demands primarily because of commercial fishing activities and higher seasonal populations in the summer, which is generally compatible with solar availability.4 Figure 2. Annual solar production percentage across four regions in Alaska by month Source: NREL 2015 Lastly, and perhaps most significantly, Alaska has more than 175 remote village populations that rely almost exclusively on diesel fuel for electricity generation and heating oil for heat (Goldsmith 2008, AEA 2014a). Although oil is extracted in the North Slope of Alaska, the in-state production does not result in a below 4 Additionally, Sidebar 1 compares the path of the sun in the village of Kotzebue, Alaska to Denver, Colorado, to illustrate solar production in the Arctic region with a reference point in the contiguous 48 states. 0% 4% 15% 17%17% 14% 15% 10% 5% 3%0%0% J F M A M J J A S O N D Arctic Alaska Annual Solar Production Percentage by Month (2.3 kWh/m2/day) 1%2% 11% 12% 14%14% 15% 13% 7%7% 2%1% J F M A M J J A S O N D Interior Alaska Annual Solar Production Percentage by Month (3.4 kWh/m2/day) 3% 9% 13% 14% 12% 11%10% 8%7% 6% 4% 3% J F M A M J J A S O N D Southwest Alaska Annual Solar Production Percentage by Month (3.1 kWh/m2/day) 3% 5% 11% 14% 15% 9% 14% 10% 8% 5%5% 2% J F M A M J J A S O N D Southeast Alaska Annual Solar Production Percentage by Month (3.1 kWh/m2/day) 30 Solar Energy Prospecting in Remote Alaska 4 market price for oil within the state. Chris Rose, Renewable Energy Alaska Project Executive Director notes, “We [Alaskans] pay the world commodity oil price. We’ve never received some sort of ‘hometown’ discount for oil.” (Gerdes 2015). Unprocessed crude oil extracted within the state is transported via the TransAlaska pipeline from the North Slope to refineries in the Interior and South-Central regions of Alaska and then delivered locally as diesel and gasoline to rural communities a few times per year. Most fuel deliveries to remote communities are made via barge, ice road, or air transport, which also contributes to the high local prices for diesel and gasoline.5 The local markup to retail pricing also adds to the “all-in” prices for fuel in rural villages. Due to these and other factors, electricity generated by diesel fuel in some rural communities can be $1.00/kilowatt-hour (kWh) or more, which is more than 8 times the national average of $0.12/kWh (AEA 2014a, EIA 2014). As described later in this report, the State of Alaska has enacted various programs for both renewable and diesel energy sources to help reduce the energy costs in rural Alaska, but many of these programs are limited to certain sectors, or are increasingly under scrutiny with the budget difficulties being experienced by the state (AEA 2016a, AEA 2016b, Johnson 2015). For these reasons and more, alternative forms of electricity generation including solar PV are increasingly being pursued in remote Alaska communities (see Figure 3 for examples of solar PV recently installed in the Northwest Arctic Borough). This analysis provides a high-level examination of the potential economics of solar energy in rural Alaska across a geographically diverse sample of remote villages throughout the state. It analyzes at a high level what combination of diesel fuel prices, solar resource quality, and PV system costs could lead to an economically competitive moderate-scale PV installation at a remote village. The goal of this analysis is to provide a baseline economic assessment to highlight the possible economic opportunities for solar PV in rural Alaska for both the public and private sectors. 5 The cost of transportation is even more pronounced in regions that require regular fuel deliveries via air shipments, if for example, barge or ice road transport is unavailable due to freezing, thawing, low runoff, high silting, or other conditions. 31 Solar Energy Prospecting in Remote Alaska 5 Figure 3. Solar PV installations at water treatment facilities in the remote villages of Ambler, Shungnak, Deering, and Kobuk, Alaska 6 Source: Mathiasson 2015b, Northwest Arctic Borough 6 Clockwise from top left, the 8.4-kW Ambler array uses a pole-mounted array design and the 7.5-kW Shungnak installation utilizes a roof-mounted design with 90° directional offsets. The 11.55-kW and 7.38-kW design in Deering and Kobuk respectively incorporate a 180° circular system design that wraps around the east, south, and west facing walls of water treatment towers. These designs are utilized to even out the daily solar production profile (compared to systems installed facing just to the south) which can ease integration with existing diesel generators. 32 Solar Energy Prospecting in Remote Alaska 6 Sidebar 1. Seasonal Sun Path in Kotzebue, Alaska, Compared to Denver, Colorado The state of Alaska is well known for its long summer days and prolonged winter nights. Given the immense size of the state from the Northern to Southern latitudes, however, there is a wide range of expected daylight hours throughout the state. For example, on the shortest day of the year the capital city of Juneau located in the South can expect 6 hours, 22 minutes of daylight while the Northern city of Barrow is in the midst of 67 straight days of total winter darkness (Alaska.org 2015). To highlight the seasonal sun path variations of one region of Alaska compared to a representative point in the contiguous 48 United States (lower 48 states), Figure 4 below shows the sun’s path for Kotzebue, Alaska, located in the Northwest Arctic Borough, compared to Denver, Colorado, which is an approximate latitudinal mid-point of the lower 48 states. This figure shows both the spring and fall equinoxes when the total length of day and night are equal across the globe and the summer and winter solstices when the longest and shortest days of the year occur. The path of the sun’s altitude for Kotzebue illustrates how the sun never falls completely below the horizon on the summer solstice, while on the winter solstice, it never quite rises above. The shape of the sun’s path for Kotzebue also illustrates a flatter and more gradual curve compared to the relatively steep curve for Denver. While solar electricity production in Kotzebue would be minimal during the winter months, the long summer days would provide a period of extended production. The spring and fall months would also produce a moderate amount of solar electricity and benefit from low ambient temperatures and increased production from sunlight reflected off of snow cover on the ground. Figure 4. The seasonal sun paths of Kotzebue, Alaska, and Denver, Colorado Source: Suncalc 2015 with visual concept adapted from Time and Date 2015 33 Solar Energy Prospecting in Remote Alaska 7 Analysis Description and Limitations This analysis examines the economics of solar electricity at a sampling of 11 remote villages across the state. The villages were selected to represent major geographical regions across the state including the Arctic Slope, the Interior, the Southwest, the Southeast, and the Aleutian Islands. In general, these regional variations were selected to capture the variations in meteorological conditions across the state, different delivery options, and possible ranges in diesel fuel prices. All of the villages are off of Alaska’s road system. The villages included in this analysis include Adak, Ambler, Anaktuvuk Pass, Hughes, Kasigluk, Shungnak, St. Paul, Tenakee Springs, Venetie, Yakutat, and Wainwright. Figure 5 shows the location of each of the 11 villages across the state and their estimated solar insolation. Figure 5. Villages included in solar analysis 7 Source: Billy J. Roberts, NREL 7 This map was produced by NREL for the U.S. Department of Energy. Annual average solar resource data are for a solar collector oriented toward the south at tilt equal to local latitude. The data is derived from a 40-km satellite and surface cloud cover database for the period 1985–1991. 34 Solar Energy Prospecting in Remote Alaska 8 The analysis uses the levelized cost of electricity (LCOE) as a metric to compare the costs of solar electricity to diesel fuel rates, reported in cents per kilowatt-hour. LCOE is a metric that takes the entire lifecycle expenditures of an energy technology including capital costs, transportation, operating, and fuel costs (zero for solar) discounted to the present term and divided by the expected annual energy production of the energy system. While there is not a single universally accepted definition or methodology to calculate LCOE, in its basic form LCOE is often used to compare the cost of different energy technologies that can have very different cost and generation profiles (i.e., capital intensive versus operational intensive, project life, fuel costs, etc.). A common criticism for LCOE is that it does not differentiate between energy sources that are generally considered non-variable such as diesel generation from variable energy sources such as wind or solar energy. Moreover, project-level feasibility and economic evaluations are not typically made with just one metric, but instead incorporate a variety of analytical criteria including LCOE, net present value, internal rate of return, payback period, and a benefit to cost ratio, among others. For these reasons and more, LCOE is a useful though not singular metric to compare the cost of solar to the fuel-only cost of diesel generation (EIA 2015).8 To conduct the analysis, a spreadsheet-based pro-forma tool was created to calculate the LCOE for solar PV systems. This model was based on a simplified version of NREL’s Cost of Renewable Energy Spreadsheet Tool that allows for basic LCOE evaluations and includes capital, operating, and financial costs, performance and inflation adjustments, as well federal, state, and local policy support schemes (NREL 2011). This model includes the ability to model the economically significant federal tax benefits given to solar energy technologies such as the 30% investment tax credit and accelerated depreciation. The model used in this analysis was tested and reviewed by two outside entities.9 See Appendix A for more information on the model used in this analysis. Analysis Limitations It is important to note that there are many factors that will impact both the technical and economic characteristics of solar electricity, which are beyond the scope of this initial analysis. From a technical standpoint, this analysis does not explicitly consider the impact of integrating high penetration levels of variable solar electricity with a baseload diesel generation system. Instead, this analysis makes a few simplifying assumptions on integrating solar and diesel generation: • First, the analysis assumes that a kilowatt-hour produced from solar electricity is able to offset a kilowatt-hour produced from diesel generation. This one-to-one offset may not always be achievable as diesel generators are often most fuel-efficient at a given power level and generation from PV could impact the generator’s power level and thus fuel efficiency. Moreover, because diesel generators provide both energy (i.e., kilowatt-hours of generation) as well as other grid services such as voltage and frequency regulation, this analysis assumes that some level of diesel generation will always be running for grid operations and is not attempting to model a “diesel-off” scenario. • Second, the analysis also assumes the PV system would be sized small enough relative to the existing diesel generator to not require extensive energy storage systems (i.e., batteries) to integrate the solar 8 See the Data Input Assumptions Section for why only the fuel-cost component of diesel fired generation is used in this analysis. 9 These entities include the original developers of the Cost of Renewable Energy Spreadsheet Tool at Sustainable Energy Advantage and researchers at the Institute of Social and Economic Research at University of Alaska Anchorage. 35 Solar Energy Prospecting in Remote Alaska 9 and diesel generators.10 As shown previously in Figure 3, the Northwest Arctic Borough recently installed a series of PV arrays at water treatment plants in remote regional villages using PV system designs that smooths the daily solar generation profile and thus integrates more easily with the existing diesel generators. Furthermore, comparatively smaller integration upgrades such as advanced power electronics and controls installed at either the diesel powerhouse or at the PV system are assumed to be utilized and implicitly included into the all-in PV system price. As an example, a 2014 study conducted by the Alaska Center for Energy and Power found that a remote Alaskan village with a peak load of about 1.1 MW could accommodate a 135-kW PV system with no control system upgrades, and a 205-kW PV system with some control system upgrades (Mueller-Stoffels 2014).11 Conversely, whole system upgrades, or a new, but smaller diesel generator is not assumed to be included in the all-in PV system price. From an economic standpoint, this analysis also does not attempt to examine the interplay of state-derived financial relief of diesel fuel purchases by remote villages through its Power Cost Equalization (PCE) program. Instead it makes a simplifying assumption that PV would be targeted at installations not eligible for PCE such as commercial businesses, schools, or state or federal buildings.12 Although the simplifying assumptions incorporated here are useful for the purposes of this high-level investigation, more research is required in order to further refine the analysis and provide project-specific economic feasibility. 10 Existing research has attempted to quantity what levels of PV integration would require extensive integration costs for a single village, though more investigation is required for broader applicability (Jensen et al. 2013, Mueller-Stoffels 2015). 11 The range of installed costs for the PV systems described in the Data Inputs Assumptions Section is likely sufficiently wide enough to include at least one case where the control upgrades are included in the PV system pricing. 12 See Sidebar 2 for more information on the Power Cost Equalization program. 36 Solar Energy Prospecting in Remote Alaska 10 Sidebar 2. Power Cost Equalization and Renewable Energy In Alaska, a long-standing state policy program known as Power Cost Equalization attempts to equalize electricity costs between high-cost rural communities with comparatively cheaper urban population centers connected by the rail and road system from Fairbanks in the Interior through Anchorage to Homer in the South- Central region (known as the “Railbelt”) and Juneau in the Southeast. The PCE program provides significant financial relief to many of the rural communities throughout Alaska, in particular those not on the rail or road system, by using a state endowment fund to subsidize rural electricity rates to be in-line with rates experienced in the Railbelt and Southeast Regions. Although several components contribute to the PCE rate amount, a sizable portion of it is determined from the cost of diesel fuel used to generate electricity in eligible remote Alaskan communities (AEA 2014b). In this sense the PCE has been suggested by some as a financial disincentive for rural Alaskan communities to reduce their diesel dependency as doing so can also reduce the amount of PCE financial support (Hirsch 2015, Fay et al. 2012). Others note that the impacts from a renewable energy installation on PCE payments can be more pronounced on certain customer classes than others and a more nuanced assessment is appropriate (Drolet 2014). In any case, the current PCE structure has unquestionably led to a debate around if, how, and to what extent the economic value of renewable energy— principally the ability offset diesel fuel costs—is restricted by the PCE. As mentioned above, this analysis does not dive into the complex assessment of determining the net impact of renewable energy to diesel savings to PCE subsidies at the village level. Instead it makes a simplifying assumption that under the current PCE structure, the solar installation is logically targeted at a facility not currently eligible for PCE. These non-PCE eligible facilities include schools, local businesses such as a village or Native corporation, or state and federal facilities (AEA 2014b). An early example of this type of installation is the 16.8-kW system installed at Bering Straits Native Corporation in Nome in 2008, shown on the left in Figure 6 (AEA 2016c). Another example is the 6.7-kW PV project (originally installed in 2012 and expanded to more than 10 kW in 2015) developed on the school in Galena, Alaska, shown on the right in Figure 6 (Galena 2012, Pelunis-Messier 2015). Given that schools are among the largest energy users at many remote village communities, schools seem like an especially likely candidate for solar PV installations without impacting PCE as it is currently structured. Figure 6. PV Installations in Nome and Galena Source: AEA 2016c and Pelunis-Messier 2015 37 Solar Energy Prospecting in Remote Alaska 11 Data Input Assumptions: Diesel Generation Costs, Solar Costs, and Solar Resource Estimates This section briefly describes each of the data sources used for this analysis and presents the range of input cost parameters tested. Input Parameters for Diesel Generation Costs For diesel-based generation, this analysis focuses principally on the costs attributed to purchasing and transporting the diesel fuel used to run the village’s electricity generators (i.e., “fuel costs”). Other fixed costs (i.e., “non-fuel costs”) also contribute to the overall electricity prices; however, because these non-fuel costs would likely not be offset by adding solar generation, they are ignored for purposes of this analysis.13 Examples of non-fuel costs excluded from this analysis are the capital and operations and maintenance (O&M) costs for a diesel generator and a utility’s administrative charges. The costs for wholesale diesel fuel prices in remote Alaskan villages are comprehensively reported by the Alaska Energy Authority (AEA) in their annual report “Power Cost Equalization Program Statistical Data by Community” for the years 2013 and 2014 (AEA 2014a, AEA 2015).14 Utility purchases of diesel fuel for electricity generation at remote villages are typically made at wholesale rather than retail rates. The 11 villages included in this analysis present a wide range of wholesale diesel fuel costs. For example, wholesale diesel fuel prices range from a low of $3.95/gallon (gal) in Wainwright up to $6.90/gal in Ambler in 2014. Figure 7 shows the diesel fuel prices distribution for the years 2013 and 2014 for each of the 11 villages tested (AEA 2014a, AEA 2015).15 There was no consistent trend for fuel prices across the 11 villages from 2013 to 2014. Some village’s diesel fuel prices stayed relatively flat or even decreased while others increased substantially. This price variation could be due to several factors including oil commodity price fluctuations throughout the course of the year, fuel purchase prices that may or may not have been locked-in a year or more in advance, cost factors from logistical and transportation challenges from one year to the next,16 or simple reporting errors.17 Given these cost fluctuations from year to year, this analysis uses the reported diesel price points for a village as illustrative rather than precise. 13 See the Analysis Description and Limitations Section for a discussion on the costs associated with integrating the diesel and solar systems. 14 The reporting period for this report is through the end of June in the preceding year. Prices are shown in nominal dollars. 15 The years 2013 and 2014 were included in the analysis as these were the only years that a comprehensive data source with a consistently applied methodology was available. Note that the 2015 version of the AEA Power Cost Equalization Program Statistical Data by Community report was released in February 2016, shortly before the publication of this report (AEA 2016d). The analysis in this report does not incorporate the AEA 2015 data. 16 Ambler and Shungnak, for example, receive fuel shipments via barge in some years and through air transport in others. 17 Note, for example, that several reviewers suspected that a few of the outlying statistics presented in AEA 2014a and AEA 2015 were likely due to imperfect reporting or other data errors (particularly for Hughes in 2013) but generally acknowledged that these data reports are among the best available sources at this time. 38 Solar Energy Prospecting in Remote Alaska 12 Figure 7. Average wholesale diesel prices in $/gal for the 11 villages tested in 2013 and 2014 Source: AEA 2014a and AEA 2015 Although the most familiar reporting term for diesel fuel prices is in dollars per gallon, in the context of electricity generation a different cost metric is used here. AEA reports the “fuel cost per kilowatt-hour sold” ($/kWh) metric for any village that receives energy price support through the PCE program. Figure 8 shows a screenshot and callout of the fuel cost per kWh data reported for the village of Anaktuvuk Pass in the AEA report (AEA 2015). For this analysis, the fuel cost per kWh sold metric is compared to the calculated solar LCOE. Note that the terms “diesel costs”, “diesel electricity costs”, or “diesel fuel costs” are used interchangeably in this narrative to represent the “fuel costs per kWh sold” metric. $4.88 $4.96 $4.20 $6.90 $5.94 $6.83 $6.17 $5.92 $4.18 $3.91 $5.10 $6.84 $4.84 $4.77$4.78 $4.61 $5.59 $5.51 $3.95 $4.31$4.36 $4.08 2013 2014 Wainwright Kasigluk Ambler Yakutat Tenakee Springs St. Paul Adak Shungnak Venetie Anaktuvuk Pass Hughes 39 Solar Energy Prospecting in Remote Alaska 13 Figure 8. Screenshot and callout of diesel fuel purchases in Anaktuvuk Pass, Alaska Source: AEA 2015 Input Parameters for Solar Electricity Generation There are three primary data inputs used to estimate the solar LCOE: (1) the all-in installation costs for a solar PV system, (2) the ongoing O&M costs for the PV system, and (3) solar resource estimates to determine the amount of electricity produced at a given location. The input parameters for the solar resource estimates are described first followed by the solar cost estimates (both installation and O&M). This analysis uses PVWatts to simulate solar electricity production at a given village under study (NREL 2015). PVWatts utilizes the NREL National Solar Radiation database and combines solar radiation data with weather data for the years 1991–2010 to estimate a PV system’s electricity production. For this analysis, the closest available meteorological data was used to determine the electricity production at each of the 11 villages.18 Figure 9 shows a PVWatts screenshot of the village of Adak, which had data available for that exact location. 18 Five of the eleven villages had weather and solar resource data available in PVWatts. The remaining six villages were based on data from the nearest available data collection site, which ranged from 24 to 117 miles from the village under analysis. 40 Solar Energy Prospecting in Remote Alaska 14 Figure 9. PVWatts solar resource estimate tool screenshot for Adak, Alaska Source: NREL 2015 After selecting the exact or nearest location, PVWatts requires a few basic assumptions about the PV system to estimate the solar electricity production at a given site. These assumptions include system size, module type (standard or premium), mounting type (roof versus ground mounted), expected losses,19 orientation, and others. For this analysis, a 100-kW system size was assumed with an open rack-mounting system common for ground-mounted systems. Figure 10 shows a screenshot of the estimated annual kilowatt-hour production for a 100-kW PV system in Adak, Alaska (67,949 kWh per year). To estimate the solar production for a 100-kW system at all 11 villages, the process shown in Figures 8, 9, and 10 was simply repeated for each of the villages.20 19 Importantly, this analysis assumes a 5% loss factor due to snow accumulation. Snow accumulation has both positive and negative impact on a PV system’s electricity production. Snow cover on the PV panels themselves dramatically reduces the system’s ability to generate electricity. However, snow coverage on the ground can actually increase a PV system’s production through enhanced reflectivity or albedo. This analysis assumes efficient removal of snow from the panels themselves due to the easy access that ground- mounted systems provide and the steep tilt of PV panels at northern latitudes. More research is required to refine this assumption. 20 Note that in the model used in this analysis, both the installed and O&M costs of the system as well as estimated energy production scale proportionally with the size of the PV system. Therefore the PV system’s size does not directly impact the LCOE results. To illustrate, a 50-kW system would cost 50% of a 100-kW system, but correspondingly only produce half of the energy. Thus, a 50-kW, 100-kW, or any other sized system would return the same modeled LCOE. In reality, however, we would expect to see slight variations in the actual pricing due to economies of scale and other non-scaling cost and production factors. 41 Solar Energy Prospecting in Remote Alaska 15 Figure 10. PVWatts solar resource estimate tool for a 100-kW PV system in Adak, Alaska Source: NREL 2015 The solar system PV cost estimates used in this analysis are based on approximate multiples of PV pricing reported in the lower 48. Lawrence Berkeley National Laboratory reports a 100-kW commercial-scale PV system at a median price point of approximately $3.40/watt (W) in the first half of 2015 (Barbose et al. 2015). As prices continued to fall in the second half of 2015 and 2016, this analysis assumes a flat $3/W pricing as the lower 48 base level price, which is then increased to account for higher costs for nearly all goods and services in remote Alaskan communities. This analysis multiplies the lower 48 base level price by 2, 3, or 4 times to get a range of estimates for remote village pricing. These multiples correspond to $6/W, $9/W, and $12/W for low-cost, base-case, and high-cost cases respectively. There is some limited evidence of PV installed pricing at both the low and high end of the range presented in Table 1. For example, Pelunis-Messier 2014 reports PV installed at approximately $5/W, Mathiasson 2015a indicates that ten small sized PV projects ranged in pricing from nearly $6/W to over $11/W, and Irwin 2013 cites a 2013 installation at nearly $11/W. Given this wide variation in pricing, this analysis uses a range of possible Alaskan village PV costs rather than a single point estimate as there is significant uncertainty in both the low and high end of the installed PV price ranges in the remote village locations. The O&M costs are treated in a similar fashion. Assuming a lower 48 cost of $20/kW per year for O&M expenditures, the low-cost, base-case, and high-cost cases for remote Alaskan villages is estimated at $40/kW/year, $60/kW/year, and $80/kW/year respectively. 42 Solar Energy Prospecting in Remote Alaska 16 Sidebar 3. Cost Trajectories of Diesel Fuel and Solar PV Figure 11 below illustrates the cost trajectories of wholesale diesel fuel rates compared to the installed price of solar PV (based on commercial sector pricing from the lower 48) from 2002 through mid-year 2015 (EIA 2016a, Barbose et al. 2015). This chart indexes diesel fuel and solar PV prices in $/gal and $/W respectively, to a base value of 100 in 2002. Figure 11 highlights the percentage change based on real dollars over time. Several trends are apparent in Figure 11. The cost of diesel fuel has been rising steadily since 2002 with two noticeably steep price declines in 2008 and 2014. Diesel fuel prices quickly recovered in 2009, but as of November 2015 remain at their lowest price point since 2003. Even at the low historic pricing levels, the indexed value of diesel fuel costs rose by more than 50% from a base value of 100 in 2002 to 153 in late 2015. Solar PV pricing has shown a steady cost decline in every year since 2002 from a base index value of 100 in 2002 to 32 in 2015 – a reduction of over 67%. Given this cost comparison over time, several factors contribute to an improving relative economic case over time for solar PV. First, solar PV price declines exhibited both predictability and an overall declining cost path. Conversely, diesel prices have been more volatile and have shown an overall increase from 2002 to 2015. Unpredictability in diesel fuel costs makes long-term village electricity cost projections difficult to manage. As a repercussion, some villages have locked in future diesel fuel purchases at a previous year’s pricing and therefore are not paying current market rates (both on a premium or a discount). Moreover, even while diesel fuel prices are currently lower than any time since 2003, there are other ramifications of the low commodity price. Perhaps most noteworthy is that Alaska’s state budget has been drastically reduced from the low price of oil. This means that many state funded programs could be at risk in the current budget environment, including ones targeted at rural communities such as PCE (Johnson 2015 and Forgey 2015). Moreover, as described later, several sources are predicting a rise in diesel rates as soon as mid- year 2016 (EIA 2016b). Solar PV can therefore offer a pricing hedge against the volatile nature of diesel fuel prices and potential changes to PCE that could impact remote communities. Figure 11. Indexed diesel and solar PV prices from 2002 to 2015 Source: EIA 2016a and Barbose et al. 2015. Diesel and solar PV pricing data underlying the index values use 2014 real dollars. Note that this comparison does not normalize for energy content. For comparison, a gallon of diesel has approximately 128,488 British thermal units (Btu) while 1 kWh of electricity has approximately 3,414 Btu (AFDC 2014). 153 32 0 50 100 150 200 250 300 350 400 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 Diesel Solar PV 43 Solar Energy Prospecting in Remote Alaska 17 Summary of Input Assumptions Table 1 presents the solar capital and O&M cost estimates for a low-, base-, and high-cost scenario. Figure 12 visually captures the at-times difficult conditions of installing and maintaining all types of equipment, including PV, in remote Alaska. The occasionally harsh conditions contribute in part to the uncertainty in costs of installing and maintaining different energy generation technologies in remote communities and thus, the wide ranges of input parameters used. Table 1. Cost Estimates for a 100-kW PV System Village Case Lower 48 Cost Multiple Capital Costs ($/W) O&M Costs ($/kW/yr) All Low Cost 2 X $6 $40 Base Case 3 X $9 $60 High Cost 4 X $12 $80 Figure 12. Servicing a PV system in remote Alaska Source: Bensin 2015 44 Solar Energy Prospecting in Remote Alaska 18 Table 2 shows the annual kilowatt-hour production for a 100-kW system installed across the 11 villages. The capacity factor is also shown for illustrative purposes.21 Table 2. Annual Solar Energy Estimates Annual Solar Energy Solar Capacity Factor Village (kWh) (%) Adak 67,979 7.8% Ambler 86,230 9.8% Anaktuvuk Pass 85,138 9.7% Hughes 90,456 10.3% Kasigluk 91,764 10.5% Shungnak 86,230 9.8% St. Paul 62,268 7.1% Tenakee Springs 88,547 10.1% Venetie 101,824 11.6% Wainwright 73,881 8.4% Yakutat 73,934 8.4% Source: NREL 2015 Table 3 summarizes the wholesale diesel fuel cost data gathered for the 11 villages in this analysis. Because diesel fuel is a world commodity with constantly changing prices, price data from both 2013 and 2014 are included in this analysis and represent the range of years in which the comprehensive and consistent data source is available.22 While the continued drop in oil and diesel fuel rates experienced in 2015 is not captured in AEA 2014a and AEA 2015, some analytical projections indicate that diesel commodity prices will begin to rise in mid-2016 (EIA 2016b). Future research could provide an update to the results presented here based the most current pricing data available for both diesel fuel and installed solar PV prices. 21 Capacity factor is a common metric reported for electrical generation, which is a ratio that compares the amount of actual electric generation produced in a year divided by its potential generation if it could operate at full capacity for the entire year. 22 Is it is also important to note that while the two metrics of fuel costs, $/gal and $/kWh, track one another fairly well, they are not perfectly correlated from one year to the next nor village to another. This is because fuel costs in $/kWh calculations are impacted by other factors such as changing diesel engine efficiency (particularly if a newer, more efficient generator is installed), electrical line losses, and other factors. It is also likely that simple data reporting inconsistencies from year to year influence how closely fuel costs in $/gal and $/kWh track one another. 45 Solar Energy Prospecting in Remote Alaska 19 Table 3. Wholesale Diesel Fuel Costs for Electricity Generation 23 2013 Diesel Fuel Cost 2014 Diesel Fuel Costs Village ($/gal) ($/kWh) ($/gal) ($/kWh) Adak $4.96 $0.57 $4.96 $0.67 Ambler $4.27 $0.33 $6.90 $0.53 Anaktuvuk Pass $6.04 $0.47 $6.83 $0.55 Hughes 24 $6.27 $0.88 $5.92 $0.41 Kasigluk $4.25 $0.47 $3.91 $0.40 Shungnak $5.18 $0.65 $6.84 $0.87 St. Paul $4.92 $0.41 $4.77 $0.36 Tenakee Springs $4.86 $0.43 $4.61 $0.45 Venetie $5.68 $0.64 $5.51 $0.75 Wainwright $4.01 $0.34 $4.31 $0.35 Yakutat $4.43 $0.34 $4.08 $0.31 Source: AEA 2014a, AEA 2015 Finally, the utilization of federal tax benefits such as the 30% investment tax credit and accelerated depreciation benefit are assumed in this analysis. In the lower 48, nearly all PV projects of the scale considered here (small commercial at 100 kW) will utilize federal tax incentives for renewable energy as part of the project’s overall economic value. In the context of Alaska, however, this concept is still relatively nascent with little precedent, but is gaining attention as state-based dollars for grants (which generally reduce the inherent value of federal tax credits) are expected to diminish in the coming years following reduced oil revenue flowing into the state (Johnson 2015). The utilization of for-profit business ownership structures adapted to Alaska’s unique business climate will likely be a critical market requirement to expanding solar development in the state. 23 Diesel fuel price inputs shown in 2014 dollars. 24 As mentioned previously, a data reporting error for Hughes in 2013 likely contributes to the high cost shown for 2013 (AEA 2014a). This data outlier is excluded from the results and conclusion discussion. 46 Solar Energy Prospecting in Remote Alaska 20 Analysis Results Figure 13 presents the LCOE results for solar PV under the low-cost, base-case, and high-cost scenarios across the 11 villages analyzed.25 The LCOE under each PV pricing scenario is shown as a different shade of blue. As an example, for the village of Venetie the low-cost scenario of $6/W results in an LCOE of just under 40 cents/kWh; the base-case scenario of $9/W results in an LCOE of approximately 60 cents/kWh; and the high-cost scenario of $12/W results in an LCOE of nearly 80 cents/kWh. Figure 13 also shows the diesel fuel costs per kilowatt-hour for each of the 11 villages in 2013 and 2014. Several interesting findings emerge from comparing the range of PV cost estimates ($6/W to $12/W) to the 2013 and 2014 fuel-only diesel electricity costs. First, a select number of villages experience diesel electricity generating costs high enough that they are approaching or nearly on par with the LCOE from even the highest PV cost scenarios. These cases include Venetie for both 2013 and 2014 and Shungnak based on reported 2014 diesel prices.26 Under these cases, achieving cost savings from a PV installation appears among the most likely scenarios as PV installation prices of $9/W or more could be cost competitive with the reported diesel electricity generating costs. PV pricing falling below $9/W would show a larger economic savings. Second, several other villages also show cases where diesel prices are still high enough that PV could potentially compete economically at the low-cost PV price scenario of $6/W. In addition to the high cost examples mentioned above, these villages include Ambler (2014), Shungnak (2013), Anaktuvak Pass (2014), Kasigluk (2013), and Adak (2014). In these examples, PV pricing at $6/W could be expected to result in economic savings when compared to the recent fuel expenditures. Third, many villages appear to show cases where the PV LCOE could be considered marginally or borderline cost competitive, even at the assumed $6/W pricing level and diesel prices reported in 2013 and 2014. In these cases, the solar PV to diesel fuel cost comparison is considered within the level of specificity of these modeling results, so a more detailed investigation could produce results with favorable solar PV economics. These situations include Kasigluk (2013), Hughes (2013), Tenakee Springs (2013, 2014), Anaktuvuk Pass (2013), and Adak (2013). Finally, there are a few cases where the diesel fuel prices in some villages are below even the lowest estimated PV LCOE, and a solar PV installation does not appear to be economically competitive at the pricing levels assumed in this analysis. These cases include the villages of Yakutat, Wainwright, and St. Paul. Importantly, and what is not captured in Figure 13, is the benefit of price predictability that solar PV can provide from zero fuel costs. As shown previously in Figure 7 and Sidebar 3, diesel fuel prices have experienced significant fluctuations from one year to the next and accurate price projections are difficult to make. Solar PV, by contrast, experiences the vast majority of its costs (with the exception of maintenance expenses) upfront and therefore offers a predictable energy price for the remainder of the system’s life—often 20 years or more. Additionally, because PV prices have historically been falling rapidly, a $6/W pricing point that is assumed as a low pricing scenario in the current analysis, could likely be reduced even further in the near future, particularly if the market for solar PV in Alaska begins to mature and efficiencies develop. 25 The full listing of LCOE results can also be found in Appendix B. Results are shown in cents per kWh rather than the equivalent $/kWh. Note that all results are presented in 2014 dollars. 26 The high diesel generation cost for the village of Hughes in 2013 appears as an outlier as significant diesel efficiency gains were reported in 2014 (AEA 2015). 47 Solar Energy Prospecting in Remote Alaska 21 Figure 13. Cost of electricity comparison between solar PV and diesel generation 0 20 40 60 80 100 120 140 Cost of Electricty (cents/kWh)48 Solar Energy Prospecting in Remote Alaska 22 Conclusion This analysis compares the cost of installing and operating a moderately sized solar PV system to recent diesel fuel expenditures for electricity generation for several remote villages across Alaska. The high-level results indicate there are plausible scenarios in which PV can be economically competitive with diesel fuel prices at low PV penetration levels. In this analysis, the cases where PV appears economically competitive generally required a combination of (1) high diesel fuel prices (at least 40 cents/kWh), (2) relatively low, for Alaska, PV prices (approximately $6 to $9 per W installed), (3) relatively high, for Alaska, solar production levels (capacity factor of nearly 10% or higher), and (4) the ability to make use of economically valuable tax benefits provided by the federal government. Solar development is likely to be favorable for other Alaskan villages not considered in this analysis but that have a similar combination of characteristics. However, to advance this high-level analysis to more precise estimates and eventually a large increase in deployed solar projects in Alaska, a select number of potential barriers noted previously will require further research or business ingenuity to address. Some of these barriers include, but are not limited to, the following. • The integration of solar PV with a diesel generator is an ongoing area of study and demonstration. The simplifying integration assumptions, including seasonal variability, made in this analysis should be revised when better information is available. • Regulatory and business structures such as how to work with the current PCE formula and how to utilize the valuable federal tax incentives will need to be addressed by the stakeholders involved. • Further refinements in real-world installation and maintenance costs of large-scale PV systems in rural Alaska will provide more accurate inputs to the economic modeling. Despite each of the simplifying assumptions made here, this analysis suggests that solar PV—along with fuel and other electricity savings measures—can be economically competitive in many remote Alaskan villages and could have a number of benefits including reducing a village’s dependency on diesel fuel, improving electricity price predictability, providing local environmental benefits, and more. 49 Solar Energy Prospecting in Remote Alaska 23 References Alaska.org. 2015. “Shortest Day in Alaska,” accessed January 20, 2016, http://www.alaska.org/advice/shortest-day-in-alaska. Alaska Energy Authority (AEA). 2014a. Power Cost Equalization Program: Statistical Data by Community. Reporting Period: July 1, 2012 to June 30, 2013. Issued February 2014. http://www.akenergyauthority.org/Content/Programs/PCE/Documents/FY13StatisticalRptComt.pdf. Alaska Energy Authority. 2014b. Power Cost Equalization Program Guide. 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UA Research Summary No. 10, January 2008, Institute for Social and Economic Research, University of Alaska Anchorage. Accessed January 20, 2016. http://www.iser.uaa.alaska.edu/Publications/researchsumm/UA_RS10.pdf. Hirsch, B. 2015. “A partial solution to rural Alaska energy challenges,” Alaska Dispatch News, October 24, 2015, accessed January 20, 2016, http://www.adn.com/article/20151024/partial-solution-rural-alaska-energy- challenges. 51 Solar Energy Prospecting in Remote Alaska 25 Irwin, C. 2013. “Displacing Diesel May Prove Cost-Prohibitive in Rural Alaska,” Breaking Energy, August 1, 2013, accessed January 20, 2016, http://breakingenergy.com/2013/08/01/displacing-diesel-may-prove-cost- prohibitive-in-rural-alaska/. Jensen, R., Baca, M., Schenkman, B., and Brainard, J. 2013. Venetie, Alaska Energy Assessment. SAND2013- 6185. Sandia National Laboratories, Albuquerque, NM, July 29, 2013. Accessed January 20, 2016. http://prod.sandia.gov/techlib/access-control.cgi/2013/136185.pdf. Johnson, K. 2015. “As Oil Prices Fall, Alaska’s New Governor Faces a Novel Goal, Frugality,” New York Times, January 25, 2015, accessed January 20, 2016, http://www.nytimes.com/2015/01/26/us/as-oil-falls- alaskas-new-chief-faces-a-novel-goal-frugality.html?_r=1. Mathiasson, I. 2015a. “2011 NAB Synergy Project.” 2015 Alaska Solar Energy Workshop, accessed January 20, 2016. http://acep.uaf.edu/media/131247/2015-SEW-Case-Studies-from-Around-the-State-Solar-PV-PCE- Calculations-Ingemar-Mathiasson.pdf. Mathiasson, I. 2015b. Northwest Arctic Borough, personal correspondence, December 7, 2015. Mueller-Stoffels, M. 2014. Adding PV Capacity: Initial Assessment and Recommendations for Galena, Alaska. Alaska Center for Energy and Power, University of Alaska Fairbanks. January 2014. Accessed January 20, 2016. http://acep.uaf.edu/media/82430/initialAssessmentReport-3.pdf. NREL. 2011. “CREST Cost of Energy Models,” Renewable Energy Project Finance, National Renewable Energy Laboratory, accessed January 20, 2016, https://financere.nrel.gov/finance/content/crest-cost-energy- models. NREL. 2013. “Renewable Energy In Alaska”. WH Pacific, Inc. National Renewable Energy Laboratory, accessed February 5, 2016. http://www.nrel.gov/docs/fy13osti/47176.pdf. NREL. 2015. “PVWatts Calculator,” National Renewable Energy Laboratory, accessed January 20, 2016, http://pvwatts.nrel.gov/. Pelunis-Messier, D. 2014. “Interior Alaska’s Solar Resource.” 2014 Rural Energy Conference, accessed January 20, 2016, http://www.akruralenergy.org/2014/Opportunities_for_Solar_PV_in_Alaska's_Interior- David_Pelunis-Messier.pdf. Pelunis-Messier, D. 2015. Personal correspondence, December 7, 2015. Renewable Energy Alaska Project (REAP). 2016. “Alaska’s Renewable Energy Projects,” accessed January 20, 2016, http://alaskarenewableenergy.org/why-renewable-energy-is-important/alaskas-renewable-energy- projects/. Suncalc. 2015. “Computation path of the sun for Kotzebue, Alaska, and Denver, Colorado,” accessed January 20, 2016, www.suncalc.org. 52 Solar Energy Prospecting in Remote Alaska 26 Time and Date. 2015. “Today’s Sun Position,” Time and Date AS, accessed January 20, 2016, http://www.timeanddate.com/astronomy/usa/denver. Wirth, H. 2015. Recent Facts about Photovoltaics in Germany. Fraunhofer ISE, Freiburg, Germany, December 25, 2015. Accessed January 20, 2015. https://www.ise.fraunhofer.de/en/publications/veroeffentlichungen-pdf-dateien-en/studien-und- konzeptpapiere/recent-facts-about-photovoltaics-in-germany.pdf. 53 Solar Energy Prospecting in Remote Alaska 27 Appendix A. Model Overview and Description The analysis utilized an NREL-developed cost-of-energy spreadsheet model intended to assist in the evaluation of the costs of an electricity generation system for a representative remote Alaskan town (model schematic depicted in Figure 14. The model calculates the cost of energy for three different types of load: Primary, Deferrable, and Thermal, based on inputs defining project installation (size, capital costs, etc.), financing, and operational costs and the ratios of each generation price and load type. Users can choose to run the model in one of three calculation modes: Target Internal Rate of Return, Target Payback Period, or Target Energy Cost, holding that variable constant and returning values for the other two variables along with debt metrics, fuel savings, and other costs. For this analysis, all revenue was assumed to be generated from the AC Primary Load, thus the inputs for the Deferrable Load and Thermal Load were set to zero. In addition to the inputs shown in Table 1 and Table 2, this analysis also assumed that the project was financed with 100% equity, generated an 8% Internal Rate of Return, and that both the LCOE and annual O&M expenditures increased by 1.5% annually. Figure 14. Schematic of LCOE model used in this analysis 54 Solar Energy Prospecting in Remote Alaska 28 Appendix B. Levelized Cost of Energy Results Table 4 shows the solar PV LCOE for each of the 11 villages under analysis for the low-cost, base-case, and high-cost scenarios. Table 4. Solar PV LCOE Modeling Results Low-Cost Base-Case High-Cost Village (¢/kWh) (¢/kWh) (¢/kWh) Venetie $39.91 $59.44 $78.96 Kasigluk $44.29 $65.95 $87.62 Hughes $44.93 $66.91 $88.89 Tenakee Springs $45.90 $68.35 $90.80 Ambler $47.13 $70.19 $93.24 Shungnak $47.13 $70.19 $93.24 Anaktuvuk Pass $47.74 $71.09 $94.44 Yakutat $54.97 $81.86 $108.75 Wainwright $55.01 $81.92 $108.83 Adak $59.79 $89.03 $118.28 St. Paul $65.27 $97.20 $129.12 55 City of Galena Solar PV & Battery Feasibility Review Prepared For: Prepared By: Coffman Project # 190604 Rev. Description By Approved Date A Draft, Issued for Review M. Miller T. SlatonBarker 14 May 2019 56 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 1 Rev A Table of Contents 1. Introduction ......................................................................................................................................................... 2 2. Existing Power System ....................................................................................................................................... 2 3. Energy Modeling ................................................................................................................................................ 2 3.1 City Load .................................................................................................................................................... 3 3.2 Solar Photovoltaic (PV)............................................................................................................................. 4 3.3 Batteries ...................................................................................................................................................... 5 4. PV & Battery Project Economics ....................................................................................................................... 7 4.1 Capital Cost ................................................................................................................................................ 7 4.2 Impact to Rates .......................................................................................................................................... 7 5. Conclusions ......................................................................................................................................................... 8 6. Next Steps ............................................................................................................................................................ 8 57 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 2 Rev A 1. INTRODUCTION The City of Galena (“Galena” or “The City”) is located in interior Alaska, along the Yukon river, approximately 270 miles west of Fairbanks. The City has approximately 500 inhabitants. Travel to Galena is primarily by airplane. Summer barge service is available along the Yukon. The City of Galena is in receipt of a US Department of Agriculture (USDA) grant for construction of a “High Penetration Solar-Battery-Diesel Hybrid System.” The proposed project includes adding a relatively large solar photovoltaic (PV) array, coupled with a battery energy storage system (BESS) and grid-forming inverter to the existing diesel-powered grid. The PV & BESS would reduce the City’s dependence on diesel fuel, with a stated goal of “15% diesel fuel displacement from 2017 baseline,” as stated in the project implementation plan, dated December 2018. The USDA grant totals $1.5M and requires a significant cost-sharing match from the City. The current project cost estimate is $4.46M. The City engaged Coffman to review the technical and economic feasibility of the project, as proposed for the USDA grant. This report outlines the results of this analysis and provides recommendations to further evaluate, refine and ultimately develop the project. The following documents were received and reviewed as part of this evaluation: • USDA Grant Project Implementation Plan (PIP), dated August 2018; • Tesla ‘indicative’ Pro Forma for PV & Battery project; • Power Cost Equalization Galena FY18 summary; • Notes and presentation slides from August 2018 public meeting in Galena; and, • Available electrical load data for the ‘City’ and ‘Base’ feeders. 2. EXISTING POWER SYSTEM The City of Galena operates the local electric utility, which is an independent, isolated electrical grid that serves customers throughout the City and the Galena Interior Learning Academy (GILA) campus. GILA is located west of town and north of the airport on a former US Air Force base. A single diesel fired powerplant provides power for all connected electrical loads. The powerplant contains six (6) Caterpillar reciprocating diesel generator sets, with capacities ranging from approximately 450kW to 900kW. A backup generator set is located on the GILA campus. Generator controls – start/stop, synchronizing, etc. – is reportedly manually operated. Detailed generator & switchgear configuration and sizing information was not available at the time of this evaluation. Age, wear and size/capacity of the generators are a concern as they were installed decades ago and operated by the Military prior to being transferred from the USAF to the City when the USAF Base shut down. 3. ENERGY MODELING The technical feasibility of the PV & BESS project was evaluated by creating an energy model based on the attributes of the existing electrical system and project components outlined in the project implementation plan. A detailed project description was not available for review at the time of this evaluation. The energy model uses an hourly time-step and covers one full year. 58 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 3 Rev A 3.1 CITY LOAD The City load profile was estimated based on information provided by the City and publicly available information through the State of Alaska Power Cost Equalization (PCE) program. The Galena Fiscal Year 2018 PCE report indicates the following gross annual figures: Galena Key Annual Metrics (from FY18 PCE Report) Variable Value Units Gross Generated Electricity 5,704,098 kWh Total Electricity Sold 5,046,507 kWh Average Load (Generated / Sold) 651 / 572 kW Diesel Fuel Consumption 423,289 Gallons Average Generator Efficiency 13.48 kWh / Gallon Average Price of Fuel $2.24 $ / Gallon Fuel Expense $0.19 $ / kWh Non-Fuel Expense $0.25 $ / kWh The City provided partial metering data that was used to develop an hourly load estimate. The data consisted of meter readings from the two primary feeders – one serving the ‘City’ and one serving the ‘Base’ (GILA campus area). Data from the two meters did not cover the entire year, but was adequate to establish typical seasonal and diurnal (day/night) load variations. Missing data was synthesized using the load ratio between the two feeders, and scaled to the PCE-reported annual sales volume. Figure 1 - Galena synthesized annual load profile 59 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 4 Rev A The data show a typical load profile for rural Alaska grids – lower loads in the summer months (375kW - 525kW), higher loads during winter (525kW – 800kW+). 3.2 SOLAR PHOTOVOLTAIC (PV) The solar PV portion of the proposed project includes 4,032 Solar PV modules. Each module produces up to 310 watts, for a total installed capacity of 1.25 megawatts-dc (MW-dc). Prelminary placement of the PV system is within the dike on the north side of the runway, as shown in Figure 2, which is copied from a 2018 presentation to the City Council. Figure 2 - Potential PV Location north of Runway 25 (from 2018 presentation to the City) Based on this location and project size, Coffman developed an independent analysis of the expected output of the PV system, using Helioscope modeling software. High quality solar data was not readily available for Galena, so the nearest data source – TMY3 data from Huslia – was used. We anticipate that the Huslia solar irradiance (available solar energy) provides a reasonable approximation for the purpose of this study. The following modeling assumptions were made in order to evaluate the output of the proposed PV array as specific design/layout information was not available for review at the time of this evaluation. • 180 degree azimuth, Fixed 25 degree tilt; • DC/AC Ratio: 1.24 (maximum AC power to the grid is less than total installed DC capacity of the PV modules); • 10% soiling for November through March due to snow (to be confirmed based on selected tilt angle). 60 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 5 Rev A Based on these assumptions, the annual output of a 1.25MW-dc PV array is 1,091,000 kWh, or approximately 22% of the total annual City electrical sales volume. This value is 5% less than calculated ‘Energy Flows’ indicated on the preliminary project Pro Forma that was received. This small discrepancy does not impact feasibility of the project and may be attributable to general assumptions that are built into the estimates, which can be resolved during detailed design. Monthly totals of available solar power are shown in Figure 3, based on the Helioscope modeling. Note that the total output during October – March is approximately 7.5% of the annual PV production and therefore is only a minor factor in energy and economic projections. Figure 3 - 1.25MW-dc Photovoltaic Array Monthly Output Due to the large PV array size in relation to the Galena grid, not all of this available solar energy may be utilized. See further analysis under the batteries section of this report. 3.3 BATTERIES The BESS portion of the proposed project includes the following components: • 7 Tesla Power Packs (Energy Storage) totaling 848 kW/1,696 kWh storage capacity • 0.9 MW Tesla Bi-Directional Inverter • 1 Proprietary Tesla Microgrid Control System We understand that the proposed project estimates 1000 hours of ‘diesels off’ operation each year. We were not able to confirm or analyze this value because battery sizing methodology and energy flow estimates were not provided to Coffman at the time of this evaluation. Therefore, our high-level analysis considers the applicability of a battery system based on the system load and available PV production, given the selected 1.25MW-dc system. This analysis is based on hourly energy modeling over the entire year. A model was developed to evaluate how much PV production would be unusable (or “excess”), if not for a battery system, which in turn helps quantify the maximum potential benefit of adding batteries to the system. The model accounts for a minimum load on the diesel engine (assumed to be 100kW). This variable may change based on the size and capabilities of the existing or replacement generators. Modeling results indicate that a ‘Base Case’ installation of only a standard grid-tied solar PV system – no batteries – would utilize approximately 73% (801,000 kWh) of the solar power generated by the 1.25MW-dc PV project described above. In this scenario at least one diesel generator set would operate continuously and the PV system would have commercially available power limiting controls. 61 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 6 Rev A The Base Case scenario modeling we performed indicates an offset of 16% of the annual fuel use, meeting the USDA grant performance goal of 15% reduction in fuel use. In the Base Case, 290,000 kWh of ‘excess’ solar electricity would be curtailed. In other words, the proposed BESS would provide a maximum value of 290,000 kWh/year. Adding a BESS is one way to capture this lost energy. Optimizing the size of the PV system could also achieve diesel offset goals, while minimizing system complexity. That optimization is beyond the scope of this current evaluation. We would expect the actual benefit of a BESS will be less than this maximum, as sizing and economic considerations are likely to result in equipment that cannot capture all available solar energy. Additionally the battery charging and discharging is not 100% efficient, so not all the solar energy can be captures and reused at a later time. For example, on a single sunny day in mid-summer, there will be over 4,000 kWh of excess energy available. The proposed BESS includes 1,696 kWh of storage, meaning that 2,300 kWh of solar energy would get curtailed on that day. This is not a criticism of the proposed system, but rather an acknowledgement of a technical and economic consideration that accompanies any such ‘microgrid’ project. A larger battery system could capture more energy on the most sunny days, but would provide little benefit for most of the year. We also looked at the timing of PV production versus town loads. Figure 4 - Galena Annual load and 1.25MW PV production profilesFigure 4 shows this information graphically. Our calculations show that the PV production is larger than the town load – including a 10% reserve margin – for 718 hours per year, which cumulatively totals nearly 30 days. If a BESS system were installed, these 718 hours would be the basis for ‘Diesels off’ operation, and would occur intermittently throughout the March- September season. Figure 4 shows that, as expected, those hours fall between March and September. Perhaps more surprising is the linear nature of the line, indicating that once the spring sun is strong enough to allow ‘Diesels off’ operation, the number of hours of ‘Diesels off’ are fairly consistent throughout the March-September period. Figure 4 - Galena Annual load and 1.25MW PV production profiles - 100 200 300 400 500 600 700 800 0 200000 400000 600000 800000 1000000 1200000 JFMAMJJASOND Cummulative Hours of Possible 'Diesels off'Power (Load or Output [Watts]Galena annual towl load, 1.25MW-dc PV output, and cummulative possible 'Diesels off' hours 1.25MW PV Output town load Cumulative hours of possible diesels off 62 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 7 Rev A 4. PV & BATTERY PROJECT ECONOMICS 4.1 CAPITAL COST Parametric cost evaluation for the proposed project based on recent pricing on similar sized systems is shown in Table 1. The total project cost, based on these parametric cost factors and exclusive of any required upgrades to the power plant or electrical distribution system, is $5.1M. The Tesla Pro Forma shows a total project cost of $4.55M, 12% less than our rough estimate. Scope of Work Capacity Parametric Cost Installed Cost Photovoltaic Installation 1.25MW-dc $3 / Watt $3.75M Batteries/Inverters/Controls 848 kW/1,696 kWh $800 / kWh $1.36M Distribution System Upgrades Undefined *Excluded* Powerplant Upgrades Undefined *Excluded* Total PV + BESS $5.11M Table 1 - PV & Battery Capital Cost Estimate We have found recent PV project pricing in Alaska to be around $3 per watt of installed capacity, including minimal site prep, fixed tilt racking, standard shallow pile foundations (no permafrost), DC wiring, PV inverters and electrical tie-in. Battery project costs are dependent on the storage capacity of the battery (kWh) in comparison to the rated power output (kW). The marketplace for both technologies is quickly evolving and may result in bid prices that differ from those shown above. Capital cost for PV projects have declined steadily and significantly in recent years. The market factors driving these price reductions are likely to continue. However, the trade dispute currently playing out between the US and China could impact availability of PV modules. A 30% import tariff was put in place in January 2018, adding to the cost of PV projects throughout the country. The tariff is set to decline 5% per year through 2021. Impacts of this trade dispute and upcoming additional tariffs that may impact the project are unknown at this time. 4.2 IMPACT TO RATES While the Pro Forma provides a starting point for evaluating the economic impact of this project, there are a number of variables that are currently undefined or unconfirmed that could significantly impact the project initial capital cost and life-cycle economics. Prior to analyzing rate impacts in detail, we recommend confirming the technical requirements of other parts of the project implementation, including: • Define operations/staffing strategy; • Define City priorities (maximize fuel offset vs. minimize installed cost); • Clarify how much flexibility the USDA grant allows to tweak the technical aspects of the project; • Optimize PV and battery sizing for the most beneficial outcome; and, 63 City of Galena Solar PV & Battery Feasibility Review 14 May 2019 Page 8 Rev A • Clearly define the power plant upgrade requirements that are separate from, but impact the project, including generation assets, switchgear and controls • Clearly define the electrical distribution system upgrade requirements. 5. CONCLUSIONS Our analysis found that the solar PV estimates indicated on the Tesla Pro Forma are reasonable, based on the solar resource in Galena and the selected project capacity. However, we were not able to determine what analysis was used to size the proposed PV array (1.25MW-dc). We recommend more detailed modeling and comparison of various sized PV arrays that would allow the City to optimize the value of its investment. Our modeling indicates that the PV array alone – without adding a battery system – results in a 16% reduction in annual fuel consumption, which meets the USDA grant performance target. If PV alone can produce the results required to obtain USDA funding, this would likely be the most cost effective option (lowest upfront capital cost). This option would also result in the simplest system configuration and would be significantly less dependent on power plant upgrades to properly function. Battery energy flow estimates were not provided to Coffman for review at the time of this evaluation. Therefore our battery sizing analysis is independent of the proposed Tesla project described above. Our calculations show that it’s reasonable to achieve over 700 hours of diesels-off operation, based on 1.25MW-dc PV capacity. Battery sizing and control methodology for the proposed project were not available for review at the time of this evaluation. It would be prudent to model both PV and BESS system capacities to optimize for the best economic value, while meeting the USDA grant performance metrics. 6. NEXT STEPS 1. We recommend that the City review power plant infrastructure as it relates to upgrades required for integration and operation of the PV & BESS project. This process includes clearly delineating capital cost and operational savings between the ‘power plant upgrades’ scope and the USDA grant-funded ‘PV and BESS’ scope. Power plant functionality and operational strategy can have a large impact on the economics of any PV or battery project. 2. We recommend that the City carefully review PV and battery sizing assumptions and optimize the project sizing to maximize economic benefit. This step will need to consider the USDA grant obligations, including performance metrics and financial matching requirements. 3. We recommend that the City evaluate the performance and requirements (total connected load, future customers) of both existing heat recovery systems and determine if and how the two systems could be combined. If they can be combined, it is expected to allow the city to reduce the number of online generators at certain times. 4. We recommend analyzing the characteristics of the system load in higher resolution (faster time scale) in order to incorporate spinning reserve margins into the modeling assumptions. 5. Once the above items are completed, we recommend updating the economic projections for an optimized PV + Battery project. Interest rates, project term, O&M impacts and other pro forma inputs should be reviewed in detail and adjusted if needed. 64 Annual Production Report produced by GEORGE VAUGHAN © 2019 Folsom Labs 1/2 April 16, 2019kWhJanFebMarAprMayJunJulAugSepOctNovDec 0 50k 100k 150k 200k Shading: 3.5%Shading: 3.5% Reflection: 3.7%Reflection: 3.7% Soiling: 3.6%Soiling: 3.6% Irradiance: 1.7%Irradiance: 1.7% Mismatch: 3.7%Mismatch: 3.7% Wiring: 0.2%Wiring: 0.2% Clipping: 0.0%Clipping: 0.0% Inverters: 2.0%Inverters: 2.0% AC System: 0.5%AC System: 0.5% 65 Annual Production Report produced by GEORGE VAUGHAN © 2019 Folsom Labs 2/2 April 16, 2019 66 Galena Hybrid System Analysis Tony Jimenez, Senior Engineer NREL Aug 3, 2020 67 NREL | 2 Background / Purpose / Approach Results / Conclusions / Recommendations Facts & Assumptions / Intermediate Analysis 68 3 Introduction / Overview The City of Galena, “Galena” requested support under the Department of Energy’s Office of Indian Energy (DOE-IE) tribal technical assistance (TA) program. Galena’s municipal utility is planning to add a PV-battery system to the existing diesel power plant. The City requests a preliminary feasibility analysis to determine the appropriate sizes for the PV array and battery bank and analyze the financial feasibility of such a system. This document describes the results of the sizing and financial feasibility analysis. In particular, the performance and costs of retrofits with and without storage were examined. 69 4 Overview Borough Yukon -Koyukuk Census Area Regional Native Corporation Doyon, Ltd Latitude N 64.7433 Longitude W 156.9275 Elevation 39 m Electric utility City of Galena Galena Overview 70 5 Overview: Location 71 NREL | 6 Background / Purpose / Approach Results / Conclusions / Recommendations Facts & Assumptions / Intermediate Analysis 72 7 Electricity Consumption The electric load used the analysis is a synthetic file created from an amalgam of several sources. •Time series data from 2020 Feb 11 –2020 Mar 8 was used to create the diurnal profile. •Monthly data from 2011 was used to create the seasonal profile •The annual consumption was scaled to the average annual total production reported in 2017-2019 Power Cost Equalization (PCE) reports, 5,844,050 kWh. •The “random variability” feature in HOMER was used to add “noise” to the load file, thus creating a (hopefully) more realistic file. •Near to medium term load growth (due to population increase) is not anticipated. This analysis assumed no load growth over the analysis period Total Annual Production (kWh)5,844,050 Peak Load (kW)1,154 Average Load (kW)667 Minimum Load (kW)295 73 8 Electricity Consumption 74 9 Diesel Fuel Consumption & Cost The table on the next slide summarizes fuel consumption and cost data for the past few years. •Average fuel consumption 2017-2019: 424,000 gallons •Average fuel cost 2012-2019: $2.90/gal ($0.77/L) The analysis included a sensitivity analysis on fuel cost. Sensitivity analysis was conducted using a fuel cost of $0.75/L and $1.00/L 75 10 Diesel Fuel Consumption & Cost Year Cost ($/gal)Cost ($/L) Annual Consump. (Gal) 2009 $4.34 $1.15 2010 $4.34 $1.15 2011 Data Unavailable 2012 $1.54 $0.41 2013 $3.70 $0.98 2014 $3.67 $0.97 2015 $3.89 $1.03 2016 $3.02 $0.80 2017 $2.56 $0.68 412,940 2018 $2.24 $0.59 423,289 2019 $2.55 $0.67 436,224 Average 2009-2019 $3.19 $0.84 Average 2012-2019 $2.90 $0.77 76 11 Heating Load The power plant does include a waste heat recovery loop that provides supplemental hear to several community facilities. It appears that the utility does not bill for this provided heat. Due to a couple of hurdles, the use of waste heat to serve thermal loads was not considered in the analysis. Waste heat production will be reduced to the extent that the generators are run less often and at lower loads. Since the utility is not reimbursed for provided heat, less recovered heat will not impact the utility’s bottom line. It will impact the entities that have been receiving waste heat. In this particulate case the impacts are anticipated to be small because the reduction in waste heat occurs mostly in the summer. 77 12 Generators The Galena power plant currently has six generators, ranging in size from 500 kW – 1050 kW. It is planned to shortly replace two of the generators with smaller models rated at 280 kW and 320 kW respectively. The analysis modeled three generators with rated capacities of 1050 kW, 600 kW, & 280 kW, respectively. The table on the next page summarizes the generator characteristics used for the analysis. 78 13 Generator Summary Label Make & Model Rated Power (kW) Replace. Cost ($) O&M Cost ($/hr) No Load Fuel Consum. (L/hr) (Gal/hr) Marginal Fuel Consum. (L/kWh) (Gal/kWh) Lifetime (Hours) Gen 1050 Caterpillar 3512A 1050 kW $732,000 $20.86 14.7 L/hr 3.9 gal/hr 0.240 L/kWh 0.064 gal/kwh 90,000 Gen 600 Caterpillar 3512A 600 kW $470,00 $18.16 8.4 L/hr 2.2 gal/hr 0.244 L/kWh 0.064 gal/kwh 90,000 Gen 280 Detroit Diesel Series 60 280 kW $283,000 $16.24 3.9 L/hr 1.0 gal/hr 0.244 L/kWh 0.064 gal/kwh 60,000 Notes: •The analysis treats the generators as “sunk” costs. Thus their capital cost is $0. The values for replacement and O&M costs are highly uncertain. The values for replacement cost are based on estimated costs for the two replacement generators given in the “City of Galena: Power Plant History” PowerPoint file. •No load fuel consumption: 0.014 liters/hr/kWr (0.0037 gal/hr/kWr) 79 14 Dispatch Strategy & Reserve Requirements The analysis examined both the load following and cycle charging dispatch strategies. To cover intra -hour variations in load and renewable energy output the following operational reserve requirements were imposed: •10% of the load •50% of the PV production The operational (spinning) reserve is the sum of the above items. For example if, in a given time step, the load is 100 kW and PV production is 50 kW, the operational reserve requirement is 100 kW * 0.1 + 50 kW * 0.5 = 35 kW. 80 15 Photovoltaics PV o Capital cost: $2,750 / kWdc o Replacement cost: 66% of capital cost o O&M: $20/kW/year o Azimuth: 180°deg (south) o Tilt: 45° General comment o The PV panels will likely be bifacial. HOMER cannot model bifacial panels directly. They were modeled by reducing the loss factors so that PV production was increased by 10%. 81 16 Converter/Battery Batteries (Li-Ion): o Capital cost: $45,000 (fixed costs) + $630/kWh (up to 200 kWh) + $432/kWh (> 200 kWh) o Replacement cost: 80% of capital cost o O&M cost (annulal): 2% of capital cost o Lifetime: 3,000 kWh per kWh of storage capacity Converter: o Capital cost: $45,000 (fixed costs) + $788/kW (up to 160 kW) + $540/kW (> 160 kW) o Replacement cost: 80% of capital cost o O&M (annual): 1% of capital cost o Lifetime: 15 years o Inverter efficiency: 95% o Rectifier efficiency: 95% General comment o The PV array and battary are assumed to NOT be DC coupled. 82 17 Solar Resource Annual Average: 2.56 kWh/m2/day 83 18 Model Financial Inputs •Analysis period: 25 years (Expected PV array lifetime. This is a conservative assumption. The panels will most likely last 30+ years) •Real discount rate: 4% •Inflation rate: 2% 84 19 Model Description -HOMER •Hybrid Optimization Model for Electric Renewables (HOMER) •Commercially available micro-grid simulation and optimization software http://www.homerenergy.com/ •Calculates energy balance for every time step (typically an hour) for entire year o Load must be met from some combination of grid purchases, on-site generation, or discharge from storage o Does not consider power flow or transient effects •Technology modules based on empirical operating data •Finds optimal technology sizes and optimal dispatch strategy subject to resource, operating, and goal constraints •Objective function is to minimize life-cycle cost of energy •Two available optimization methods o HOMER proprietary optimizer o “Search space”: For each decision variable, the user enters the value(s) to simulate. HOMER will simulate every combination of values. 85 20 Search Space Each battery (100 LI) string represents 100 kWh of storage capacity 86 NREL | 21 Background / Purpose / Approach Results / Conclusions / Recommendations Facts & Assumptions / Intermediate Analysis 87 22 Decision Variables PV capacity Converter capacity (kW) Battery storage capacity (kWh) Diesel dispatch strategy (load following or cycle charging) The decision variables are items for which the model selects the values. 88 23 Results –Bottom Line Up Front For the proposed retrofit system. the Galena has a choice between two broad approaches, no-storage and storage. •Assuming a no-storage system, the recommended configuration consists of a PV array of 500-750 kWdc. Under both the low and high cost fuel sensitivities, the optimal no-storage system has a lower life cycle cost (referred to as Net Present Cost [NPC] in the HOMER results) than the optimal system with storage. The big disadvantage of a no-storage system is that it does not allow for diesel-off operation. •Assuming a system with storage, the recommended configuration consists of a minimum of 1,000 kWdc of PV, 600 kWh of storage, and a 600-kW converter. For the low-cost fuel case this is not the lowest NPC system with storage but is the smallest system that will allow for significant diesel-off time. The disadvantage of this approach is that is more costly (on an NPC basis) than the no-storage approach. This disadvantage can be mitigated with additional grant funds. 89 24 Observations / Conclusions •If storage is to be included, the recommended minimum converter capacity is 500-600 kW. This value is based less on the analysis results and more on what this analyst considers to be good practice. This is large enough to cover most of the summer-time load, thus allowing diesel-off operations. Interestingly, increasing the converter capacity beyond 600 kW does not improve performance (in terms of reduced fuel consumption, or more diesel-off time) at all. •Adding storage results in a modest decrease in fuel consumption compared to the no- storage case. For example with a 1,500 kWdc PV array, adding storage reduces annual fuel consumption from 328,000 gallons to 315,000 gallons. •A minimum PV capacity of 1000 kWdc is required to achieve significant diesel-off time. Increasing the PV capacity from 750 kW to 1000 kW increases the annual diesel-off time from under 40 hours to just over 600 hours. Increasing the PV array capacity to 1,500 kWdc increases the annual diesel-off time to over 1,000 hours. •If the retrofit includes storage, the preferred dispatch strategy is cycle charging. Under this strategy, if a diesel generator is dispatched, it will charge the battery in addition to meeting the load. 90 25 Observations / Conclusions (Low Fuel Cost) •Under the low fuel cost sensitivity the lowest Net Present Cost (NPC) retrofit is adding 500 kWdc of PV and no storage. This configuration has a 25-year NPC of $21,010,000. (NOTE 1: the modeled NPCs are relative, not absolute.) (NOTE 2: The NPCs do not account for any grant funding. Any grant funding received can be directly subtracted from the NPC) This estimated capital cost is $1,400,000, so it could be covered by the existing USDA grant. In taking the no-storage route the community should purchase the largest PV system it can get (up to ~750 kWdc) with the existing grant. •The lowest NPC retrofit with storage (that makes engineering sense) consists of 500 kWdc of PV, a 600-kW converter, and 300 kWh of storage. This configuration has a 25- year NPC of $21,560,000 and an initial capital cost of $2,000,000. While this is the lowest NPC system with storage, this analyst recommends consideration of a configuration with additional PV and storage. Specifically, this analyst recommends a minimum of 1000 kWdc of PV and 600 kWh of storage. This would allow for significant diesel-off time. 91 26 Observations / Conclusions (High Fuel Cost) •Under the high fuel cost sensitivity the lowest Net Present Cost (NPC) retrofit is adding 750 kWdc of PV and no storage. This configuration has a 25-year NPC of $26,418,390. (NOTE 1: the modeled NPCs are relative, not absolute.) (NOTE 2: The NPCs do not account for any grant funding. Any grant funding received can be directly subtracted from the NPC) This estimated capital cost is $2,000,000. •The lowest NPC retrofit with storage (that makes engineering sense) consists of 1,000 kWdc of PV, a 600-kW converter, and 300 kWh of storage. This configuration has a 25- year NPC of $26,593,790 and an initial capital cost of $3,500,000. This system has the minimum size PV, Storage, and Converter that allow for significant (600 hours in this case) diesel-off time. The community may want to consider additional PV and storage to enable additional diesel-off time. 92 27 Observations / Conclusions The following table and figures further illustrate the points discussed here. The systems with storage include a 600-kW converter and either 300 kWh or 600 kWh of storage These systems are generally the lowest NPC systems, (for the given PV array size) that include a converter with a minimum capacity of 600 kW. Model outputs include both physical metrics (e.g. PV production, fuel consumption etc.) and financial metrics (Net Present Cost [NPC], O&M, etc.). For a given configuration the physical metrics are the same (or should be the same) regardless of fuel cost. •The base case (no PV and no storage) shows a fuel consumption of 402,000 gallons. This compares with 2017 actual consumption (adjusted for the difference in annual production) of 434,000 gallons. This indicates that the modeled fuel consumption values are about 7%-8% low. •In the no-storage case the quantity of excess (spilled) electricity increases rapidly for PV array sizes larger than 750 kWdc. Based on these results, 750 kWdc is a reasonable upper bound for the PV array capacity in the no-storage case. 93 28 Notes on Tables & Charts Configurations with Storage •All systems with storage include 600 kW of converter capacity Configurations with storage (Low cost fuel) •Systems up to 750 kWdc of PV capacity have 300 kWh of storage •Systems with > 750 kWdc of PV capacity have 600 kWh of storage Configurations with Storage (High cost fuel) •Systems up to 500 kWdc of PV capacity have 300 kWh of storage •Systems with > 500 kWdc of PV capacity have 600 kWh of storage The charts all show the results for the low-cost fuel sensitivity. 94 29 Conceptual Design Comparisons (Low-cost fuel) PV (kW)PV (kW)0 250 500 750 1000 1250 1500 NPC ($)Storage $21,633,450 $21,563,160 $21,577,440 $21,614,950 $21,788,240 $22,090,010 No Storage $21,062,660 $21,020,870 $21,009,870 $21,126,130 $21,377,150 $21,725,170 $22,095,040 COE ($)Storage $0.235 $0.234 $0.234 $0.235 $0.237 $0.240 No Storage $0.229 $0.228 $0.228 $0.230 $0.232 $0.236 $0.240 Initial capital ($)Storage $1,309,300 $1,996,800 $2,684,300 $3,501,400 $4,188,900 $4,876,400 No Storage $0 $687,500 $1,375,000 $2,062,500 $2,750,000 $3,437,500 $4,125,000 Ren Frac (%)Storage 4.4 8.9 12.9 16.6 19.4 21.5 No Storage 0.0 4.5 8.8 12.4 15.1 17.3 19.2 Total Gen Run Hours Storage 8,760 8,760 8,723 8,156 7,898 7,690 No Storage 8,930 8,905 8,897 8,889 8,884 8,852 8,769 Diesel Off Hours Storage 0 0 37 604 862 1,070 No Storage 0 0 0 0 0 0 0 Total Fuel (Gal/yr)Storage 383,073 365,571 350,003 334,366 323,383 314,783 No Storage 402,485 385,342 368,814 355,049 344,281 335,690 327,925 % Fuel Use Storage 95.2%90.8%87.0%83.1%80.3%78.2% No Storage 100.0%95.7%91.6%88.2%85.5%83.4%81.5% Excess Elec (%)Storage 0.0 0.0 0.6 1.2 2.9 5.1 No Storage 0.0 0.0 0.2 1.1 2.8 4.9 7.2 Excess Elec (kWh/yr)Storage 0 1,709 32,343 72,371 174,915 313,216 No Storage 0 0 10,493 64,852 167,032 302,459 452,254 PV Production (kWh/yr)Storage 0 262,666 525,331 787,997 1,050,663 1,313,328 1,575,994 No Storage 0 262,666 525,331 787,997 1,050,663 1,313,328 1,575,994 Operating cost ($/yr)Storage $1,290,226 $1,242,120 $1,199,382 $1,149,892 $1,117,249 $1,092,761 No Storage $1,337,109 $1,290,812 $1,246,469 $1,210,205 $1,182,496 $1,160,945 $1,140,781 Fuel cost ($/yr)Storage $1,087,448 $1,037,766 $993,572 $949,180 $918,002 $893,590 No Storage $1,142,554 $1,093,891 $1,046,971 $1,007,896 $977,327 $952,939 $930,896 O&M ($/yr)Storage $184,197 $187,713 $190,927 $187,354 $187,315 $188,388 No Storage $180,192 $183,908 $187,866 $191,854 $195,823 $199,538 $202,38595 30 Conceptual Design Comparisons (High-cost fuel) PV (kW)PV (kW)0 250 500 750 1000 1250 1500 NPC ($)Storage $27,338,780 $27,007,320 $26,777,150 $26,593,790 $26,603,670 $26,775,080 No Storage $27,061,980 $26,764,680 $26,507,310 $26,418,390 $26,508,900 $26,728,850 $26,982,980 COE ($)Storage $0.297 $0.293 $0.291 $0.289 $0.289 $0.291 No Storage $0.294 $0.297 $0.293 $0.291 $0.289 $0.289 $0.291 Initial capital ($)Storage $1,309,300 $1,996,800 $2,813,900 $3,501,400 $4,188,900 $4,876,400 No Storage $0 $687,500 $1,375,000 $2,062,500 $2,750,000 $3,437,500 $4,125,000 Ren Frac (%)Storage 4.4 8.9 13.1 16.6 19.3 21.5 No Storage 0.0 4.5 8.8 12.4 15.1 17.3 19.2 Total Gen Run Hours Storage 8,760 8,760 8,430 8,156 7,898 7,690 No Storage 8,930 8,905 8,897 8,889 8,884 8,852 8,769 Diesel Off Hours Storage 0 0 330 604 862 1,070 No Storage 0 0 0 0 0 0 0 Total Fuel (Gal/yr)Storage 383,053 365,551 348,234 334,332 323,354 314,738 No Storage 402,485 385,342 368,814 355,049 344,281 335,690 327,925 % Fuel Use Storage 95.1%90.8%86.5%83.0%80.3%78.2% No Storage 100.0%95.7%91.6%88.2%85.5%83.4%81.5% Excess Elec (%)Storage 0.0 0.0 0.2 1.2 2.9 5.1 No Storage 0.0 0.0 0.2 1.1 2.8 4.9 7.2 Excess Elec (kWh/yr)Storage 0 1,709 12,877 72,326 174,869 312,947 No Storage 0 0 10,493 64,852 167,032 302,459 452,254 PV Production (kWh/yr)Storage 0 262,666 525,331 787,997 1,050,663 1,313,328 1,575,994 No Storage 0 262,666 525,331 787,997 1,050,663 1,313,328 1,575,994 Operating cost ($/yr)Storage $1,652,414 $1,587,728 $1,521,245 $1,465,960 $1,422,944 $1,390,181 No Storage $1,717,960 $1,655,442 $1,595,459 $1,546,170 $1,508,272 $1,478,591 $1,451,080 Fuel cost ($/yr)Storage $1,449,855 $1,383,608 $1,318,064 $1,265,445 $1,223,893 $1,191,282 No Storage $1,523,405 $1,458,521 $1,395,961 $1,343,861 $1,303,103 $1,270,585 $1,241,195 O&M ($/yr)Storage $184,096 $187,611 $190,927 $187,354 $187,315 $188,388 No Storage $184,096 $187,611 $187,737 $187,199 $187,142 $188,211 $202,38596 31 Excess Energy vs. PV Capacity 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000 0 200 400 600 800 1000 1200 1400 1600Excess Electricity (kWh/year)PV Capacity (kWdc) Excess Electricity Storage No Storage All systems include a 600-kW converter Systems up to 750 kWdc of PV include 300 kWh of storage Systems > 750 kWdc of PV include 600 kWh or storage 97 32 Fuel Consumption vs. PV Capacity 200,000 250,000 300,000 350,000 400,000 450,000 0 200 400 600 800 1000 1200 1400 1600Fuel Consumption (Gal/year)PV Capacity (kWdc) Fuel Consumption Storage No Storage All systems include a 600-kW converter Systems up to 750 kWdc of PV include 300 kWh of storage Systems > 750 kWdc of PV include 600 kWh or storage 98 33 Renewable Fraction vs. PV Capacity 0.0 5.0 10.0 15.0 20.0 25.0 0 200 400 600 800 1000 1200 1400 1600Renewable Fraction (%)PV Capacity (kWdc) Renewable Fraction Storage No Storage All systems include a 600-kW converter Systems up to 750 kWdc of PV include 300 kWh of storage Systems > 750 kWdc of PV include 600 kWh or storage 99 34 Diesel-Off Time vs. PV Capacity 0 200 400 600 800 1,000 1,200 0 200 400 600 800 1000 1200 1400 1600Diesel Off (Hours)PV Capacity (kWdc) Diesel Off All systems include a 600-kW converter Systems up to 750 kWdc of PV include 300 kWh of storage Systems > 750 kWdc of PV include 600 kWh or storage 100 www.nrel.gov Thank You This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Indian Energy. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.101 Federal Financial Report (Follow form lnstructions) OMB Number: 4040-0014 Expiration Date: 01/3 1/2019 1. Federal Agency and Organizational Element to Which Report is Submitted Rula] Ut-iliries Service 2. FederalGrant or Other ldentirying Number Assigned by Federal Agency (To repon rnultple grants, use FFR Attachment) 68-A8 4 3. Recipient Organizalion (Name and complete address including zip code) Recipjent Organization Name: Streetl: Street2: City: State: Country: r49 Provincei UNITED STATES ZIP / Postal Code:97 414r49 4a. DUNS Number 2341395 4b. EIN 92-4444429 5. Recipient Account Number or ldentifying Number (To repod multiple grants, use FFR Attachment) 68-A84 6. Repon Type X Quarterly n Semi-Annual n Annual E Final 7. Basis of Accounting I casn n Accrual 8. Projecvcrant Period Frcm: To: L Repoding Pedod End Date 12 / 31/ 2AL8 10. Thnaactions Cumulative (Use lines a-c fot single or muniple gnnt Epotting) Fedg.al Cash (To .eport multlple g.ants, also usg FFR attachment): a. Cash Receipts 0.0c b. Cash Disbursements 0.0c c. Cash on Hand (line a minus b)0.0c (Use lines d-o for single grant rcpoding) Fqderal Expenditures and Unobligaled Balance: d. Total Federal funds authorized 1,500,000.00 e. Federal share of exDenditures 0.00 f. Federal share of unlrquidated obligations 0-00 g. Total Federal share (sum of Iines e and 0 0.00 h. Unobligated balance of Federal Funds (line d minus g)1,500,000.00 Recipient Share: i. Total reciplent share required 2,964, A92 .A j. Recipient share of expenditures 0.0 k. Remaining recipient share to be provided (line i minus j)2 ,964, O92.04 Program Income: l- Total Federal program income earned 0. 00 m. Program Income expended in accordance with the deduction alternative 0.00 n. Program Income expended in accordance with the addition alternative 0. c0 o. unexpended program income (line I minus line m or line n)0. 00 102 b. Rate c. Period From Period To d. Base f. Federal Share 12. Rema*s: Attadl any exphndions deemed necessary or infomation EquiBd by Federaf q@gf,dng agcncy in compliance with govemi.tg logistati@: 13. Cenification: By slgnlng this r€po4 | cadify that lt is true, comploto, and rccunte to the bost ot my knowledge. I am awrre that any fabe, fic0dous, or t6uduleni infonnation may subjsct ma to criml.lal, clvil o. admlnistrative p€oahigs. (U.S. Code, TlUe 18, s€ctlon l00l) a. Name and Title of Authorlzed Certirying Oftcial Prefr: j"]l---l Sufrx: c. Telephone (Area code, number and extension) 90?-656-r301 Standard Form 425 103 Unlted Stat$ Dopaftrent of Agticultu|€ Rural Utllldos sorvlcs Asslstanco to Rural Communldos wlth Exttemely High Enorgy Co3t3 Grant Agrcoment 1.THIS GRANT AGREEMENT (Ag|€smont) dated Septemb€r 21, 201E, ls an agreement for receipt of Hlgh En€rgy Cost grEnt tunds under 3€ction 19 of the Rural Electriflcation Act of '1936, as amended (7 U.S.C. 918a), belnoen ttre Uniled Stateg of America, ading through the Admlnistrator of the Rural Utiliti€s Servics (RUS), Unibd Slatea Department of Agriculture (USDA), (Grantor) and the City of Galena, Alasks (Grantee) for lhe purposes of satisfactorily performing tho Grant Project as descrhed below. The Grantor agrees to award to the Grantoe this High Energy Cost Grant (Grant Award) In the amount of$1,500,000 subject to tha termg and conditlone ae establiehed by lhe Grantor. Should adual prdsct coot8 be loner than pojeded in lhis agreomanl' the amount of the grant shall be adjusted to refloct tho lowor amount. The Grant Project descrlbed es the Solar BEttery Storage In tho Grar 36's application package submitted In respons€ to the FY 2017 Notlce of Funding Avallablllty publlEhod on Octobor 12, 2017 (E2 FR 47446) (NoSA), Includlng any sub8€quont amerdmgnts 0r submisslons, ls incorporatod and lncludcd as part of thls agrB6ment by reference and is horeby approv€d by RUS subj€ot to any Special Conditiom o. LlmltationE a3 set forth below. In consideration of this Granl Award, the Granlee agrees that it will use the Granl Award only for the Grant Project and only eliglble projects and activiti63 dofined and set forth in the NO-SA and sootlon 19of tho Rural Electriflcation Aol (7 U.S'C. 918a)' and RUS Assistence to Hbh Enorgy Cost Rural Communitiee program regulations at 7 CFR part 1709' The Grantee agrees that it shall submit, in writing lo RUS, and thal it thall obtain p of writlen approvtl by RUS for any mat€rial change to tho adiviti€s or scope of the Grant Project, in;luding -ny material change to the projeGl design, proied management' !u-dget. or communities io bi served as set forth by tho Granteo In lts Grant Project for this Hlgh Energy Cost Grant This Grant Award ie governed by and the Grantee agrees that it shall comply with all applicable F€doral statutes, regulations, and roquirements that govern ths applioatlon, acceptanca, and uso of Federal Grant funds for thle Grant Project. 4. 104 City of Galena High Energy Cost Grant Agreement 4K0068-.A84 September 21, 2018 7.This Grant Award is governed by and tho Grantee agrees to @mfly wlth all applioable provisions of the following or their Euocossors: U. S. Department of Agriculture Regulations for Grants and Agreements, 2 CFR parts 400 to 422; Assistance to High Enorgy co€t Communities, 7 CFR pari 1709; Otfic€ of Management and Budggt, Uniform Administrativ€ Requirements, Coet Principles, and Audil Requiramenls for Federal Awards, 2 CFR part 2oo; New Restrictions on Lobbying, 2 CFR part418; Government'Wide RequiremEnts for Drug-Free Workplace (Financial Assisiancs), 2 CFR par. 421; and Non Procurement Debarment and Suspension, 2 CFR parl417 and 2 CFR part 180' The Grantee acknowledgos and agrees to the followlng Sp3clal Conditiono establish8d for this Grant: 8.1. The Grantee shall carry out the proiecl oonstrudion aclivities as desqibed in the Grant Project, environmental review, and supporting documants with any subsequent amendments or revisions as approved by RUS, 8.2. The Grantee shallsubmit a proppeod prdoct implomentation plan including a proposed project schedule, propoeed performanct moasur€8, key pe|tonnel, and a proposed frolect budget induding any changss slno€ the submission of lho proloct bpplication foi RUS review and approval. Please ldentlfi, as part of thls dan, the nalure . ahd timing for oontribuling the match funding to the proiect. Tho projeot implementation plan must be approved in writing by RUS bofore any r€quest for reimbursomer or advance of funds will irb approved. Thl Grantee wlll immodiately nofiry RUS In writing of any changos in prdect design, schedule, key pelsonnel, or budget, 8.3. The Grantee shall obtaln all nocassary pamlts, llcens68, oasements, and rights of way for constructlon and oporatlon of the Grant and shall incorporale any Propoe€d mitlgauon lnto the projeot to ofbet potentisl impaots to tho environment or cultural resources. The Granteo shall oontaot tho RUS Engineering and Environmental staff immedistely if any subsequent changes are proposed related to the prcjects scope prior to or during construction so thal lhey may determlne if futther Agency environ'm6ntal review and approval of the revisad project are nocg38ary 8.4. The Granl term will run for thr68 y€ars from the dale of the Grant agreemont' 8.5. Thig Grant Award rBquir€s matoh funding in the amount of $3,000,000 In local oontributions which are to be idEntified and committed prior to the first advance of funds under this grant. The Grantso reporting shall ensure that a full description of lhe nature and cost of the match contribution is included as part of the ov€rall projeot implementatlon and cost tracking. RUS reserves the right to wlthhold grant dlsbursements pending conflrmatlon of match contributions consistent wlth the lmplementation Plan. 8.6, Tho Grant Award may be used for advances and reimbursements of eligible projoot costs as provided in program regulations at 7 CFR part 1709and 2 CFR part200' incLuding ellgiblo pro-award project costs, wher€ advances are limitsd to expenditures to be made within 30 days follo/ving the advance. Preaward expenditures may bo roimbursed Page 2 of 6 105 Clty of Galena High Energy Cost Grant Agreement AK0068-484 September 21, 2018 under cerlain circumstances wh6ro tho6o exponditures are included in the budgat approved in writing by RUS. 8.7. The Grantee shall rsquest drews under lhe grant in writing from RUS ueing Form SF 271 "outlay Report and Requegt for Roimbursemonl for Construction Programs" and supporting doCumentation. RUS will approv€ the advance or reimbursement for eliglble granl activities over the term of the Granl. 8.8. The GrantEe shall providB periodic reports as requhed by the Grantor. Quarterly Reporls: The Granteo shell report on lhe expendlturs of Grant Funds and any non-Federal project funds or matchlng contrlbutlone In quarlerly flnanclal and progress and performanc€ nanativo r€ports during tho term of the grant. Th€ Granteo 8hall attaoh Form SF 425 "Federal Financlal Report' to thoso reports. Quarlorly reports shall be due 30 days from the end of each quarter endlng Maroh 31, June 30, September 90, and December 31 of each year. Each quarterly report shall a narrative description of project lmplementation actions conpleled during the period. Final Construction Exponditure Report: Tho quarterly roporl filed after construc'tion has beon completed and all projeot construotion expendltures finallzed shall serve aa the final construction expenditu16 report. Annual Reporl: The last quarterly report of each cal€ndar y€ar ehall serve as the projeo't annual rgporl. Final Project Reporl; The Grantee thall provldo RUS with aflnal projeot report dgtailing project perfoimance, final proiect expenditures, and one full year of operaling data including energy produced, fuel savings, end/or cost savlngs assoclatad with the project, and community beneflts, This report shall lndudo data whlch domonstratBs whether the followlng p€rlormance objectives listed In the grant appllcatlon have been met: a, Heat recovsry on one dieeel engine (475 kW) in the powerhouse, which is expected to save approximately 5,000 gallons of diesel fuel annually.6. A 1.25 MW hlgh penelration solar photovolteic batlery - diosel hybrid syslem utilizlng a grid-formlng bi-directional Invertor to allow for "di6sols-off' oporqtion for approximataly 18% of the tim€ on an annual basis.c. Eiectricity ourr€ntly sell6 tor $0.67ftWh for resldential rate payers, and b provldod by the City-owned elechic utllity, running on diosel gonerator 8€18, this project i8 eipected to lower the production oost of electricity by at leasl 4 cents/kWh. At the written requsst of th€ Grante€, RUS may extend the period for filing quarterly, annual, and final reportb. 8.9. The Grantee shall provide bondlng and Insurance coverage for the projecl as described In the Granl Project and consbtenl wlth its own praclices and 2 CFR Part 200, or its successors, as applicable. 8.10. The Grantee shall submit to RUS a copy of an audit prepared ln accoldanco with RUS fegulations on audit requirem€nts at 7 CFR section 1709'21 and conslst€nt with Page 3 of 6 106 City of Galona Hlgh Energy Cost Grant Agreemont 4K0068-484 September 21, 2018 subpart F cif 2 CFR Part 200 for any flsoal yaar In whloh lt expends $750,000 or more in Federal Grant Funds. This Grant Award and the obligation of RUS to advance this Grant Award or any portion of this Grant Award shall €xpiro three years from the date hereof (Expiration Date). No portion of this Grant Award wlll bo advanced by RUS to th€ Grantee aller the Expirallon Dale. RUS, in its sole discretion, may approve an oxtenEion of the Explratlon Dats provlded thal the Granlee notilies RuS, ln wrillng prlorto the Explratlon Date, of the reasons and noed for an extension, together wlth a suggesled revlsed Exphation D5te. This Agreement may be suspended in accordance wlth 2 CFR S200.238 for failure to comply with Federal stalutes, regulations or the torms and oonditions of a Federal award. This Agroomont may be telminatcd for cause in accordance with 2 CFR Section 200.339 in the event of failure of the dofault on the part of the Grantee or for convenience of the Grantor and Grantee prior to the date of oompletion of the grant purposo. Termination for conveniencs will occur when both the Granteo and Grantor agroe in wrltlng that the continuation of the Granl Project wlll nol produce benefiolal result8 comm€nsuratg with the furlher expenditure of funds. RUS and the Grantee agree that this Agreement sets forth the entire undorstanding of lhe parti$ and may be modified or amended only by a Mitten instrumenl duly oxecuted by bolh RUS and the Grantee. Pursuant to 41 U.S.C. 22, no member of, of delegate to, Congress ehall be admitted to any shar6 or part of this Glant Agroemont or lo any.bsnefil to ariso lhorefrom' This Grant award is subjecl to tho following: 13.'l The Grsntee shall not require its employees, contractors, or subrecipients s66king to report fraud, wasle, or abuse to sign or oomply with Internal contidsntlality agr€em€nte_or statements prohibitlng or othenrvise reetricting them from lawfully reporting that waste, fraud or abuse to a designat€d investlgatlvE or law enforcsmenl representativo of a Federal department or agoncy authorized to recelve such information. 13.2 The Grantee must notify its employees, contractors, or subrecipients that the prohibitions and restdctions of any internal confldontialily agreemenls Inconglstent with paragraph (a) of thls Section are no longer ln effect. 13,3 The prohlbition in paragraph (a) of this section does not conlravene requirem€nts applicable to any other form issued by a Federal department or agency governing the nondisolosure of classified informailon. 13.4 lf the Agency detemines that the Granloe ie not in complianoe with the provisions of this Section, it: 10. 1',I. 12. 13. Page 4 of 6 107 Clty of Galena High Energy Cost Grant Agreemont AK006E-A84 Soptember21,2018 13.4(a) will prohibit the Granteo's use of Grant funds, in accordance with sections 743, 744 of Division E of the Consolidated Appropriations Act, 2016 (Pub. L. 1'14-113) or any successor Drovision of law: and 13.4(b) may pursue other remedies available for the Grantee's materialfallure to comply with award terms and condltions. 14. By executing this Grant Agreem6nt, the Granteo affirms and ratifies all slatements, representations, and wrilten documsnts that it has submitted to RUS related to this Grant Project. 15. RUS or the Grantoe may withdraw ils obligation to provide this Grant Award if the Grantee does not sign and deliver this Grant Agreement to RUS on or before 180 days from the date of this Grant Agreement. 16. This Grant Agroemenl may be executed in several counterparts, each of which shall be deemed lo b€ an original. 17. In meking thls Grant Award, RUS ls under no obligation to provide further federal financial assistance or other support to the Grantee. Page 5 of 6 108 AA Cliy of Galena Hbh Enoqy cost Grant Agr€emerd AK0fft&484 Scptamba 21, 2018 Th€ Grantee afirms, eol€ias, end accails all t€rms and cordluone of ttls Grant Avrard a3 stat€d In thl8 Grant Agreemsnt. lN WITNESS WHEREOF, the partl€s herdo hsus oaus€d thls Agr€smont b ba duly 6xtcuted as of t|o day and yeer fi]El abs€ wrl[6n. CIW OFGALENA, ALASI(A Namc: ritle: tVl Af o( UNITED STATES OF AI'ERJCA Dana Pot€rgon AEilng chlofofSffi Rural Utillflee Servlce Page I of 5 109 a City of Galena High EncEy Cod Grant AgEom€nt AKm6&A84 Ssptember 21, 2018 The Grant€€ affrms, agree8, and acceptE all tenna and conditione of this Grant Auad ae stated in thie Grant Agrcemant" lN WTNESS WHEREOF, th6 parties herefio haw oaueed this Agrsoment to bc duly executed as of the day and yoar first aborc wtitbn. oF cAt Ft{\ ALASI(A UNITED STATES OF AMERICA By: Ading Chldof Staff USDA Rural Litiliti$ Seryice CITY By: - Page 6 of6 110 AK0068‐A84 City of Galena High Energy Cost Grant Agreement United States Department of Agriculture Rural Utilities Service Assistance to Rural Communities with Extremely High Energy Costs Amendment No. 1 to Grant Agreement THIS AMENDMENT (Amendment) dated as of August ____, 2021, amends the GRANT AGREEMENT (Agreement) dated September 21, 2018 for receipt of High Energy Cost grant funds under section 19 of the Rural Electrification Act of 1936, as amended (7 U.S.C. 918a), between the United States of America, acting through the Administrator of the Rural Utilities Service (RUS), United States Department of Agriculture (USDA), (Grantor) and the City of Galena, Alaska (Grantee). 1. Section 8.4 of the Agreement, is hereby amended to read, in its entirety, as follows: 8.4 The Grant Award and the obligation of RUS to advance this Grant Award or any portion of this Grant Award shall expire on September 21, 2024 (Expiration Date). No portion of this Grant Award will be advanced by RUS to the Grantee after the Expiration Date. 2. This provision of this Amendment No. 1 is the only change to the Agreement. All other terms and conditions of the original agreement shall remain in full force and effect. __________________________________ Signature of Authorized Grantee Official Name: Title: ____________________________________ Christopher A. McLean Acting Administrator USDA Rural Utilities Service 111