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Home My WebLink AboutPower Cost Equalization Funding Formula Review Technical Report March 2012no7re-7UNIVERSITY OF ALASKA ANCHORAGE ae INSTITUTE OF SOCIAL AND ECONOMIC RESEARCH POWER COST EQUALIZATION FUNDING FORMULA REVIEW Technical Report PREPARED By GINNY FAY,ALEJANDRA VILLALOBOS MELENDEZ TOBIAS SCHWOERER PREPARED FOR NATIONAL RENEWABLE ENERGY LABORATORY MARCH 2012 INSTITUTE OF SOCIAL AND ECONOMIC RESEARCH UNIVERSITY OF ALASKA ANCHORAGE 3211 PROVIDENCE DRIVE ANCHORAGE,ALASKA 99508 For information contact vfay@alaska.edu or 907-786-5402 Table of Contents Table of Figures and Tables ..........cccssseccecsecseessecssessssessssessussesseeeesesseeseessessessessesanssessaeneseeneeeensees 3 EX@CUtIVE SUIMMATLY........cscceccecsscessecesseceseteneerenesesesesssecenscecesdseeseaceeneasueenesesseeceeessesesesesseessnersneesaeeanes 5 Power Cost Equalization Program .........cccccsccssssssssssessscseseeceneecussaesasaressseersnnsessseaseseesssanersueessanasescaneneeesnees 5 ANALYSIS .....csscssccssecssccssscesscetsescnseesesseeseneteaeeeeeeeeeenesesesseesseeseeesueesuenedeseseeeeeesesenaeeneesssenseesseassnaseeennesnnesane®7 Alternative PCE funding formulas .............eesecsnesscersseesscessseseseseuscsesennscneeesaseseecssecsseeseessssesneeseesanessneesness 9 Other Policy Considerations...ee ee eesssessssssesesssessessecsssscsesenssensesnseensesnoeeeseeesnesssenseassssasenessuseenenenenness 10 INtrOGUCTION ........ceceescccessecsssneessaceeseseeessceessseceseseeeeeceeseseaecnseeecssdseseeeseccssseccuecensescesseacesaeesesatenenseees 13 Power Cost Equalization HistOry.........c.sccccssccescecsseecsseessnecccnssseenseecensssecseaseceeeseeseeseesereceneseneneeeses 14 Program IMplOEMENtation ..........sccsessesscccescecsscecesncecsssscssessssessssssesseessessesenseesssasesseeseneeesseresaneresseeeseneeens 16 Electricity Rates and Levels of CONSUMPTION..........cc ceeceecesteeseseeeeteeeeeceneeesteeseseseeceeeeeeseresecreneeeeees 21 How the current Power Cost Equalization funding formula WOrKS ........ccessescseseseteceeeeseeeseeneeees 26 AM AlYSIS ......cescccssscccsscccssecesnseeecssceecsaecessoeseseucesenecesseseseseeseceeeeceerensceeesseesesaeessdecesueesenseaneeeuasenenenes 28 impacts of PCE on efficiency,innovation and conservation iINCENTIVES.........esse ssesesestseseeseteeeseseneetees 28 General price and CONSUMPTION EFFECTS...ee eee eeeeseereeeereecesersseseneessescsssesusneusessecaeesseesseessusesesones 28 Fuel cost calculation @ffects..........ce escessssesscesereseeesecerseeereessecenseesneesreresesereserseesedensssseusseeesseeseeasseeseeeas 30 Renewable energy and electric heat 0.0...eee eseeseeseeerecesseeeeseeeserereceresesseeseseceeesneesddeesesesseseseseseneas 33 Distribution of renewable energy SaViNS ............ceseseccesecesessseeesecesecenecenacesecesceeeseseseesseeecerseeeseeneesees 36 Alternative PCE funding formulas ...........csescsseseseceseeceeeeeseneseeeseesasenececeeeneeseceenseseseeseoesseeetaneraersasenesens 37 Seasonal Fixed Payment FOrMula.............csccccessssccsessseccsestseecsesnaeecssstasecseseeecessaeecseseseeessuseeecsesenseseeges 39 Policy CONSIAErAatTIONS ...........cceseseseseseccecceceneasseneecccescansusssesececesecsacsauseesececcuenenassesseceeessecggssesseceeeeses 42 PCE Funding FOrmulla.............:scccsssccsssscsssscessncssseecsssecessaeessuecesssesesesessseseseeecesssessuasesenecenseseseseeeseecesanesesstess 43 Centralized versus disaggregated BENeratiOn...........cccscccsssccesscessseesssceesceeesnsesssssesscecensuessecesessateneneesnees 43 Expanding eligibility to CommMercial CUStOMELS ..........seccseseseceseccssnesesessseceseeesssesssecsteneucnstscsrscsnsvsnarseeesases 44 Increasing residential customer eligibility cap to 700 kWh per MOMtN...........ccceccsseseetseseessesesecesetssessees 45 REFEFENCES .o.eeseccceeccsceseesetesseseeseeseesceaecssesesseeseesssasessesecseseessusoesssssesssesssssssstenecseessenseseesaseeeceesananss 47 Appendix A.PCE funding levels per year .........ccccsscssccssessscssecsecssesssecesecesecscesessessescesscssesssesesesavenee 50 Appendix B.PCE appropriations and disbursements Over time..........cccccsssssssssssscesesevesseesseseaseee 51 Appendix C.Residential and effective rates of PCE communities,2001-2010 ..........cccceeeeseeens 52 -2-March 14,2012 Appendix D.Effective residential rates and consumption of electricity in PCE communities, 2008-2010 ue eeeecessceescceseceesneesneessecesseceueeseseesosecsescsascseueeuecessesseessaeeeseeseeeseeecaeecseeseasscsesseeusaeaees 53 Appendix F.PCE communities characteristics of importance as factors of electricity production AN CEMANA......eee eeeecseseceeeessessseesesecesseeescesecsnsssecsaesseessesssecseessessessessaseneesuseseeceueseseaeesesesseseneneees 54 Appendix G.Monthly Customer Payments under Current PCE Formula and Seasonal Fixed Payment FOrmula.........cccccsssccssccsssesssccssscsscssseecseeessecssecsseseseecsseseseseseeeeseseseeeseseseusaesausussaeesesseceeoes 67 Appendix H.Data sources and Methods..........cccccsscsssesssscessecsasessecesseeceeeseeecseseseteesesesseeseecaseseenesees 80 Power Cost Equalization program data ............::cccssscssssccssssssseseseccesesesssasessseasanecseecensuseneeceseeseeessnesessas 80 Other SOULCES 0...ee eeseceseecsesecscesetescesnescesssesseeseesesecsresscsnesessensessesaeeaeaasceaecaesenseseeucesasensensesseseesensenssssees 80 Data Quality...ce sccssccssssccsssscsssccssscssssncccssecsseesessseseseeessseeesrssssesessorevscssessseeeneseseasecesseessatesseesenseeasenesnars 80 Methods.........scssccscscssssssscssecssecsssessscsssseesseseessusssnsesscesnessusesusessscesusseasscesseaessaeenseesscoauscnnseaueceneusnessneasaseats 81 Appendix |.Map of Alaska Energy R@iOns...........sccsscsssccsssesssssssceesceesaecesceesesesseseeeessucesseseneesnecass 82 Table of Figures and Tables Table 1.Timing and characteristics of implemented power cost assistance ProgramMS..........scccseccccsseeesees 16 Figure 1.PCE appropriations,disbursements and distillate fuel oil prices per gallon in the electric sector OVEL THITC .ceecsscstesecssesceesceseessesesosenecesceseessssnssseesessuaeesssesssasessnasossesoeesesscscnnasssaneceseesessescenscosseconanssensenenaeas 18 Figure 2.Power sold,PCE eligible kWh and average residential monthly payment,1981 to 2010...........19 Figure 3.Power sold,PCE eligible kWh and average annual kWh sold per capita,1981 to 2010..............20 Table 2.Utilities/communities eligible and participating program,CY 2010.00...eeessesseeeceseeeeeteneenes 20 Table 3.Average Annual Residential Electricity Consumption and Rates,2008-2010...ee eeseeeeseees 21 Figure 4.Residential kWh sold in PCE COMMUNItICS.0...eee eeeeeeeresereseeevsaessesesssenscassneseasneesesessesenssones 22 Figure 5.Community Facilities kWh Sold in PCE COMMUNITIES .........cceescsesvereseesscsrevsnsesssrsesasensneustesteeaeses 22 Figure 6.Kilowatt hours sold by customer category and census region,CY 2010 .........cssssscsrsseresrssesereens 23 Figure 7.PCE eligible and non-eligible customers by region,CY 2010 ........cesssssssesesscssstecsseseseeeneessenseses 23 Figure 8.Average residential and effective rates of PCE communities by census region,CY2010............24 Table 3.Average consumption per customer per month in PCE communities,CY 2009 ..........ccceseereseeees 25 Figure 9.Seasonal changes of electricity consumption in PCE communities,CY 2009 ..........csesseeesereeres 26 Table 4.Minimum efficiency standards for electricity ZeMeration.............ccssccessnereseesseeeesteeeseessseeesneseees 27 Table 5.Example of PCE fuel costs calculations and its effects on renewable generation............cseeeees 31 Table 6.Sample PCE level calculation before and after integrating renewable energy..........sseeeeeeerers 31 Table 7.Example of effects on customers'bills from integrating renewables...........ssssesscseeneereseeceeees 33 Table 8.PCE and heat sales in high penetration SYStEMS........cccssesscsscssesersrersresssesseestesssseresecsssrsaseses 35 Table 9.Example of PCE savings distribution from integrating renewables ...........ssescscseeretetererreetesetees 36 Table 10.Example of PCE savings distribution from integrating renewables &excess capacity for heat .37 Table 11.Summary of incentive CffCHS..........csscssssscsessecseseeeseseetssseseesscessneetersecuseasesenessseseeserseessseseenerey 38 Table 12.Evaluation of reviewed formula structures based on reforming Criteria .........scssseeerereesers 39 Figure 10.Average annual PCE payment with respect to fuel prices .........-.esssseeesssesesesescessssceeeeeeacseneneaees 40 Table 13.Actual and estimated residential!disbursements by funding formula,CY 2009............sccseseees 41 -3-March 14,2012 Figure 11.Energy use in surveyed PCE communities by Category...cssessssessesrsceserstestestesssseesterseees 42 Figure 12.Average commercial consumption levels in PCE communities (500 KWh Cap)........eeseesereees 45 Figure 13.Average commercial consumption levels in PCE communities (700 KWh Cap)........:.sceseeeeeees 45 Acknowledgements We sincerely appreciate the time and effort of utility and program managers who met with us and shared information and insights.We also thank colleagues who gave us valuable feedback. Suggested citation: Fay,Ginny,Alejandra Villalobos Meléndez and Tobias Schworer,Power Cost Equalization Funding Formula Review,University of Alaska Anchorage,Institute of Social and Economic Research,prepared for the U.S.Department of Energy National Renewable Energy Laboratory,March 2012,82 pages. -4-March 14,2012 Executive Summary The purpose of this study is to examine the current Power Cost Equalization (PCE)program formula's impacts on incentives for implementation of energy efficiency and renewable energy measures.In addition,it examines if alternative formula structures might improve market signals that are more conducive to investment in energy efficiency and renewable energy in rural Alaska.As part of the analysis we also present information on the history of the PCE program and levels and patterns of electricity consumption across regions of Alaska. Alaska has large regional and intra-regional differences in energy consumption and prices that result from a number of factors including proximity to different types and quantities of resources,community population,remoteness,and transportation costs.Most communities in rural Alaska depend on volatile and high priced fossil fuels for the generation of electricity,space heating and transportation. The Alaska statewide weighted average residential rate for electricity (17.6 cents per kWh in CY2011)is substantially higher than the U.S.average of 11.8 cents per kWh (U.S.EIA,2012).Yet in Alaska the average residential rate per kWh is currently lower than in Hawaii (34.5 cents),New York (18.4 cents) and Connecticut (18.1 cents).Hidden in the Alaska statewide average is considerable variation with some communities paying less than the national average and some-generally those least able to afford it-paying among the highest in the country. The Railbelt and Southeast regions have the lowest average residential electric rates (Appendix |map). North Slope residentia!customers also have lower average rates because of access to natural gas and North Slope Borough energy payments in addition to PCE disbursements.Most other regions have rates two to three times as high as Alaska urban rates.Some communities with hydroelectric power have notably low rates but customers are not paying the full,true cost of power because the cost of construction was heavily subsidized by state and federal governments.In Table 3 (p.20)we present average annual residential electricity consumption and rates for different regions of Alaska. Power Cost Equalization Program The Power Cost Equalization program is a rural lifeline program with a funding formula tied to utility costs and rates thereby reducing electricity rates that residential customers and community facilities pay.The PCE program had two predecessors between FY1981 and FY1985,the Power Production Cost Assistance program and the Power Cost Assistance program;the current PCE was created in 1984.The PCE program has had only a few modifications over its almost 26 year life.Table 1 describes the differences across the programs,which in their basic structure and funding formulas are quite similar.In 2010,there were 190 communities that were eligible and participated in the PCE program. The responsibilities of administering the PCE program are divided between the Regulatory Commission of Alaska (RCA)'that evaluates utility eligibility and costs per kilowatt-hour (PCE level),and the Alaska ,Originally APUC,Alaska Public Utilities Commission. 5-March 14,2012 Energy Authority (AEA)?that determines the number of eligible kilowatt-hours (kWh)in order to calculate the appropriate payment and make the disbursement. A utility's PCE payment per kWh is determined by a formula that covers 95%of a utility's cost between a floor or base rate of currently 13.42 cents/kWh and a ceiling of currently $1,00/kWh.The base rate is equal to the average price per kWh in Anchorage,Fairbanks and Juneau and is adjusted annually.PCE disbursements per customer are limited to a 500 kWh per month for residential customers and 70kWh per month and resident for community facilities.The PCE rate is re-calculated for eligible utilities once a year by RCA.The PCE formula also includes efficiency and line loss standards.State and Federal government customers as well as commercial customers are not eligible for the PCE credit. Seven years after the PCE program was established,funding the program became a challenge as world oil prices sharply decreased,which lowered state revenues.Since inception,the program was not fully funded by the Legislature in 15 out of 25 fiscal years.However,per capita electricity consumption continued to steadily rise in the years of pro-rated funding. During 2009 summer months,less than 18%of eligible communities had average electricity consumption Jevels above the PCE cap.Most of the communities where average monthly consumption exceeded the 500 kWh cap were communities that have effective rates comparable to those in urban areas (e.g.,North Slope Borough communities)',have comparatively high incomes,and/or are located in southeast or southwest Alaska.Even during winter,about 60%of the PCE communities did not have average consumption above 500 kWh per month per customer.On average consumers that increase their levels of consumption by more than 10%during the winter months are those in communities where the effective rates*are below 30 cents per kWh. The average PCE utility generates less than 3,000 MWh per year;about 30%of the utilities generate less than 500 MWh and the smallest generate less than 30,000 kWh per year.By comparison,urban utilities (Anchorage and Fairbanks)generate over 1 million MWh per year.This means urban utilities produce over 300 times more power than the average PCE utility.This difference illustrates one of the challenges in providing electricity (and other public services)to rural residents.The lack of economies of scale leads to very costly electricity per unit produced.The fixed costs associated with operating an electric utility are large and if the number of customers and/or levels of consumption are small these costs must be spread over few customers and kilowatt-hours. Despite this challenge,the PCE program is fairly effective at bringing the first 500 kWh of residential electricity rates closer to Alaska urban rates.Communities with higher rates receive more relief,while regions with lower rates such as the North Slope receive lower levels of assistance. Originally APA,Alaska Power Authority *The North Slope Borough communities benefit from availability of natural gas in some of its communities and additional subsidies.Rate structure is a flat rate of about 15 cents per kWh for all communities in the borough.*Effective rate is the rate that the residential customer actually pays for the first 500 kWh consumed,(Residential Rate -PCE credit). -6-March 14,2012 Analysis There are four primary ways that the PCE program ultimately affects the price of electricity to rural residents,which in turn impacts efficiency,innovation and conservation incentives.One is a broad effect on prices and consumption.The second is the specific application of the current PCE formula as written in statute and applied by RCA.The third is how the application of the PCE formula affects s heat sales in high penetration (providing over 50%of power)renewable energy systems.The fourth is how the savings from integrating lower cost renewable resources is distributed among PCE eligible kWh,non- eligible kWh,and the PCE program. PCE lowers the price of electricity for eligible kilowatt-hours;hence it allows customers/households to purchase more electricity and utilities to supply more power than they would if they were paying the full market price.However,comparatively high electricity rates coupled with low cash incomes result in average per customer electricity consumption of less than 400 kWh -over 40%less than the urban Alaska average of 700 kWh.It appears that the primary effect of the PCE program is increasing the quality of life of rural residents rather than encouraging "excessive”use of electricity.Because effective PCE rates remain relatively high,the larger barrier to household investments in demand side energy efficiency is likely insufficient household income and capital to finance the upfront costs of these investments. For utilities,pressure from customers paying non-PCE rates (more than 50%of kWh,on average) probably overwhelms any effect of PCE to reduce the incentive to maximize generation efficiency in terms of kWh generated per gallon of diesel fuel.There are also generation efficiency and line loss standards that must be met in order to receive the full potential PCE level. While the high cost of electricity may override any incentives caused by the PCE funding formula,the PCE program does not address the fundamental barriers to improving energy efficiency.Because the formula currently used to calculate rates is directly tied to fuel costs,integrating alternative or renewable generation technologies could result in a lower PCE payment causing the effective electric rates to increase.Knowing how the PCE level will change requires an individual analysis for each utility and generation alternative because alternative sources of generation affect non-fuel costs (which are also considered in the PCE formula),hence the PCE level may increase,decrease or remain the same. The new PCE level depends on how the utility cost structure changes and by how much. A decline in fuel costs from the integration of renewable energy generation affects the PCE level calculations because in the formula the total fuel costs are divided by total kilowatt-hours sold,not just the kilowatts-hours sold that were generated using diesel fuel (see formula in text box below).At the time the current PCE formula was developed,all kWh were generated using diesel.Nowadays with over 30 renewable energy projects in rural Alaska,the current PCE formula incorrectly calculates the fuel cost component of the rate for hybrid generation systems.The larger the renewable generation,the lower the fuel cost per kWh that is used in the PCE formula to calculate the PCE level.° 5 This complexity and scenarios of how integrating renewable affects the PCE level and effective rates is illustrated in the full report in the section "Fuel cost calculation effects”,pg.32. -7-March 14,2012 PCE level =[(Non Fuel Costs/kWh Sold +Fuel Costs/kWh Sold)-Base Rate]*95% Given that space heating is often the largest household energy expense in rural Alaska,sizing renewable energy capacity to increase economies of scale and produce excess electricity for space heating to displace fuel oil usage may make economic sense in some applications.It is especially important for rural wind-diesel installations aiming to generate more than 50%of their current energy consumption with wind,because wind is not a firm source of power and at times power production exceeds the available load.In those circumstances,using and storing the "excess”wind as thermal energy via electric boilers, ceramic thermal stoves,or other electric heating devices avoids having to curtail or waste renewable energy production already paid for in the hardware.The pricing of electric heat sales adds another layer of complexity to the application of the current PCE formula.From the perspective of the utility,the heat kWh needs to be priced to cover the cost of production but to be competitive in the market it must be priced less than the price of diesel fuel it displaces.Including heat kWh in the PCE formula further exacerbates the problem of dividing by all kWh sold rather than those kWh generated with diesel.A more appropriate application of the formula-dividing solely by diesel-generated electric kWh sold,and offsetting electric revenue requirements with heat sales revenues-can more accurately compensate the utility while providing benefits to community members. Our modeling clearly showed that depending on wind-diesel system configuration and rate structure, the benefits resulting from high penetration wind-diesel systems can be distributed non-proportionally within the community.The benefits from harnessing excess energy are received primarily by commercial customers and the school/community if electric boilers are installed.Residential customers,on the other hand,face increased energy costs mainly due to decreases in PCE payments,as a result of the current funding formula.Given enough capital investment in residential electric stoves,residents could realize additional energy cost reductions,however,the decline in PCE payments would outweigh these other reductions. If integrating renewable energy sources results in comparable or lower costs,this results in a clear benefit to the utility and community as a whole.Nonetheless,if these customers do not realize monthly savings on their bills,a "public relations”problem is likely to result for the utility.Customers typically focus on their monthly bills,not the price per kWh,not their total monthly consumption,not the PCE funding formula,and the amount of diesel consumed to produce their electricity. If the PCE level declines causing the effective residential rates to increase for PCE eligible kWh,PCE eligible rate payers consuming below the 500 kWh cap see little benefit on their monthly bills because the savings accrue to the PCE program,not the rate payer.Alternatively,if the PCE level remains the same,these same customers still see no change in their monthly bills.If the PCE level increases,the effective rate marginally declines,thus providing some decrease to customer bills.But the latter only occurs if the renewable generation is more expensive than diesel fuel generation,which is counter to the purpose of integrating renewables and should not happen. -8-March 14,2012 Preliminary estimates of rate effects of the renewable energy grant funded projects on effective PCE rates showed the proportion of savings to PCE eligible ratepayers was about 1-2%with the remainder of savings split between PCE ineligible ratepayers and the PCE program.° Alternative PCE funding formulas One of the objectives of this research is to analyze whether there are alternate funding formula structures to calculate PCE payments that would eliminate or reduce the energy efficiency and renewable energy disincentives created by the current PCE funding formula.' When analyzing alternative funding formulas and comparing them to the current PCE funding formula, we used the following key parameters to evaluate whether the alternatives are improvements over the current system: Y Improves market signals Does not penalize increased energy efficiency or integration of renewable energy Has an equitable distribution across households Does not decrease the current distribution of funds to a community or utility Simplifies administration for utilities and state agencies and enhances understanding by customers/rate payers Y Simplifies formula and information needs for implementationSNNN The current PCE program uses a rate/cost formula to calculate PCE reimbursement rates.The key variables in the current PCE formula for calculating rates are non-fuel costs and fuel prices and consumption.Under a formula rate program,the calculated rate is then applied to the eligible amount of kilowatt-hours to determine the PCE payment. In contrast,a Fixed Payment formula provides a payment per given time period independent of rates and consumption.The fixed payment,however,can vary by community and be determined based on the differences in prices customers pay or the cost of producing electricity. The examined formulas included a:cost index,rate index,combined cost and consumption index, geographic price differential index,life line fixed payment,and postage stamp rates.We found that the cost and index formulas had the potential to slightly improve market signals but did not provide much improvement over the current PCE funding formula based on review parameters. Among alternate PCE structures we analyzed for this report,one deserves particular attention.We developed a fixed payment formula based on the per gallon price of fuel in a community,a generation efficiency rate,and the mean seasonal household monthly kWh consumption level.A fixed payment is calculated by dividing the price per gallon of fuel oil in a particular community (regardless of whether they generate their power with fuel oil or other sources;fuel price is used as a proxy to measure how ®Alaska Energy Authority,calculations for the Renewable Energy Fund Grant program review,January 2012. 7 In order to analyze the programmatic effect of potential changes in funding formula structures from the current structure,the eligible kilowatt-hours cap was held constant at 500 kWh per residential customer per month. -9-March 14,2012 much more costly it is to generate in one village compared to others)by a fixed generation efficiency of 14 kWh per gallon.This factor is then multiplied by the seasonal median monthly residential consumption. [(Fuel price $/gallon)+(kWh/gal)]*Average monthly consumption per season The resulting fixed payment would be applied to the rate payer's bill every month and paid to the utility. However,to accommodate changes in seasonal consumption needs,the fixed payment would change by season so that during the summer months (April-September)the customer receives a lower fixed payment credit reflecting lower seasonal consumption levels,and in the winter months (October-March) the fixed payment would be higher reflecting higher winter consumption. Applying this formula results in similar total residential disbursements as the current PCE funding formula.However,because the payment does not depend on the amount of fuel consumed and the customer receives payment regardless of consumption or rates,household and generation energy efficiency and renewable energy incentives are reestablished.If the utility is able to produce energy at lower cost through gains in demand or supply side efficiency or using renewable energy,the benefits to the utility and customer increases.Other criteria identified above,such as ease of program administration,are also met under this proposed formula. An important feature of this potential Seasonal Fixed Payment formula as conceived for this research effort is that if the customer has an electric bill lower than the fixed payment,the balance could be carried over to future months as a credit.At the end of the year if the customer has a net credit,there are a number of options that the program could offer to customers.For example,the customer could use the credit to purchase more energy efficient appliances and/or lighting products,transfer the credit to a relative in the village who may need it,or simply carry it forward to the following year. Other Policy Considerations The PCE program is critical to many rural residents;restructuring the program to improve its effectiveness and efficiency is complex.There are no simple solutions to addressing the problems of high costs that rural utilities and residents face.In seeking solutions to these issues,it is important to approach the PCE program in the context of total energy use in rural Alaska.The PCE program alone has not and will not solve the fundamental issues that result in high cost energy and the impacts this has on rural residents. Most PCE communities depend on fuel oil for both electricity generation and space heating. Consequently,high fuel oil prices increase both the cost of electricity and space heating,thus magnifying the pressure on households.Space heating is a larger share of overall energy costs,about 40%of household energy expenses,followed by transportation,about 33%(Colt,2011),with the remainder devoted to electricity.PCE provides important relief on electricity rates;however,only about 27%of fuel consumed in PCE communities is used to produce electricity.On top of this,only about 30%of kWh used -10-March 14,2012 in eligible communities is affected by PCE effective rates-so the PCE program only touches about 10% of the energy picture in rural Alaska. From a whole village perspective,one of the first objectives is to assist rural residents to be as energy efficient as possible to reduce the impacts of energy price volatility while maintaining quality of life.In addition to the current on-going weatherization efforts in rural communities,energy efficiency and conservation could be maximized to fulfill this objective.This does not mean that new efficiency and conservation programs are needed but instead existing programs can be better coordinated and delivered.For example,a recent weatherization and electrical retrofit on 13 community buildings and four teacher housing units in Nightmute was done as a concurrent effort.This more comprehensive and integrated effort resulted in estimated annual electric power savings of 59%and thermal energy savings of 56%(Butler 2010). Power Cost Equalization eligibility depends on having a centralized utility.As a result,for some of the smallest communities there could be an incentive to over capitalize electricity generation despite the potential availability of less capital intensive and possibly more cost effective solutions.Further research is necessary to determine the population size at which a rural village may be able to access lower cost electricity through disaggregated self-generation rather than opting to run a centralized utility. Finally,there has been recent discussion of expanding the PCE in its current form to include commercial customers and expanding the eligibility of residential customers.We analyzed how these expansions would impact the current PCE program. Under the current PCE program structure,funding for disbursements would have to increase about $11 million or 35%,to provide assistance to commercial customers at the 500 kWh per month level.If eligibility was available for 700 kWh per month,funding would have to increase about $15 million or 47%.Average commercial customers'consumption in 93%of PCE communities would exceed the maximum eligibility cap of 500 kWh per month.At the 700 kWh per month cap,the average commercial customer's consumption would exceed the 700 kWh per month eligibility cap in about 77%of PCE communities.At the 500 kWh level in about 38%of communities,most commercial customers would see relief on half or more of their total electric consumption.In 60%of communities,most commercial customers would see relief on half or more of their total electric consumption at the 700 kWh level. Increasing the eligibility threshold is not likely to provide substantial additional assistance to rural households.Limited levels of consumption among PCE communities suggest that given the current levels of PCE assistance,relatively low household incomes have a larger impact on their ability to consume more electricity than the PCE eligibility ceiling.Customers who would benefit the most from an increased eligibility cap are residential customers with lower effective rates who are already consuming significantly higher amounts of electricity each month,residential customers with higher incomes that consume more electricity than the average customer,or a small portion of customers that due to moderate effective rate and income levels are able to increase their electricity consumption due to seasonal changes during the winter. -11-March 14,2012 Consequently,it is an inaccurate assumption that increasing the eligibility cap would translate into extensive economic relief for all PCE eligible customers,or those who may need the relief the most. We estimated the increase in total disbursements to residential customers in CY2009 if the eligibility cap were 700 kWh per month.Raising the cap would have increased disbursements to almost $34 million from $31 million,or less than 8%.However,increasing the kWh ceiling would also increase the potential state liability by 40%to about $63 million,if all residential customers consumed up to the higher cap. -12-March 14,2012 Introduction Rural Alaska communities are remote,subject to challenging environmental conditions,and sparsely populated.These factors make it very difficult and expensive to provide basic services;energy is especially disadvantaged,and hence more costly,because of high heating degree days,poor housing stock,and soils that pose difficulties for construction of infrastructure.While rural Alaska is perhaps an extreme example,these issues are not unique to Alaska and there are no simple solutions to "overcome the problems of high cost,remoteness and lack of economic base.Subsidies seem to be required to bridge the gap between high cost and affordable rates”(Colt et al.,2003,p.1).Most rural Alaska communities have mixed subsistence-cash economies with limited cash employment available to residents.Over the years,the Alaska State Legislature has established a number of programs to help rural residents cope with high energy costs,not only to provide economic relief to households but also with the intent to help support economic development in remote communities. After the Prudhoe Bay oil field and Trans-Alaska pipeline began operation in 1977,state revenues grew dramatically.High state revenues as a result of high oil prices facilitated efforts to advance rural electrification.However,high fuel prices also significantly increased the cost of generating power in rural Alaska.Hence,the Legislature sought not only to expand rural electrification but also to make power more affordable.There has always been a tension between high oil prices that benefit the state treasury and the impacts of high prices on Alaska households.When oil prices are high,state coffers overflow,but these high prices simultaneously put strains on household budgets.As a result of higher costs and lower median incomes,high energy prices are especially hard on rural residents (Saylor,Haley, and Szymoniak 2008).When oil prices fall,state budgets are strained in their capacity to pay for any programs,including those directed at relieving rural household energy costs,which remain high as a result of high fixed costs.Rural energy costs are never low-they simply fluctuate between high and extremely high compared to urban Alaska and the rest of the country. This paper focuses on the Power Cost Equalization (PCE)program that is intended to bring greater parity between electricity rates in rural Alaska and Alaska's urban centers of Anchorage,Fairbanks and Juneau. Currently,there is renewed interest in the PCE program as a result of increased fuel and electricity prices since 2008.As one response to historic high fossil fuel prices in 2008,the Alaska State Legislature created the Renewable Energy Fund program (REF),a grant program to encourage the development of renewable centralized energy generation.In 2010 the Legislature set energy policy goals of generating 50%of Alaska's electricity from renewable energy by 2025 and reducing per capita electricity use by 15%by 2020.This analysis investigates how the currently structured PCE program interacts with these recently adopted goals and,by extension the REF program. The economic importance of the PCE program to rural utilities and customers is well established.®The program is clearly critical to the viability of rural communities and households and is in part a political *The importance of the program has been addressed indirectly in a number of analyses of the PCE program and formula."The Economic Significance of the Power Cost Equalization Program”by Dr.Scott Goldsmith (1998)is one of the most comprehensive studies on the importance of PCE. -13-March 14,2012 result of past investment in urban energy infrastructure that required rural support and continues to provide benefits to the urban regions of the state in the form of large hydropower,high voltage transmission lines,and other subsidized infrastructure.This paper takes the importance of the PCE program as given.The purpose of this paper is to examine whether potential changes to the funding formula improve program benefits to rural residents as well as help achieve the goals of increased energy efficiency and use of renewable energy. The first section covers the history of the PCE program,how the program operates and its impact on rural residents.This is followed by an analysis of the PCE program effects on incentives for efficiency and innovation.We then review alternative formula structures,how these alternatives affect the PCE program,and resulting policy implications.There have long been criticisms of the PCE funding formula structure because it is perceived to reduce incentives to utilities and rate payers for improving energy efficiency and for integrating renewable energy into their system.As part of this review,we investigate that perception. When analyzing alternative funding formulas and comparing them to the current PCE structure,we used the following key parameters to evaluate whether they improved the current system: ¥Improves market economic signals Does not penalize increased energy efficiency or integration of renewable energy Does not decrease the current distribution of funds to communities Has an equitable distribution across households Simplifies administration for utilities and state agencies and enhances understanding by customers/rate payers ¥Simplifies formula and information needs for implementationSNNN These parameters recognize the critical importance of PCE to communities and households while examining the principal issues that impact the current PCE funding formula structure. Power Cost Equalization History The first electricity assistance program established by the Alaska State Legislature was called the Power Production Cost Assistance (PPCA)program.It was implemented during state Fiscal Year (FY)1981. Through this program,a portion of the generation and transmission costs of utilities with high rates were paid,which enabled utilities to reduce rates for residential,community facilities and charitable organization customers.About 15 utilities participated in this program benefiting 11,405 residential and commercial customers,238 organizations and 473 community facilities (Alaska PowerAuthority,1988). The PPCA program covered about 33%(40,490 megawatt-hours)of generated power.At that time the average per gallon cost of fuel for participating utilities was $1.054 (about $2.64 in 2010$S$).°However, °PCE program data is calculated on a state fiscal year basis.The fiscal year starts July 1 and ends June 30. Estimation of figures in constant dollars is done using the U.S.Department of Labor Bureau of Labor Statistics consumer price index (CPI)for a fiscal year. -14-March 14,2012 the program lasted only one fiscal year during which it distributed $2.2 million in assistance (about $5.5 million 201088). The legislature instituted significant modifications to the program in FY 1982 and renamed it the Power Cost Assistance program.This program operated from FY1982 to FY1984.The major changes included increases in the entry and ceiling rates,decrease in the portion of eligible costs for reimbursement and the inclusion of distribution and administration as eligible cost categories.The last year the program was implemented,it served 61 utilities benefiting 21,702 residential and commercial customers and 985 community facilities (Alaska PowerAuthority,1988).The PCA program reduced the price of about 40% (96,520 megawatt-hours)of the generated power.At that time,the average per gallon cost of fuel for participating utilities was $1.70 (about $3.62 in 2010SS).The last fiscal year of operation the PCA program distributed $8.3 million in assistance (about $18.4 million in 2010$$). The Power Cost Equalization program was created in 1984 when the Legislature enacted Alaska Statutes 44,83.162-165 replacing the Power Cost Assistance program.The program became effective in October 1984 (FY 1985)and was funded through appropriations from the general fund of $6.67 million (2010$$). Since that time,the PCE program has had only a few modifications over its almost 26 year life.Table 1 describes the differences across the programs,which in their basic structure and funding formulas are quite similar. Over the years,the Alaska State Legislature has actively debated energy policy covering a wide span of issues from affordability and power availability in rural areas,to development of hydroelectric generating facilities,and goals of developing other renewable energy sources,as well as oil and gas policy.Many decisions regarding the PCE program were made in the political arena and were a result of trade-offs negotiated as part of the legislative process.In 1985,shortly after PCE was established,the origins of the program were described as follows in an Anchorage Daily News article: "Power Cost Equalization is the result of a legislative trade by urban politicians who wanted Bush support for massive hydroelectric projects -the proposed Susitna and Bradley Lake Projects in the Railbelt and four other dams in Southeast Alaska.In return for tens of millions of dollars in state money invested in waterpower engineering and construction,the Bush delegation won equalization”(Mauer,1985) To this day the PCE program continues to provide critical economic relief to rural communities throughout the state,but it does not address the roots of the problem of high costs and low cash incomes. -15-March 14,2012 Table 1.Timing and characteristics of implemented power cost assistance programs PPCA PCA PCE PCE PCE. (FY 1981)(FY 1982-(FY 1985)(FY2000)(FY 2011)> 1985) Entry rate (2010 18.4 24.3 17.2 15.2 14.0 cents/kWh) "Ceilingrate 9.0 °°}©g12,0- - *S 1064 |65 |100.0 (2010 cents/kWh) "Eligiblecostsfor tS 85%”95%9%95%«95% reimbursement "Eligiblecostsfor Yes,100%|No No No.No. reimbursement over ceiling "Consumption Limits-None 55kWhper 70kWhper 70kWhper 70 kWhper Community Facilities?Resident Resident Resident Resident kWh/month "Residential®=N/A|600 =--"'TS™©6cS00C t '"C('CSs 500° Commercial Commercial Commercial Consumption Limits no longer no longer kWh/month -eligible eligible "Eligible cost categories oy) for reimbursement generation generation,transmission,distribution and administrative and | transmission Source:Modified table "Comparison of PPCA,PCA,PCE and PCE-REC”(Brooks,1995)5 Community facilities is defined as water and sewer facilities,charitable educational facilities,public lighting,or community buildings whose operations are not paid by the state,federal government or private commercial party. *Starting in 1993,the PCE eligible kWh per month limit dropped to 700. Program Implementation The responsibilities of administering the PCE program were divided between the Regulatory Commission of Alaska (RCA),*°which evaluates utility eligibility and costs per kilowatt-hour (PCE level),and the Alaska Energy Authority (AEA),**which determines the number of eligible kilowatt-hours in order to calculate the appropriate payment and make the disbursement.The legislature established criterion for utility eligibility that excluded urban areas and regions that benefited from hydroelectric development (Four Dam Pool utilities--Kodiak,Port Lions,Valdez,Petersburg,Wrangell and Ketchikan)(Matz & Kreinheder,1988,p.11). 0 Originally APUC,Alaska Public Utilities Commission. ut Originally APA,Alaska Power Authority -16-March 14,2012 At its inception the program had the following key provisions: Y Utility provides electric service to the public for compensation ¥During calendar year 1983,less than 7,500 megawatt-hours were sold to residential customers or less than 15,000 megawatt-hours if two communities were served and ¥During calendar year 1984,diesel-fired generators were used to produce 75%of electricity The program was designed and directed toward centralized utilities using diesel fuel to produce electricity.It was also designed to ease the ability of utilities to participate since according to statute "a utility may not be denied power cost equalization because complete cost information is not available” (State of Alaska,1989,p.16).The Legislature also required that participating utilities submit a monthly report that "records monthly kilowatt-hour sales or generation,monthly fuel balances,fuel purchases and monthly utility fuel consumption”(State of Alaska,1989,p.20).AEA would then review these monthly reports,check the calculations,determine the appropriate payment and make the disbursement. Seven years after the PCE program was established,funding the program became a challenge as world oil prices sharply decreased lowering state revenues.Since inception,the program was not fully funded by the Legislature in 15 out of 25 fiscal years.In 1990,in an attempt to contain costs,the Legislature directed the Alaska Public Utilities Commission to implement new efficiency and line loss standards and to more clearly define eligible costs.To further address high operating costs,AEA provided technical support,preventative maintenance and upgrading/replacing equipment of rural utilities (Pourchot, 1990,p.11). In FY 1992,the program was pro-rated to 80%eligible PCE payments because of funding shortfalls for eleven months of the year.One year later,the Power Cost Equalization and Rural Electric Capitalization Fund (the PCE fund)was created by the Legislature with an appropriation of $101 million (2010$S). During subsequent years,PCE expenses were drawn exclusively from the PCE fund and were nearly spent by the end of FY 1999 (State of Alaska,Office of the Governor,1999).This continued to be an issue until FY 2000 when the PCE program had full funding for one year.”Then,during FY 2001,the PCE Endowment fund was created.Originally the fund was capitalized using the proceeds from the sale of the Four Dam Pool Projects and funds from the Constitutional Budget Reserve.Later in 2007,the fund was once again capitalized with general funds.The Rural Electric Capitalization Fund and PCE program costs are appropriated using dividends from the PCE fund'?(Alaska Energy Authority,2009,p.2).For the last three fiscal years,the PCE program again received full funding.Last year the legislature appropriated an additional $400 million for the PCE endowment fund.Figure 1 shows annual PCE appropriations, disbursements and average distillate fuel oil prices since the first program was implemented.” v Appendix A details PCE funding levels per year *The fund is managed by the Department of Revenue;it is invested to earn 7%over time.Seven percent of the fund's 3-year monthly average returns may be appropriated. *Historical data was gathered from PCE Annual Statistical Reports published by the Alaska Energy Authority since 1988,for further detail regarding data sources and methodology please see Appendix G. -17-March 14,2012 Figure 1.PCE appropriations,disbursements and distillate fuel oil prices per gallon in the electric sector over time $50 $4.5 Bh 945 -+$4.0 3s A |\a 940 |"Vt $35 2<3 ="€8 Fe bp SK iy 8$30 7 ;ae TF -2 SAN OPN Ge nn coe@$25 te ay ea =i E6-4 \°Now /j -$2.0 5 920 7->"ye Sf NES”a °2 i "an -$15 %3 $15 +-#fs if |$1.0QOsi91)PCE is .=>a created F SprcahSOqTTqT T UJ T T T UJ LU T T T T T qT qv UJ i Lf qT T qT T T T qT T qT qT $0.0 YY a ND SY oO Oo AN GD Dd &A &HB"DS SD BD BD DW BD AD QD OD'GQ LH'LC'COPPPPVPOWewDTPPPPPFiscalYear =Total PCE disbursements -::=Appropriations -=Fuel Oil Price per Gallon Source:PCE Statistical Reports 1988-2010 and Author's calculations. Coping with volatile and generally increasing crude and fuel oil prices has been a challenge for the PCE program since its inception.Average fuel oil prices in the power sector in Alaska increased sharply between FY 1980 and FY 1981,and then decreased sharply until FY 1986.For participating utilities, average fuel oil prices were highly volatile but the average annual real price of fuel was relatively stable between FY 1981 and FY 1986.Because PCE was not fully funded in most years from FY 1992 through FY 2007,fuel prices and program payments were not highly correlated.Figure 1 shows how after the first year the PCE program was created,the total amount of funds disbursed steadily decreased while fuel oil prices had a volatile but relatively flat trend.However,after FY 2005 high fuel prices and program growth resulted in record high PCE disbursements.In FY 2009,coinciding with the 2008 crude oil price run up,PCE disbursements increased to about $37 million (2010SS). Total electricity (kWh)sales of participating utilities steadily increased until FY 1999,the last year commercial customers where eligible to receive the PCE credit (Figure 2).Some of this increase resulted from additional utilities participating in the program.In FY 1999,in addition to eliminating reimbursements to commercial customers,the number of eligible kWh per month per residential -18-March 14,2012 customer was also decreased from 700 to 500 kWh.After that adjustment,consumption re-adjusted and continued an upward trend.However,the total number of kilowatt-hours eligible for reimbursement has remained relatively flat over time following adjustments in eligibility levels in FY 1993”and FY 2000.During the years of the PCE predecessor programs both sales and eligible kilowatt- hours exhibited higher growth,largely due to the increase in the number of participating utilities. The average number of eligible kilowatt-hours grew at about 5%per year since FY 1985;the average annual population growth in participating utility communities was 2%over the same time period.Figure 2 shows kilowatt-hours sold,PCE eligible kWh and the average residential monthly payment per customer since disbursements became available to residential customers.The sharp declining trend during the 1990s and first half of 2000s resulted from pro-rated PCE disbursements due to lack of funding (Appendix A).Figure 3 shows kWh sold and PCE eligible kWh with average kWh sold per capita; notably per capita electricity consumption continued to steadily rise in the years of pro-rated funding. The sharp increase starting in FY 1985 coincides with the increase in eligible kWh from 600 (under the PCA program)to 750 after the PCE program was instituted and the increase in participating utilities.The sharp decrease in per capita consumption between FY 1987 and FY 1988 coincides with the crash of the Alaska economy due to a drastic decrease in world oil prices.*© Figure 2.Power sold,PCE eligible kWh and average residential monthly payment,1981 to 2010 600,000 160 500,000 aN =_AIXee_f 120wnieneoe5400,000 -43aof 10082rg/'a3300,000 +a ,+80 =&':° Y " .-L 60 2=200,000 +”4 53).; -¢en >fF 40© . ' -100,000 +emul Ne |2 a ||L 20 0 qT T qT Lj Lf T T LJ Lj Lj r qT T qT qT T qT qT T qT T qT LJ LJ Lj T Lf qT T 0 S o&©A OD SS &©cl OD oy O&O ©OOIPPSP?HP SOP PT HAP AP IP APT HP”AP Ho Fiscal Year Mmmm PCE Eligible kWh £0.73 Total kWh Sold ===Average Residential Monthly Payment Source:PCE Annual Statistical Reports 1988-2010 and authors'calculations. *In 1993,residential customer eligible kWh dropped from 750 to 700. 6 Though oil prices decrease,the effects of the economic crash on lowering economic activity and income were likely the cause of the decrease in consumption.In general price elasticity of demand in PCE communities is highly inelastic.For more information about this topic please refer to Fay and Villalobos,All-Alaska Rate Analysis. -19-March 14,2012 Figure 3.Power sold,PCE eligible kWh and average annual kWh sold per capita,1981 to 2010 600,000 5000 ON rf +4500 >m"- 's ££3500 €2 400,000 4 8=Uo F 3000 s = 3 300,000 _---_+2500 §S >bn wv2F2000§ 4 Qa=200,000 ---11500 3 Y qt,:ns 2 °oa+1000 8€100,000 + :Ne H 3,2 F 5008 0 U ents T T qT T qT T qT T T T LJ ul in ly T T qT T t T T Li U T Ly T 0 Fiscal Year Mmmm PCE Eligible kWh a4 Total kWh Sold ome Average kWh Sold per Capita Source:PCE Annual Statistical Reports 1988-2010 and authors'calculations. Table 2 shows eligibility and participation by utilities across regions of Alaska;in 2010,a total of 190 utilities were eligible and participated. Table 2.Utilities/communities eligible and participating program,CY 2010 AEA Energy Region Yes Inactive No Total Percent Active Aleutians 12 1 0 13 92% Bering Straits aa100%Bristol Bayeee n-ne-1CopperRiver/Chugach 6 eee 02Bo I ST:ee ee ee6 OP_tower Yukon-Kuskokwim 48 OO.48.100%wn. North Slope eeeereeOsBn88%Northwest Arctic OBB21rer.Oe ee a i Se O103T88%Yukon-Koyukuk/Upper Tanana 38 3 2 43 88% Total 190 8 29 227 84% Note:For utilities that serve multiple communities with no grid such as AVEC and AP&T,each community is counted individually. Source:Alaska Energy Statistics report 1960-2010,ISER (2011). -20-March 14,2012 Electricity Rates and Levels of Consumption The biggest challenge in providing electricity (and other public services)to rural residents lies in the lack of economies of scale;this intractable problem is difficult to overcome.The fixed costs associated with running a utility are large and if the number of customers and/or levels of consumption are very small these costs must be spread out over very few customers and kilowatt-hours.Most PCE communities are similar in that they produce all or most of their electricity using diesel generators,have small populations,and customers pay electricity rates higher than customers in Anchorage,Fairbanks and Juneau.However,across PCE communities there are significant differences in remoteness,population sizes (ranging from 8 to about 6,000 people),available means for transporting and storing fuel,income and other factors that ultimately affect their electricity prices.'”Hence,there is a large variability in electricity rates across PCE communities,which in turn,affect their levels of electricity consumption (Table 3). Table 3.Average Annual Residential Electricity Consumption and Rates,2008-2010 "kWh per Customer BeforePCE After PCE AEA Region 2008 2009 2010 2008 2009 2010 2008 2009 2010 "Aleutians 47764788 5014|048 040 044 022 O21 O21, "Bering Straits 45694,7514524|041 047 0.44 0.16 0.20 0.21."BristolBay 4219 3,910 4131|043 050 047 0.17 021.0.28"Copper River/Chugach 4,0544,297 4331 |0.28 0.25026 018 019 0.18.Kodiak 4,380 4,779 5,145 0.20 0.17 0.18 0.12 O13 £0.16 "LowerYukon=EEE Kuskokwim 41574262 4,333 |0.52058052 0.19 0.22 0.24"North Slope 59187,4808230]O14 014 013 O11 0.13 0.12."Northwest arctic 5537 5,7555860|048 056 051 0.21 0.20 021 "Railbet 8080 7897 7514|016 016 0.15 016 0.16 0.15, Southeast (Non PCE)11,412 12,244 11,733 0.11 0.10 0.10 0.11 0.10 0.10 Southeast (PCE)4,545 4,460 4,290 0.43 0.38 0.41 0.18 0.19 0.19 "Yukon-Koyukuk/Uppers-<-sts-'-sSsSsSsSsS-sSsS Tanana 3,191 3,348 3,322 0.53 0.52 0.52 0.20 0.22 0.23 Source:Alaska Energy Statistics 1960-2010,(2011). However,on average,PCE residential customers consume significantly less (over 40%)electricity per month than customers in urban areas of Alaska.Average annual per customer residential consumption in most Alaska regions is between 4,000 and 6,000 kWh per year or 333 and 500 kWh per month.The Yukon-Koyukuk/Upper Tanana region has the lowest at just over 3,000 kWh per year or 250 kWh per month.In the Railbelt average annual consumption in Fairbanks is 8,285 kWh and Anchorage is 7,475 kWh or 690 kWh and 623 kWh per month,respectively.The average PCE utility generates less than 3,000 MWh per year;about 30%of the utilities generate less than 500 MWh and the smallest generate u Appendix F lists PCE communities and their residential and effective rates,average consumption per residential customer per month,population,average household size (2004),average real median income (2004)and average fuel prices in 2009. -21-March 14,2012 less than 30,000 kWh per year.By comparison,urban utilities (Anchorage and Fairbanks)generate over 1 million MWh per year.This means urban utilities produce over 300 times as much power as the average PCE utility. Overall,less than 30%of all kWh sold in PCE communities receive PCE credit.However,the importance of this assistance to residential customers and community facilities is significant.As illustrated in Figure 4,in CY2010,almost 70%of all residential kilowatt-hours received PCE credit.PCE also provides significant assistance to community facilities;Figure 5 shows that of all kilowatt-hours consumed by community facilities in CY2010,about 50%received PCE reimbursement. Figure 4.Residential kWh sold in PCE communities 100% 90%: ,}-- 80%}- 70% 60%: -- 50%= - 40%- 30%+S -.- 20%+- . - 10%+- .-- 0%.:-_-:;;-:; ov Ss?Na wa ce wh Wi SP wyaSaSaSoSay2aSaSaS :kWh covered by PCE mkWh not covered by PCE Source:PCE Annual Statistical Reports 1988-2010 and authors'calculations. Figure 5.Community Facilities kWh sold in PCE communities 100% 90% 80% 70% j 60%+-- e-_- 50%+--- 40%+-- 30%+-_ 20%+-- 10%+-é;-_- 0%. : +2 .. : L : ° :-, SF FS SS "kWh covered by PCE m kWh not covered by PCE Source:PCE Annual Statistical Reports 1988-2010 and authors'calculations. The effect of the PCE program varies across communities depending on the proportion residential and community facilities comprise of total utility kWh sales.Figure 6 shows kWh sales by customer category -22-March 14,2012 by census area.Regions are organized from the largest to smallest residential customer share to illustrate the regional differences in demand composition by customer categories.It illustrates how in the census areas of Hoonah-Angoon or Yukon-Koyukuk among others,residential and community facilities sales account for about 50%of total kilowatt-hours sold.In comparison,in census areas such as Bristol Bay or North Slope,residential and community facility sales are less than about 25%of total kilowatt-hours sold.Most of the regions on the right side of the chart with large portions of commercial customer power sales have large fish processing operations that have high electricity demands. Figure 6.Kilowatt hours sold by customer category and census region,CY 2010 90%+]ae to)od : |fr 80%-SS | Lit70%+H | L 60%+4 - 50%+os |_fd 04 yt |_|L y LIL biti tibi EF PABy |+i ag mia40%r i }WN _int_hi¥_}ry "LI =?=3%cade TY Lean aM20%Hey HH HH HHH HHH EE 10%at ot RS Re RO eo eect ect es ost)Os ct tt tt eo Fe OR Pr rr 0%oT T T T T T 7 qt T u oe a a T T 1 T q S ©&wo &+¥WOW SO 2 Oo SX SA ©&SeFMBKPFFHPFsSPPPSFSFWw<PQ KP PM KK SG LK SK ow LK 9 ee)OL SPH I oF FW VS FPPTWMSWSSeeegeweSeysaSevfSowewe©=we Re ww ye”wr?r \? ? m Residential mCommunity Facilities m Commercial ©Other Source:PCE monthly program data CY 2010 and authors'calculations. Similarly,Figure 7 shows the proportion of eligible customers by region starting with the region with the largest share of eligible customers from left to right.Regions that have large industrial sectors also have lower shares of PCE eligible customers. Figure 7.PCE eligible and non-eligible customers by region,CY 2010 MPCE Eligible Customers -_«Customers Not Eligible for PCE Source:PCE monthly program data CY 2010 and authors'calculations. -23-March 14,2012 Figure 8 shows both the average residential and effective rates (residential minus PCE credit).It exemplifies how the PCE programis fairly effective at lowering the effective residential rates for the communities served.Those regions (and communities)with higher rates receive more relief,while regions with lower rates such as the North Slope,receive lower levels of assistance." Figure 8.Average residential and effective rates of PCE communities by census region,CY2010 1.2 1 0.8 x re)az°°}7)oO O S 0.4 ©OQ é)(*)#)oO O o (@) S o"024 o nn oo ,o o 0 T UJ 7 7 T T LJ 7 t T 7 t T J Lf qT 1 qT u 1 ><xoeweRaaeeAS.&Ss se BS 3&Cs &oo”Rg Ro a 3 oO RoeSeyesswLXyewwBS>cS a om w oe RS RS &ao yoCo*w Sf &oe Ne Ry ge &we }SeSSyeye”RS D>RG ao ? @ Residential Rate mEffective Rate Source:PCE monthly program data CY 2010 and authors'calculations.Averages are weighted. In most PCE communities average consumption per customer per month is below the 500 kWh PCE eligibility cap.Table 3 shows the different levels of consumption at various rates.During summer months in 2009,less than 18%of eligible communities had average consumption levels above the PCE cap.Most of the communities where average monthly consumption exceeded the 500 kWh cap were communities that have effective rates comparable to those in urban areas (e.g.North Slope''),have comparatively high incomes,and/or are located in southeast or southwest Alaska.Even during winter, about 60%of the PCE communities did not have average consumption above 500 kWh per month per customer.On average,as shown in Figure 9,consumers that increase their levels of consumption by more than 10%during the winter months are those in communities where the effective rates”are below 30 cents per kWh. *®The North Slope Borough communities benefit from availability of natural gas in some of its communities and additional subsidies.Rate structure is a flat rate of about 15 cents per kWh for all communities in the borough.*°Effective rate is the rate that the residential customer actually pays for the first 500 kWh consumed,(Residential Rate -PCE credit). -24-March 14,2012 Table 3.Average consumption per customer per month in PCE communities,CY 2009 Calendar Year 2009 -Summer (April-September) Effective Rate Min Mean Max No.Communities No.Observations Less than $0.10 203 294 345 0 3 "$0.10-$0.19 |107;371|924,ti(i'CSCSs7;,iti'527, $0.20-$0.29 |113;317,717,i (i'S;«;6/|330° $0.30-$0.39|-140[301/486;of 84"$0.40-$0.49 |182;303;sol;©s5|©.27 "$0.50-$0.59 |69|162];329;£422,21, $0.60-$0.69 |115;i197;293)-C-i"'<i'2 73(§XY } SCTlttC "Morethan ||ms;|Of 0:1 $0.70 Calendar Year 2009 -Winter (October -March) :Effective Rate Min Mean Max No.Communities No.Observations Lessthan$0.10 |324| 548|816 1 6 "$0.10-$0.19 |100;432|970;2- - <CSCi'C:;*;”49;597° "$0.20-$0.29 |92]379;966|«101;°°°2} } &|276 $0.30-$0.39 ||144;322|606 }§|10;©58 "$0.40-$0.49 |148;30s;506;ti(';OCFriLO ™37, "$0.50-$0.59 |53]|138;365;£42,13. "$0.60-$0.69 |81;21}351;-C-<"';]}XW®®!®*€* «Ctl "Morethan |”59;7s]91f 00 $0.70 Source:PCE monthly program data CY 2010 and authors'calculations.Note that the number of communities in the summer only adds up to 171 and not 172;this is because not all PCE communities file their monthly report year-round.In this case a community only filed during some of the winter months. Also the number of communities within a rate range is determined by taking the monthly average for the season;hence in some cases it may show a number of observations,but zero communities. Overall price elasticity of demand for electricity in PCE communities is highly inelastic (Villalobos Melendez,2012)and communities with higher effective rates have significantly lower demand.In addition,generally the consumption range in communities with higher effective rates is measurable smaller than in communities with higher rates.Essentially,residential customers with effective electric rates above $0.30 per kWh are consuming such a small amount of electricity that it is difficult to consume much less during any time of the year. Measuring how much more households are consuming because of PCE is a very difficult question to answer for two primary reasons:1)The program has been in place for several decades and there are no residential customers in PCE communities who are not eligible for the PCE program to enable a comparison.2)There are no household level data that enable estimation of the actual differences caused by the subsidy. March 14,2012 Figure 9.Seasonal changes of electricity consumption in PCE communities,CY 2009”°CentsperkWh0 100 200 300 400 500 600 Average Consumption per Customer per Month,kWh =e Summer -fwinter Source:PCE monthly program data CY 2010 and authors'calculations. The most likely explanation for why consumption levels are significantly lower than the eligibility cap and so unresponsive to price changes over such a large price range is that the income effect on consumption overwhelms the price effect."In other words,customers can not afford to consume any more electricity even at the PCE effective rates because their incomes are insufficient.These price and income effects also seem to have a compounding effect because communities with the highest electric rates also tend to be the smallest and most remote communities that have the lowest average incomes (see appendix F for information on median household incomes and electric rates). How the current Power Cost Equalization funding formula works The PCE program reduces the kWh electric rates charged to rural residents in areas where residential rates are high.The RCA determines utility eligibility and the PCE level (the amount paid per kWh).The PCE level is determined by a formula based on a utility's rates or costs,whichever is less. »°This figure is based on discrete data and the lines do not represent a functional relationship between consumption and price,but the lines help visualize seasonal differences.The formal functional relation between consumption and price for PCE communities is reviewed more extensively in All-Alaska Rate Analysis by Fay and Villalobos,2012. 71 A change in the demand of a good or service,induced by a change in the consumers'discretionary income.Any increase or decrease in price correspondingly decreases or increases consumers'discretionary income.The price of electricity reduces the amount of discretionary income available to purchase more electricity to the extent that there is no discretionary income available to purchase more electricity even if prices decline. -26-March 14,2012 Lesser of PCE Rate =[(Non Fuel Costs/kWh Sold +Fuel Costs/kWh Sold)-Base Rate]*95% or PCE Rate =[Residential Rate -Base Rate]*95% if<maximum allowed rate A utility's PCE payment per kWh is determined by a formula that covers 95%of a utility's cost between a floor or base rate (average rate for Anchorage,Fairbanks and Juneau,13.42 cents/kWh)and a ceiling (currently $1.00/kWh)for a defined level of consumption (500 kWh for residential customers,and 70 kWh per month multiplied by the community's population for public facilities).The PCE base rate is re- calculated every year by RCA.Also,the PCE level is re-calculated for eligible utilities at least once a year based on the utility's annual filing or if the utility files for a re-calculation of the PCE level based on rates and/or fuel price changes.State and Federal government customers as well as commercial customers are not eligible for the PCE credit. There are other factors that also affect the calculation of the PCE level including minimum efficiency standards for diesel generation depending on the quantity of electricity the utility produces.Table 4 shows how utilities that produce more than 80%of electricity from diesel have slightly higher efficiency standards than those who produce less than 80%of electricity from diesel.Also,utilities that produce more kilowatt-hours are expected to have higher levels of efficiency.In addition,a maximum 12% distribution line loss standard is expected from all utilities.If the minimum level of efficiency or the line loss exceeds the standards allowed,the PCE level is decreased.An important consideration related to these standards is that they have not been updated to keep up with technological changes since they were implemented in FY 1990.For these standards to be meaningful it is important that they reflect achievable goals of current technologies. Table 4.Minimum efficiency standards for electricity generation Total Diesel Generation Total Generation (kWh)More than 80%|Less than 80% kWh/gal kWh/gal 0 to 99,999 9.5 8.5 100,000 to 499,999 10.5 10.0 500,000 to 999,999 11.5 11.0 1,000,000 to 9,999,999 12.5 12.0 More than 10,000,000 13.5 13.0 Source:Table recreated from the PCE Program Guide,2011,Alaska Energy Authority. Participating utilities are required to file reports with both RCA and AEA;these reports are used to approve costs and determine the utility's PCE reimbursement rate per kWh.Unregulated utilities must file an annual report with RCA accompanied by accounting documentation such as balance sheets, -27-March 14,2012 invoices and other details to support their costs.RCA uses these records to verify allowable costs for power production.If RCA deems any of the costs ineligible,those costs are not included in the calculation of the PCE level.Regulated utilities can also request a Cost of Power Adjustment (COPA)to adjust their fuel costs between PCE level adjustments.Most utilities participating in the PCE program are unregulated (about 73%). In addition to annual reports,all participating utilities must file a monthly report with AEA containing production and sales information including total kWh generated,gallons of fuel used,and kilowatt- hours sold.This report is used to determine the number of kilowatt-hours eligible for PCE level reimbursement.Utilities also submit copies of their customer ledger documents that AEA uses to verify that kilowatt-hours sold are eligible.Utilities self report to RCA and AEA;the agencies and their functions relative to the PCE program are independent.Utilities are instructed to submit consistent information to both agencies,but there is no on-going process to audit or reconcile the consistency of the information provided to both agencies. Analysis Information for this analysis was obtained primarily from existing reports and datasets.Details on data used and data documentation are contained in Appendix G.In addition,we performed a literature review of previous reports and analyses regarding changes to policy and program guidelines. Finally, we conducted informal and semi-structured interviews with utility managers,program managers and other leaders in the industry. Impacts of PCE on efficiency,innovation and conservation incentives There are four primary ways that the PCE program ultimately affects the price of electricity to rural residents,and thus efficiency,innovation and conservation incentives.One is a broad effect on prices and consumption.The second is the specific application of the current PCE formula as written in statute and applied by RCA.The third is how PCE impacts heat sales in high penetration systems.The fourth is how the savings from integrating lower cost renewable resources is distributed among PCE eligible kWh, non-eligible kWh and the PCE program.We will discuss each of these four issues sequentially below. General price and consumption effects The PCE program in its current form has a range of impacts on economic incentives.Economic theory tells us that more of a good is consumed as prices decline.Because PCE lowers the price of electricity for eligible kilowatt-hours,it allows customers/households to purchase more electricity and utilities to supply more power than they would if they were paying the full market price.However,because the cost of producing electricity in most PCE eligible communities is so high,the residential customer rates (referred to as the "effective rates”)even with PCE are still very high.Comparatively high electricity rates coupled with low cash incomes result in average per customer electricity consumption of less than 400 kWh-over 40%less than the urban Alaska average of 700 kWh.While residents in PCE communities may be consuming more electricity than they would if they were paying market prices, 22 .ar ..A complete list of sources is listed in the "References”section. -28-March 14,2012 their consumption is in the realm of "lifeline”levels barely powering what would be considered essential modern household functions such as lights and refrigeration.It appears that the primary effect of the PCE program is increasing the quality of life of rural residents rather than encouraging "excessive”use of electricity. On the other hand,by lowering the price of electricity PCE lengthens the payback period of household investments for energy efficient products and lowers the energy efficiency incentives to households. However,this effect may be outweighed by the relatively high electricity prices households pay even with PCE effective rates.The larger barrier to household investments in demand side energy efficiency such as more efficient appliances and lighting is likely insufficient household income and capital to finance the upfront costs of these investments.An increase in residential energy efficiency does not necessarily result in utilities having to cope with lower electricity demand because these household efficiency gains may allow households to increase consumption over time,thus becoming more likely to reach parity with urban household consumption levels,and increasing rural quality of life. At the utility level,there are generation efficiency and line loss standards that must be met in order to receive the full potential PCE level.If these generation efficiency standards are not met,the PCE level is lowered.In addition,utilities submit detailed documentation regarding their operating costs and RCA determines if costs are eligible.Yet,the reporting complexity and limited resources of some utilities may result in detailed operational data not being updated frequently,resulting in PCE levels being lower than necessary to cover actual utility costs.” Utility generation standards provide a disincentive to generate at lower efficiencies.However, adjustments in the PCE effective rate calculations are complex and utility clerks and rate payers may not fully realize that they have forgone a portion of the PCE payment because the utility is generating power less efficiently than the standards.There are also a myriad of causes of poor efficiency including old generators,generators poorly sized for the load,failing transmission lines and transformers,deferred and insufficient maintenance,lack of operator training,and loads that are too small to support a central generating facility,all of which are difficult for small cash strapped utilities to control or address.The Alaska Energy Authority (AEA)and other institutional support have improved this situation generally, but the needs and issues are so diverse and complex that it is impossible to fully overcome. Probably the most significant incentive utilities have to operate as efficiently as possible is the fact that for most utilities,PCE eligible kWh are less than half of the total kWh sold.So a significant number of their customers are paying the full rate for all (commercial and other)or a portion of their kWh consumption (residential and community facilities).In many cases,the cost to self-generate for their commercial customers may be similar to the rates these customers are paying the utility.So the utilities are under substantial pressure to keep their rates as low as possible because losing commercial customers is likely to send the utility into a downward spiral of escalating costs and declining sales over which to spread the costs,along with declining generation efficiency as the load decreases.From the 23 Work with some rural utilities on their cost structures and limited review of PCE non-fuel cost data suggest that this issue is not uncommon. -29-March 14,2012 utility perspective,this results in disincentives to have either individuals or commercial customers self generate,generate renewably,or decrease their load through efficiency or conservation. In summary,while PCE reduces the rates paid for eligible kWh,for most residential customers the effective rates are still sufficiently high and household cash incomes sufficiently low such that most customers minimize electricity use.Low income and high energy costs coupled with volatile fossil fuel prices and the fiscal challenges of fully funding the PCE program,result in a high level of "energy insecurity”in most rural communities.The PCE data show that average per residential customer consumptions is well under the cap of 500 kWh.The fact that average consumption is lower than the allowable cap illustrates a degree of uncertainty by residential customers regarding if and how much reimbursement they will actually receive.For utilities,pressure from customers paying non-PCE rates probably overrides any effect that PCE may have on reducing the incentive to maximize generation efficiency in terms of kWh generated per gallon of diesel fuel.While the high cost of electricity may overwhelm the disincentives caused by the PCE funding formula,the PCE program does not address the fundamental barriers to improving energy efficiency and saving rate payers money in rural communities. However,the PCE funding formula structure does result in a disincentive towards innovation and alternate sources of energy as potential solutions to the problem of high costs of rural energy because PCE is directly tied to fuel costs.As a result,integrating alternative or renewable generation technologies may result in a lower PCE payment causing the effective electric rates to increase.Knowing how the PCE level will change requires an individual analysis for each utility and generation alternative because alternative sources of generation affect non-fuel costs (which are also considered in the PCE formula),hence the PCE level may increase,decrease or remain the same.In other words,the new PCE level depends on how the utility cost structure changes and by how much.Considering the impact of PCE is highly situation specific and difficult to predict,perhaps the policy could be better targeted if it were aimed at answering the following question:what do we want to incentivize? Fuel cost calculation effects A decline in fuel costs affects the PCE level calculations because in the formula the total fuel costs are divided by afl kilowatt-hours sold,not just the kilowatts-hours sold that were generated using diesel fuel (see text box below).Table 5 shows a generic example of how dividing fuel costs by total kWh sold results in a decrease in the fuel cost variable used in the PCE level formula.Hence the way fuel costs are calculated in the PCE formula becomes a financial disincentive against integrating renewable generation and also increasing the penetration of renewable power generation.This results because the larger the renewable generation,the lower the fuel cost per kWh that is used in the PCE formula to calculate the PCE level.The simplified examples below should help to clarify this complexity. PCE Level =[(Non Fuel Costs/kWh Sold +Fuel Costs/kWh Sold)-Base Rate]*95% if<maximum allowed rate -30-March 14,2012 Table 5.Example of PCE fuel costs calculations and its effects on renewable generation Generation from diesel,100%Generation from diesel,50% Total fuel costs $1,000 |Total fuel costs $500 Total kWh sold from diesel 10,000 |Total kWh sold from diesel 5,000 Total kWh sold 10,000 |Total kWh sold 10,000 Fuel costs/kWh sold from diesel $0.10 |Fuel costs/kWh sold from diesel $0.10 Fuel costs/total kWh sold $0.10 |Fue!costs/total kWh sold $0.05 In order to illustrate how the effect of reduced fuel cost could decrease the PCE level and lead to higher effective rates for residential customers,we developed two scenarios of renewable integration based on PCE program data.We review the differences in the rate calculations between generating all electricity with diesel with generating electricity with a hybrid diesel-renewables system.The first scenario reviews the changes for a utility with high renewable penetration using hydroelectric generation.The second scenario reviews the changes for a utility with low renewable penetration using wind generation. However,the type of renewable generation is immaterial to the results. In both scenarios we assume that total generation,total kWh sold,average fuel price and residential rates remain constant.Though these factors may also change,we keep them constant to clearly illustrate the effect of fuel costs in the current PCE level formula.In the first scenario we assume that non-fuel costs remain the same (though this is unlikely in any renewable energy system);and in the second scenario we assume that non-fuel costs increase at about 3 cents per kilowatt-hour.Table 6 shows the calculations of the PCE level for both scenarios. Scenario 1 shows a PCE utility moving from generating all electricity with diesel to having a high renewable penetration hybrid system of 90%hydroelectric and 10%diesel generation.This change leads to a decrease in fuel costs by 90%.Consequently,their total cost per kWh drops and so does the PCE level,by about 33%.The result is an increase in the residential effective rate from 16 cents/kWh to 28 cents/kWh (about 75%). Scenario 2 shows a PCE utility moving from generating all electricity with diesel to having a low renewable penetration hybrid system of 9%wind and 91%diesel generation.This change leads toa decrease in fuel costs of about 9%.In this scenario,we assumed an increase in non-fuel costs of 3 cents per kWh sold and this leads to an increase of 17%in total non-fuel costs.After the decrease in fuel costs and the increase in non-fuel costs,the total cost per kWh increases 2 cents/kWh and the PCE level increases 1 cent/kWh.Consequently,although the residential effective rate ($0.18)decreases 1 cent/kWh (from $0.19 in the diesel only column),this decrease in the effective rate would have been larger if the fuel cost/kWh calculation in the PCE formula had only been done using kWh sold that were generated with diesel and not all kWh sold.This computational design is based on the formula being developed when it was assumed all generation would be done with diesel fuel.If fuel costs per kWh were calculated based only on the kWh sold generated with diesel,the fuel costs per kWh would have remained constant.Under this more accurate application of the formula,residential customers would have seen a 17%decrease in their effective rate. -31-March 14,2012 Table 6.Sample PCE level calculation before and after integrating renewable energy Scenario 1 Scenario 2 Generation Diesel Only Diesel-Hydro Diesel Only Diesel-Wind Renewables generation,kWh Diesel generation,kWh 0 1,682,428 (100%) 1,507,416 (90%) 175,012 (10%) 0 341,956 (9%) 3,866,416 (100%)3,524,460 (91%) Total generation,kWh 1,682,428 1,682,428 3,866,416 3,866,416 Total kWh Sold 1,454,633 1,454,633 3,646,178 3,646,178 Costs Total fuel consumed 89,307 9,290 288,771 263,231 Average fuel price 2.31 2.31 2.63 2.63 Total fuel costs 206,045 21,434 758,991 691,864 Fuel cost/kWh sold 0.14 (27%)0.01 (4%)0.21 (54%)0.19 (51%) Non-fuel costs 542,128 542,128 641,935 751,320 Non-fuel cost/kWh sold 0.37 (73%)0.37 (96%)0.18 (46%)0.21 (49%) PCE Calculations Total costs/kWh 0.51 0.39 0.38 0.40 Base rate 0.13 0.13 0.13 0.13 PCE costs 0.38 0.26 0.25 0.26 Eligible PCE costs 95%95%95%95% PCE rate 0.36 0.24 0.24 0.25 Rates Residential rate 0.52 0.52 0.43 0.43 -PCE rate 0.36 0.24 0.24 0.25 Effective rate 0.16 0.28 0.19 0.18 This uncertainty regarding the impact on the resulting PCE level may be a disincentive toward seeking renewable sources of generation.If integrating renewable energy sources results in comparable or lower costs,this results in a clear benefit to the utility and community as a whole.Table 7 illustrates the effects the residential customer may see in their monthly bill under the two scenarios discussed above. If these customers do not realize monthly savings on their bills,a "public relations”problem is likely to result for the utility.Customers focus on their monthly bills-not the price per kWh,not their total monthly consumption,not the PCE funding formula,nor other factors except what they must pay each month.An expected rational reaction of utilities would be to further increase non-fuel costs beyond the actual added costs from renewable energy integration to help offset the inaccurately large calculated decrease in the fuel costs portion of the formula. March 14,2012 Table 7.Example of effects on customers'bills from integrating renewables Scenario 1 Scenario 2 Diesel Only Diesel-Wind No PCE PCE No PCE PCE Residential rate $0.43 |$0.19 |$0.43 |$0.18 Monthly Bill @ 400 kWh/month |$172|$761 $172 72 Monthly Bill @ 600 kwh/month |$258 |$138]$258 133 Renewable energy and electric heat24 Given that space heating is the largest household energy expense in rural Alaska,sizing renewable energy capacity to increase economies of scale and produce excess electricity for space heating to displace fuel oi!usage can potentially make economic sense.This is especially important for rural wind- diesel installations.Wind is not a firm source of power and at times production can exceed the available load depending on the wind energy system capacity.In those circumstances,using the "excess”wind for heat via electric boilers,ceramic thermal stoves,or other electric heating devices avoids having to curtail or "dump”production.This disincentive under PCE is then magnified when adding renewable energy capacity for heat. Pricing of electric heat sales add another layer of complexity with the current PCE formula.The kilowatt-hours sold for heat should be priced to cover the cost of production yet less than the price of diesel fuel it displaces.Including heat kWh in the PCE formula further exacerbates the problem of dividing by all kWh sold rather than diesel generated kWh only.An alternate application of the formula, dividing solely by diesel electric kWh sold,and offsetting electric revenue requirements with heat sales revenues can more accurately compensate the utility while providing benefits to community members. Even when using diesel only systems and filing for PCE under the current program structure,the complete accounting of non-fuel costs seems to be a challenge and there is some evidence that the calculations of non-fuel costs may not be updated frequently enough,resulting in partial forgone PCE level.In most cases adding renewable energy to an electric generation system will increase non fuel costs,hence accounting for those costs accurately and adjusting rates appropriately is very important when adding high penetration of renewables for electric heat sales. We conducted additional analysis on how PCE levels are affected by high penetration wind diesel systems utilizing excess wind power for residential and community heating purposes.The analysis is based on ISER's IRECOS (Isolated Renewable Energy Economic Simulator)”and the following assumptions: -10%line loss -100%availability 4 This section presents shared model analysis done by our colleague Tobias Schworer to whom we are grateful for his contribution. 25 IRECOS was developed to analyze high penetration renewable energy systems while accounting for stochastic variables like wind speed and availability of the energy system.More information in regards to this model can be obtained upon request. -33-March 14,2012 -100%collection rate - Allexcess electricity is sold in form of heat to residents and the community at 8 cents/kWh -Electric heat is metered separately from electricity -Residential electric heat is provided in 30 of the 100 households of the case study community (limited heat sink dependent on number of stoves and seasonal demand for heat) -Community electric heat is used to heat water for the washeteria/school (unlimited heat sink) -The utility has one electric rate that is based on the remaining revenue requirement after heat sales are realized. -Costs are modeled based on real fuel and non-fuel costs observed in the case study community and estimated wind turbine costs described below. -Residential households consume 1,000 gallons of stove fuel per year and consume 500kWh/month on average -Retail price for stove fuel:$5.55/gal -Diesel price for utility:$4.55/gal The heat rate roughly equals the incremental cost of wind power which we estimate to be $0.075/kWh, consisting of $0.029/kWh for operations and routine maintenance,and $0.045 for repair and replacement.For the case study community,this price is equal to half of the energy equivalent stove fuel price. In order to investigate the sensitivity of PCE levels to the amount of renewable (non-firm)energy production,we show four scenarios (Table 8)with different levels of renewable energy production. Scenario 3 is diesel-only,while Scenario 4,5,and 6 are wind-diesel with installed nameplate wind capacity of 100kW,300kW,and 500kW,respectively.We assume that non-fuel costs in scenarios 4,5, and 6 are what they are in scenario 3 plus the incremental cost of wind $0.08/kWh multiplied by the amount of renewable energy generated.Thus,non-fuel costs are increasing the more wind turbine capacity is added to the system. We used IRECOS to run 1,000 iterations within two simulation runs.Based on the above assumptions, the wind-diesel system in our case study community would generate on average more than twice what it produced as a diesel-only utility,2,000,000 kWh instead of 900,000 kWh.Since wind-diesel systems of this size are capable of reducing fuel costs substantially,the cost of power is estimated to drop by ten percent,outweighing the increase in non-fuel costs.Since PCE levels are calculated based on the average cost (cost of power divided by all firm and non-firm power generated),PCE levels would drop from 54 cents/kWh for the diesel-only utility,to 15 cents/kWh in scenario 6.The effective electricity rate for residential customers consuming less than SOOkWh/month,under the current PCE formula would increase from 17 cents under the diesel-only to 39 cents/kWh in scenario 6.Assuming heat is sold at 8 cents/kWh,residential customers owning electric stoves would cut their heating bills by $500 annually. Considering the household budget for energy,the decrease in PCE would outweigh the reduction in heating costs.Under the current PCE formula,residents of communities harnessing wind for residential heating purposes would see an increase in their energy costs of up to 12 percent. -34-March 14,2012 On the other hand,reduced fuel costs in scenario 4,5,and 6 would benefit commercial customers who are ineligible to receive PCE,such as the commercial sectors or schools.In our case study community, commercial customers could realize a reduction of 23 percent in their cost of electricity. Our modeling exercises clearly showed that dependent on wind-diesel system configuration and rate structure,the benefits resulting from high penetration wind-diesel systems can be distributed non- proportionally within the community.The benefits from harnessing excess energy mainly go to commercial customers and the school/community given they have electric boilers.Residential customers,on the other hand,face increased energy costs mainly due to decreases in PCE payments under the current formula.Given enough capital investment in residential electric stoves,residents could realize additional energy cost reductions,however,the reductions in PCE would outweigh the benefits. Table 8.PCE and heat sales in high penetration systems _ Scenario 3 Scenario 4 Scenario 5 Scenario 6 ;Diesel-only Wind-diesel Wind-diese]Wind-diesel Wind capacity,kW 100 300 500 Generation Renewables generation,kWh 0 (0%)|278,363 (27%))$35,149 (56%)}1,391,980 (69%) Diesel generation,kWh 899,840"(100%)|735,313”(73%)|655,997"(44%)|630,823"(31%) Total generation,kWh 899,840 1,013,676 1,491,146 2,022,803 Consumption Electricity sold,kWh 809,552”(100%)!809,552” (90%)|809,552"(61%)}809,552"(45%) Heat sold,kWh 0” (0%)|92,340"(10%)|525,931” (39%)|1,005,857"(55%) Total kWh sold 809,552 901,892 1,335,483 1,815,409 Costs Fuel cost,$/kWh sold 0.47 0.28 0.17 0.12 Non-fuel cost,$/kWh sold 0.23 0.21 0.14 0.10 Wind for heat cost,$/kWh sold 0.08 0.08 0.08 Rates Heat rate,$none 0.08 0.08 0.08 Avg.electricrate,$0.70 0.56 0.54 0.54 -final PCE level,$0.54 0.36 0.22 0.15 Effective rate,$0.17 0.20 0.32 0.39 Residential customer energy costs Electricity,$998 1,191 1,944 2,360 Heat,$5,550 5,550 5,086 4,970 Total 6,548 6,741 3%7,030 7%7,330 12% Total community fuel displacement Generation,gal none 29,298 34,501 36,115 Residential space heating,gal none 2,413 6,967 8,696 Community water heating,gal none 273 8,331 20,561 Total fuel displacement,gal 0 31,984 49,799 65,372 Sources:Institute of Social and Economic Research,Isolated Renewable Energy Economic Simulator model, IRECOS,February 2012;Alaska Energy Authority,PCE program data. -35-March 14,2012 Distribution of renewable energy savings If the PCE level declines causing the effective residential rates to increase for PCE eligible kWh,PCE eligible rate payers consuming below the 500 kWh cap see little benefit on their monthly bills because the savings accrue to the PCE program,not the rate payer.Alternatively,if the PCE level remains the same,these same customers still see no change in their monthly bills.If the PCE level increases,the effective rate marginally declines providing some decrease to customer bills.But the latter only occurs if the renewable generation is more expensive than diesel fuel generation,which is counter to the purpose of integrating renewables and should not happen. Preliminary estimates of rate effects of the renewable energy grant funded projects on effective PCE rates showed the proportion of savings to PCE eligible ratepayers was about 1-2%with the remainder of savings split between PCE ineligible ratepayers and the PCE program.”This preliminary estimate (Table 9)is consistent with the estimates shown in example Scenario 1 (above in Table 6),and in Scenario 6 of renewable integration for heat sales (above in Table 8). Tables 9 and 10 provide example summaries of the savings distributions from integrating renewable energy generation based on scenarios 1 and 6 above.These examples use FY 10 PCE data from utilities to calculate the specific saving distributions across different classes of rate payers and the PCE program. Table 10 Scenario 7 is based on scenario 6 in Table 8 above but applies a community's specific cost structure to calculation of potential distribution of savings from integrating renewable resources. Table 9.Example of PCE savings distribution from integrating renewables Scenario 1-Diesel-Hydroelectric Savings For eligible customers (48%of all kWh sold)distribution Production cost savings/kWh $0.12 PCE eligible kWh 692,489 PCE program savings/kWh (based on 95%covered by PCE program)$0.12 Tota!PCE program savings $81,798 45% Customer savings (based on 5%not covered by PCE program)$0.01 Total eligible customer savings $4,305 2% For non-eligible customers,100%savings (52%of all kWh sold) Non-eligible customers'savings/kWh $0.12 Total non-eligible kWh $762,144 Total non-eligible customer savings $94,763 53% Total production savings from renewable energy integration $180,866 Source:Alaska Energy Authority,PCE program data. 6 Alaska Energy Authority,calculations for the Renewable Energy Fund Grant program review,January 2012. -36-March 14,2012 Table 10.Example of PCE savings distribution from integrating renewables &excess capacity for heat Scenario 7-High Penetration Wind-Diesel Savings For eligible customers (37%of all kWh sold)distribution Production cost savings/kWh $0.40 PCE eligible kWh $0.380 PCE program savings/kWh (based on 95%covered by PCE program)$0.020 Total PCE program savings $134,203 36% Customer savings (based on 5%not covered by PCE program)$0.020 _Total eligible customer savings $7,063 2% _For non eligible customers,100%savings (63%of all kWh sold) Non-eligible customers'savings/kWh $0.40 Total non-eligible kWh 591,183 Total non-eligible customer savings $236,473 63% Total production savings from renewable energy integration $377,740 Source:Alaska Energy Authority,PCE program data. In summary,the current PCE formula arguably becomes a disincentive against energy efficiency and renewable energy integration in relation to all of these issues. Alternative PCE funding formulas One of the objectives of this research is to analyze whether there are alternate funding formula structures to calculate PCE payments that would eliminate or reduce the energy efficiency and renewable energy disincentives created by the current PCE funding formula,and ideally,provide market incentives to encourage energy efficiency and renewable generation.7'This goal is congruent with international energy subsidy reform guidelines published by the United Nations in which it states that "a good subsidy is one that enhances access to sustainable modern energy or has a positive impact on the environment,while sustaining incentives for efficiency delivery and consumption”(UNEP,2008).These guidelines suggest basic principles needed in implementing reforms to existing programs.Namely,a subsidy should be well-targeted,efficient,practical,and transparent among other features. When analyzing alternative funding formulas and comparing them to the current PCE funding formula, we used the following key parameters to evaluate whether the alternatives are improvements over the current system: v¥Improves market signals ¥Does not penalize increased energy efficiency or integration of renewable energy Y Hasan equitable distribution across households ?7 in order to analyze the programmatic effect of potential changes in funding formula structures from the current structure,the eligible kilowatt-hours cap was held constant at 500 kwh per residential customer per month. -37-March 14,2012 ¥Does not decrease the current distribution of funds to a community ¥Simplifies administration for utilities and state agencies and enhances understanding by customers/rate payers v¥Simplifies formula and information needs for implementation In addition,previous research illustrates the impacts different types of economic assistance structures have on incentives.In 1987,an important conceptual review of potential structures of the PCE program was completed for the Governor's Energy Policy Task Force (Mitchell 1987).In this review,Mr.Mitchell analyzed and ranked various program structures and funding formulas with respect to maintaining utility and customer market signals and economic incentives (Table 11).This research evaluated incentive effects of a subsidy program by analyzing what proportion of electricity generation cost savings are kept by the utility under various program structures (Table 11,Utility Incentive).Customer incentives were evaluated by analyzing the proportion of cost reductions from energy conservation measures kept by the customer (Table 11,Customer Incentive).According to Mr.Mitchell's research,under a Fixed Payment Formula utilities are able to keep 100%of the benefit from generation cost savings,and customers are able to keep 100%of the benefits from savings through energy conservation measures they implement.Our research extends this analysis by defining specific formulas and using PCE data to model their potential impacts to PCE recipients.We modeled specific potential formulas to estimate different outcomes compared to the current PCE formula based on the criteria listed above. Table 11.Summary of incentive effects program Utility Customer 7:Incentive Incentive PCE Rate [current]13%33%, significantly PCE FormulaRate 100%___lessthan33% _Shared Savings Rate 58%___less than 33% Baseline Rate eee 538%0I8%.. Postage Stamp Rate i 8%33%, _Fixed Payment Formula 100%i.100% _Fixed Payment Cost 98%100% Fixed Payment Formula -No Excess 100%75% Source:Table recreated from The Effect of Electricity Subsidy Programs on the Economic Incentives for Improving Generation and End-Use Technologies,A comparison of Power Cost Equalization and Alternatives;prepared for the Governor's Energy Policy Task Force,Alan Mitchell,1987. The current PCE program uses a rate/cost formula to calculate PCE reimbursement rates.The key variables in the current PCE formula for calculating rates are non-fuel costs,fuel prices and consumption.Under a formula rate program,the calculated rate is then applied to the eligible amount of kilowatt-hours to determine the PCE payment. -38-March 14,2012 In contrast,a Fixed Payment formula provides a payment per given time period independent of rates and consumption.The fixed payment,however,can vary by community and be determined based on the differences in prices customers pay or the cost of producing electricity. We examined six potential formula structures and then did sensitivity analysis by changing the parameters resulting in fifteen possible scenarios.The examined formulas included a:cost index,rate index,combined cost and consumption index,geographic price differential index,life line fixed payment, and postage stamp rates.”*We found that the cost and index formulas had the potential to slightly improve market signals but did not provide much improvement over the current PCE funding formula based on review parameters.The formulas with the greatest potential and review criteria are shown in Table 12.7? Table 12.Evaluation of reviewed formula structures based on reforming criteria "Structure Improved = - -Doesnot Nolarge -Equitable -Simplify -*Simplify | market signals penalize price distribution administration formula efficiency increase to or households renewables Seasonal Fixed Y Y Y Y Y Y Payment 5101 a en Rate and Y,butdampened Y-RE,N-EE Y oy marginal ON - Consumption EO FOP ae esesassssnccsaesceececeansesenssssaesssanseesssaasaessesseasanseaseseases Fixed Payment Unclear Unclear N Y marginal "NO Formula,Rate fa aeennsesenenseneneenenstensFixedPaymentUnclearUnclearN"Y NN. Formula,Cost Source:PCE monthly program data CY 2010 and authors'calculations. Seasonal Fixed Payment Formula Among alternate PCE structures we analyzed for this report,one deserves particular attention.We developed a fixed payment formula based on the per gallon price of fuel ina community,a generation efficiency rate,and the mean seasonal household monthly kWh consumption level.A fixed payment is calculated by dividing the price per gallon of fuel oil in a particular community (regardless of whether they generate their power with fuel oil or other sources;fuel price is used as a proxy to measure how 8 Other potential structures were also tested,but did not yield results due to data issues or invalid assumptions. For example,we attempted to model a formula rate structured based on fuel cost and State of Alaska geographic cost differential used to set pay differentials in different regions of Alaska.However,the geographic differentials are based on too few communities and do not include many PCE communities.We also attempted to model a formula that accounted for high overhead or lack of economies of scale.However,many communities,reviewing the relationship between rates and levels of electricity production,had no clear relationship.This is probably due to the fact that most PCE communities are operating a production levels too low to capture any economies of scale.For information on a postage stamp rate,see Fay and Villalobos,2012,All-Alaska Rate Analysis. °Details of these analyses are available upon request. -39-March 14,2012 much more costly it is to generate in one village compared to others)by a fixed generation efficiency of 14 kWh per gallon.This factor is then multiplied by the seasonal median monthly residential consumption. [(Fuel price $/gallon)+(kWh/gal)]*Average monthly consumption per season The resulting fixed payment would be applied to the rate payer's bill every month and paid to the utility. However,to accommodate changes in seasonal consumption needs,the fixed payment would change by season so that during the summer months (April-September)the customer receives a lower fixed payment reflecting lower seasonal consumption levels,and in the winter months (October-March)the fixed payment would be higher reflecting higher winter consumption®. Applying this formula results in similar total residential disbursements as the current PCE funding formula.However,because the payment does not depend on the amount of fuel consumed and the customer receives payment regardless of consumption or rates,household and generation energy efficiency and renewable energy incentives are reestablished.If the utility is able to produce energy at lower cost through gains in demand or supply side efficiency or using renewable energy,the benefits to the utility and customer increases.Figure 10 shows how the communities with higher fuel prices will receive higher monthly payments. Figure 10.Average annual PCE payment with respect to fuel prices 10.00 S 8.00 ma yA =x -gO AAwA6.00 zx g<=4.00 a S 2.00bebe -50 100 150 200 250 300 Monthly Fixed Payment «Annual Payment M!Summer Payment Winter Payment Source:PCE monthly program data CY 2010 and authors'calculations. This formula structure is particularly simple and significantly decreases the administrative burden rural utilities face to file for PCE payments with the RCA and AEA.Because of its simplicity,the administration %0 Appendix G shows CY 2009 PCE program data including residential rates,PCE level and fuel prices;it also shows the estimated monthly payments per customer under the current PCE formula and the Fixed Payment Seasonal formula. -40-March 14,2012 of the program could potentially be given to a single agency resulting in lower administrative costs to the state.*? An important feature of this potential Seasonal Fixed Payment formula is that if the customer has an electric bill lower than the fixed payment,the balance could be carried over to future months as a credit.At the end of the year if the customer has a net credit,there are a number of options that the program could offer to customers.For example,the customer could use the credit to purchase more energy efficient appliances and/or lighting products,transfer the credit to a relative in the village who may need it,or simply carry it forward to the following year. Table 13.Actual and estimated residential disbursements by funding formula,CY 2009 Estimated Average sae Total Payment per |Structure Description Disbursement Residential (Million)Customer Current PCE Formula $26.4 $125 Current PCE Formula All customers @ 500 kWh $45.5 $184 @ current consumption 928.0.3128|Rate-Consumption Index @ fixed 250 kWh/month $243984.@ fixed 500 kWh/month $48.5 $187 .100%of mean consumption $17.8 $67FixedPFormula,R wcreeeeteceneenenessccettstenascnentenntaasnannansastiatansasensacnnsnaeteensxedPaymentFormula,Rate 50%of mean consumption $8.8 $33 _100%of mean consumption 294 9137 .50%of mean consumption $7.0 $68Formula,Costs --crcvsensarsvsstocencnnnonnennsrentactpentrnnncnnnenagealennennncannnnrnngcaenesFixedPaymentFormula,Costs "100%of mean consumption,RCA $12.0 $192 50%of mean consumption,RCA $5.9 $96 @ 14 kWh/gallon $29.2 Summer $95 Summer Winter $111 340 kWh/customer/month Annual $103 .WinterSeasonalFixedPaymentFormula400kWh/customer/month @ 12 kWh/gallon $34.1 Summer $110 Winter $130 Annual $120 Source:PCE monthly program data CY 2010 and authors'calculations. This Seasonal Fixed Payment formula is consistent with previous research findings showing that decoupling the funding formula structure from fuel costs helps remove incentive barriers to energy efficiency and renewable energy development.However,this formula represents preliminary analysis on a potential new formula design.Although fuel prices may reflect differences in generation costs across rural utilities,the suggested formula does not account for differences in costs resulting from utility size and/or non fuel costs.As previously explained in this report,lack of economies of scale result in fixed costs making up a larger proportion of kWh production costs for smaller rural utilities. 31 Additional research is needed to estimate and analyzed the amount and areas where savings can occur. -41-March 14,2012 Additional in-depth research is required to determine an effective way to account for that variability among utilities.In addition,a preliminary review of PCE data shows that rates and costs do not seem to have an expected clear relationship which may be a consequence of lack of data availability or the complexities of tracking costs as utilities may receive assistance from other state programs (e.g.for maintenance,infrastructure upgrades). This formula design relies on only one cost variability proxy (fuel price),however fuel prices are volatile and this volatility may be passed along in the formula because as currently constructed there is no mechanism to smooth potential volatility.This could be addressed by using rolling averages of fuel prices.However,the research presented in this paper suggests that decoupling can be achieved and incentive barriers removed. Policy considerations The PCE program is critical to many rural residents;restructuring the program to improve its effectiveness and efficiency is complex.There are no simple solutions to addressing the problems of high costs that rural utilities and residents face.In seeking solutions to these issues,it is important to approach the PCE program in the context of total energy use in rural Alaska.The PCE program alone has not and will not solve the fundamental issues that result in high cost energy and the impacts this has on rural residents. Most PCE communities depend on fuel oil for both electricity generation and space heating. Consequently,high fuel oil prices increase both the cost of electricity and space heating,thus magnifying the pressure on households.Putting electricity consumption in context,space heating is the largest share of household energy expenses (40%),followed by transportation (33%),Figure 11,(Colt,2011). PCE provides important relief on electricity rates;however only about 27%of fuel consumed in PCE communities is used to produce electricity (Figure 11).On top of this,only about 30%of kWh used in eligible communities is affected by PCE effective rates-so the PCE program only touches about 10%of the energy picture in rural Alaska. Figure 11.Energy use in surveyed PCE communities by category Electricity 27%Transportation 33% Source:Energy Use the Big Efficiency Picture.Presentation at the Alaska Rural Energy Conference by Steve Colt (2011),ISER. -42-March 14,2012 This composition of energy use is reflected in the course of this and other rural energy research and interviews in which we found a high level of "energy insecurity”expressed by rural residents.Given volatile and unpredictable energy prices and past changes in legislative funding of the PCE program, many residents are understandably concerned about the ability to stay warm,gather subsistence resources and keep the lights on.Reviewing and improving rural energy programs must be done from a "whole village energy”perspective. From a whole village perspective,one of the first objectives is to assist rural residents to be as energy efficient as possible to reduce the impacts of energy price volatility while maintaining quality of life and reducing anxiety over energy security.In addition to the current on-going weatherization efforts in rural communities,energy efficiency and conservation could be maximized to fulfill this objective.This does not mean that new efficiency and conservation programs are needed but instead existing programs can be better coordinated and delivered-when a home or building is weatherized,it can also be retrofitted to improve electrical efficiency.Commercial and public building can be weatherized and electrical energy efficiency measures installed simultaneously with residential housing weatherization and rebate programs. A recent weatherization and electrical retrofit on 13 community buildings and four teacher housing units in Nightmute was done as a concurrent effort.This more comprehensive and integrated effort resulted in estimated annual electric power savings of 59%and thermal energy savings of 56%(Butler,2010).It is likely residential buildings experience similar savings and whole village efforts could produce substantial energy saving for residents,public buildings,businesses and schools.Realizing these substantial demand side efficiency gains is a first step to solving the challenge of high rural energy costs for residents.It logically proceeds before addressing supply side generation,either fossil fuel,renewable or disaggregated,because the generation capacity would be inappropriately sized for the demand and would continue to overcapitalize generation and waste high priced fuel.These actions could take place in concert with the assistance that a re-formulated PCE program can provide. PCE Funding Formula After reviewing possible alternatives,the Seasonal Fixed Payment Formula seems to be a viable option to support rural residents;it removes or decreases current barriers or disincentives found in the current PCE funding formula.Its simplicity could also translate into administrative savings that could be repurposed to support efficiency and demand side solutions. Centralized versus disaggregated generation Power Cost Equalization eligibility depends on having a centralized utility.As a result,for some of the smallest communities there is an incentive to over capitalize electricity generation despite the potential for less capital intensive solutions.Institutional mechanisms that emphasize conventional solutions "raises the propensity to ignore decentralized supply options”(Hourcade &Colombier,1990).For communities with very small populations,a traditional centralized utility may translate to higher cost power as compared to disaggregated generation because of the added cost of administration, transmission lines,and building necessary redundancy into the system among other costs that could potentially be avoided through disaggregated generation,though each individual household may -43-March 14,2012 experience differing degrees of reliability and access to power.If economic assistance for electricity was not restricted to centralized utilities,villages could organize through their local tribes or government to create mechanisms to support current or alternative ways of disaggregated generation that may be less costly to operate.It may also result in job creation that can be more compatible with the subsistence life styles of many rural residents and potentially more sustainable in the long run.Further research is necessary to determine the population size and other circumstances at which a rural village may be able to access lower cost electricity through disaggregated self-generation rather than opting to runa centralized utility. Expanding eligibility to commercial customers In the early years of the PCE program,commercial customers were eligible to receive PCE;it was not until FY2000 that commercial customers became ineligible primarily as a program cost containment measure.Commercial rate payers were eligible to receive PCE assistance for the same amount of kilowatt-hours as residential customers (700 kWh per month in 1999,the last year they received assistance). The sharp increase in fuel prices since 2008 has aggravated many challenges rural residents face in keeping their communities viable places to live.During the 2011 Alaska Rural Energy Conference,a number of participants raised the topic of expanding eligibility of PCE to include commercial customers to help lower the risk of businesses failing due to the economic pressure from high energy prices.Based on 2009 PCE program data on the number of commercial customers and kilowatt-hours sold,we estimated how much it would cost to expand eligibility to commercial customers.The estimates were calculated at eligibility of 700 kWh per month (level when commercial customers were last eligible)and at SOOkWh per month (current residential eligibility level). Under the current PCE program structure,funding for disbursements would have to increase about $11 million or 35%,to provide assistance to commercial customers at the 500 kWh per month level.If eligibility was available for 700 kWh per month,funding would have to increase about $15 million,or 47%.Average commercial customers'consumption in 93%of PCE communities would exceed the maximum eligibility cap of 500 kWh per month.At the 700 kWh per month cap,the average commercial customers'consumption would exceed the 700 kWh per month eligibility cap in about 77%of PCE communities. At the 500 kWh level in about 38%of communities,most commercial customers would see relief on half or more of their total electric consumption.In 60%of communities,most commercial customers would see relief on half or more of their total electric consumption at the 700 kWh level.Figure 12 and Figure 13 shows the number of communities with different average levels of electricity consumption by commercial customers under the two kWh caps. Our analyses show that renewable energy project development primarily benefits commercial customers and those not eligible for PCE.So increased renewable energy development and energy efficiency improvements should reduce the need for PCE for commercial customers. -44-March 14,2012 Figure 12.Average commercial consumption levels in PCE communities (500 kWh cap) 90 80 70 80 60 5a 50 40 30 17 12Numberofcommunities 0 T q qT T uJ <500 S501to 1,001to 2,501to 5,001to >10,000 1,000 2,500 5,000 10,000 Average commercial consumption levels mw Commercial cap at 500 kWh Source:PCE monthly program data CY 2010 and authors'calculations. Figure 13.Average commercial consumption levels in PCE communities (700 kWh cap) 90 80 70 60 50 40 80 40 Numberofcommunities10 + i¢)qT T U LI qT od <700 =701to1000 1,001to 2,501to 5,001 to >10,000 2,500 5,000 10,000 mw Commercial Cap at 700 kWh Source:PCE monthly program data CY 2010 and authors'calculations. Increasing residential customer eligibility cap to 700 kWh per month In the spirit of providing additional assistance to households,recently introduced House Bill 294 proposes to increase the residential customer eligibility ceiling to the 1999 level of 700 kWh per month. Appropriate to the discussion of raising the PCE ceiling are two important questions.Does increasing the ceiling benefit those who are targeted by the change?And,what is the additional cost to the state? -45-March 14,2012 In a previous section of the report we extensively discussed consumption patterns among PCE communities and their variability within and by region.This review clearly shows that on average residential consumers in most PCE communities do not consume all of their eligible kilowatt-hours.In CY 2009 total PCE disbursements were about $31 million;however,if all eligible residential customers consumed all their eligible 500 kWh,year round disbursements would have been about $45.5 million. Hence,in effect the lower levels of consumption found among PCE customers lowers current program costs by over 30%annually. Increasing the eligibility threshold is not likely to provide substantial additional assistance to rural households.Limited levels of consumption among PCE communities suggest that given the current levels of PCE assistance,it is the income and/or other effects that have a larger impact on their ability to consume more electricity.Customers who would benefit the most from an increased eligibility cap are residential customers with lower effective rates who are already consuming significantly higher amounts of electricity each month,residential customers with higher incomes that consume more electricity than the average customer,or a small portion of customers that due to moderate effective rate and income levels are able to increase their electricity consumption due to seasonal changes during the winter.This phenomenon is well documented in the literature:"The strife to ensure equal access to electricity for all citizens through subsidized rates,increases the consumption by higher-income consumers,and does not guarantee access to basic services by the poorest residents”(Hourcade &Colombier,1990). Consequently,it is an inaccurate assumption that increasing the eligibility cap would translate into extensive economic relief for all PCE eligible customers,or those who need the relief the most. We estimated the increase in total disbursements to residential customers in CY2009 if the eligibility cap had been 700 kWh per month.Raising the cap would have increased disbursements to almost $34 million from $31 million,or less than 8%.However,increasing the kWh ceiling would also increase the potential liability to the state by 40%to about $63 million,if all residential customers consumed up to the higher cap. -46-March 14,2012 References Alaska Energy Authority.(2009).Power Cost Equalization Program Guide.Anchorage:Alaska Energy Authority. Alaska Energy Authority.(1990).Second Annual Statistical Report of the Power Cost Equalization Program,Fiscal Year 1989.Anchorage:Alaska Energy Authority. 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Villalobos Melendez,A.(2012,May,forthcoming).Aligning Electricity Energy Policies in Alaska:Analysis of the Power Cost Equalization and Renewable Energy Fund Programs (Master's thesis).Fairbanks, Alaska:University of Alaska Fairbanks. -49-March 14,2012 Appendix A.PCE funding levels per year Average .Annual |PCE Funding Level DetailProgramcaPCEFunding|PCE No.of PCE No.of PCE No.of PCE No.of ;Level |Level.Months __Level Months.Level_.Months__Level.Months PPCA 1981 100.00%|100%12 PCA 1982 100.00%|100%12 PCA 1983 100.00%|100%12 PCA 1984 100.00%|100%12 PCA PCE 1985 100.00%|100%12 PCE 1986 100.00%|100%12 PCE 1987 100.00%|100%12 PCE 1988 100.00%|100%12 PCE 1989 100.00%|100%12 PCE 1990 100.00%|100%12 PCE 1991 100.00%|100%12 PCE 1992 81.67%|100%1 80%11 PCE 1993 89.17%|80%90%11 PCE 1994 95.00%|90%2 95%100%2 PCE 1995 97.50%|100%10 85% PCE 1996 97.50%|85%2 100%10 PCE 1997 85.00%|85%12 PCE 1998 85.00%|85%12 PCE 1999 83.08%|85%10 73.5%2 PCE 2000 100.00%|100%12 PCE 2001 97.83%|100%11 74%1 PCE 2002 80.33%|92%7 80%4 66%1 PCE 2003 86.17%|84%8 90%3 92%1 PCE 2004 82.25%|92%3 83%6 75%2 63%1 PCE 2005 72.08%|81%2 76%5 65%4 63%1 PCE 2006 88.17%81%4 78%3 |100%5 PCE 2007 94.50%|100%6 89%6 PCE 2008 100.00%|100%12 PCE 2009 100.00%|100%12 PCE 2010 100.00%|100%12 Source:Statistical Reports of the Power Cost Equalization Program 1988-2010 -50-March 14,2012 Appendix B.PCE appropriations and disbursements over time v Program FiscalYear Appropriations Total Disbursements _ c on.($)($) PPCA 1981 2,657,600 2,183,168 PCA 1982 9,300,000 6,419,408 PCA 1983 8,300,000 8,327,152 PCA 1984 8,300,000 8,740,820 PCA/PCE 1985 19,100,000 13,800,868 PCE 1986 21,700,000 17,785,390 PCE 1987 13,840,299 16,771,338 PCE 1988 15,067,900 17,018,680 PCE 1989 19,724,000 17,104,631 PCE 1990 16,814,000 17,785,256 PCE 1991 16,912,100 19,607,435 PCE 1992 15,029,700 15,731,165 PCE 1993 18,026,700 17,341,042 PCE 1994 17,920,000 17,516,024 PCE 1995 18,635,000 18,493,448 PCE 1996 19,385,600 19,201,515 PCE 1997 18,500,000 17,906,275 PCE 1998 18,700,000 18,503,992 PCE 1999 18,050,000 17,949,524 PCE 2000 15,700,000 14,415,676 PCE 2001 17,090,222 17,076,203 PCE 2002 15,700,000 15,469,105 PCE 2003 15,700,000 15,448,480 PCE 2004 15,700,000 15,617,225 PCE 2005 15,700,000 15,370,599 'PCE 2006 22,020,000 21,494,137 PCE 2007 25,619,000 25,437,093 PCE 2008 28,560,000 28,137,549 PCE 2009 38,500,000 37,029,584 PCE 2010 37,660,000 30,627,339 PCE 2011 51-March 14,2012 Appendix C.Residential and effective rates of PCE communities,2001-2010 Residential and Effective Rates of PCE communities (2001-2010) Nominal$KWh 2001 2002 2003 .2004 2005 wd _ ;.7 -_-_-_--a =-=-- oe 2006 2007 2008 2009 2010 Jee oe |cK...J Residential Rate CL]Effective Rate (residential -PCE)| Graphs by Year Residential and Effective Rates of PCE Communities (2001-2010) 2010$/KWh 20014 2002 .2003 .2004 2005 4 eakd ==aeere 00s 2007 2008 2010 = j$te $a $a $4 $45the.{Cd Real Residential Rate C-.. _]Real Effective Rate (residential-PCE)| Graphs by Year -52-March 14,2012 Appendix D.Effective residential rates and consumption of electricity in PCE communities,2008-2010 Effective Residential Rates and Consumption in PCE Communities $/kWh 2008 2009 2010 0 J e e S ° e -4*e e o i wc o 2 BS 4 =uJ ;-ae "A ee o- 0 500 1000 1500 0 500 1000 1500 0 500 1000 1500 Average Residential Consumption per Customer per Month,kWh Graphs by Year -53-March 14,2012 Appendix F.PCE communities characteristics of importance as factors of electricity production and demand22 Fuel Average Community Residential Fffective prices kwh Average Household Median .Rate Residential .Income Name Census Region Rate 2010S 2010$__-s per Population Income,*2010$Monthly (2004)per kWh er kWh per gallon Consumption 2004 2010SPgallonP(2010$$) . Adak a.Aleutians West (CA)0.73 0.23 355SAF 8B105 i:2*64,453" Akiachak Bethel (CA)0640.24 3.72)15.05 306!624.441,459 Akiak Bethel (CA)64082 455 1245 8B339 i.430,372 Akutan AleutiansEast 033 0143.22889 8B12 2 __.39,049| Alakanuk Wade Hampton (CA)=0.63 0.20 3.90 1355 007 AN 695 5____30,483__ _Allakaket Yukon-Koyukuk(CA)0.70 0.19438 13856 287105 ee!2°__23,824" Ambler.Northwest Arctic 0.76 0.21 447 1413 888258 eee 4 ___50,330__ Anaktuvuk Pass NorthSlope=6 14 520 1052 0 044309 cece 3.____60,743 Angoon Hoonah-Angoon (CA) *Income and household data are originally sourced from the Internal Revenue Service for the Viable Business Enterprises for Rural Alaska project by ISER and other partners (http://ced.uaa.alaska.edu/vibes/VIBESsummary.pdf).The Income and household data represent calendar year of 2004 and adjusted to 2010 dollars.Although more recent data is available through the U.S.Census Bureau America Community Survey (ACS),we present older data because we believe it is more accurate.ACS data is available as a 5 year average and is the result extrapolation of sampled data.However,due to the challenges of small samples in Alaska,ACS tends to have very large margin of errors severely limiting its value.When data from the VIBES project was not available,ACS data is presented; this is indicated by the asterisks next to the data point. , -54-March 14,2012 Fuel Average Community Residential Effective Prices kWh Average Household Median | .Rate Residential .Income Name Census Region Rate 2010S 2010$per Population Income,2010$Monthly (2004)*:per kWh er kWh per gallon Consumption 2004 20108PgallonP(2010$$) 0.48 0.20 2.78 14.08 412 450 .3 34,550 Aniakoo.Bethel (CA)2 07S 0-27 3-62.13.39 0 AB 994 eee 3...48,450 | Anvik Yukon-Koyukuk(CA)0.68 0.19 4.47 10.92 0 BAF 72 eee 3...24,587. Atha:Aleutians West (CA)0 0.710.240 4.19 10.793898 63.3...35,796 | _Atmautluak Bethel (CA)0-78037359698 3840269 ieee 5____43,871| _Atqasuk North Slope 0 O19 O18 30008397838s2120 477,065. Beaver Yukon-Koyukuk (CA)0.56 0.140 38000 BB.73.333,264 Bethel Bethel (CA)i 0:50.0.16 5.05 13.76 505 93,966 ww...3.____66,321| Settles Yukon-Koyukuk(CA)0 0.62 00.19 2.650 12.138882 BB 357,128Brevig Mission Nome (CA)oe 0:60!0.19 4000 44200 ANB:398 4 ___.25,310_ Buckland NorthwestArctic053!0.23500 14-42 08238.392.5.44,352 | Central Yukon-Koyukuk(CA)O60 0.32 2.27 10.82067 96 eee2*14,278" _Chalkyitsik Yukon-Koyukuk(CA)0.97059 4-18 10.59 A A.2 ___18,801. Chefornak Bethel (CA)0 064 026 413 12.95 A930 ieee.S___41,139- Chenega Valdez-Cordova (CA) -55-March 14,2012 Fuel Average Community Residential Effective Prices kWh Average Household Median .Rate Residential .Income Name Census Region Rate 2010S 20108 per Population Income,x20105Monthly(2004)per kWh er kWh per gallon Consumption 2004 2010SPgallonP(2010$$) Bay 0.47 0.17 3.30 6.64 343 80 4 62,190 Chevak Wade Hampton (CA)=ss 066 019 4.038 1287 80 931.531,095_ Chignik Lake and Peninsula =0.52.18 27S 103428H 84.339,628-Chignik tagoon Lake and Peninsula 0.45 0.15 3931060 eB 82 ee 3.___106,789_ _Chigniklake Lake and Peninsula =0590.19 280 WT.4 _A7,967|Chilkat alley.Haines048 9.20 320 8cece 43,855* Chistochina Valdez-Cordova(CA)0520.19 2.31 1050 28 93s2*47,040"| Chitina Valdez-Cordova(CA)=0.55 0.25 2.78 13.25 2.133!2*12,763"| _Chuathbaluk Bethel(CA)101)0.26 5-05 10-53 2 107,nn.439,669 Circle Yukon-Koyukuk(CA)0.68 0.192.43 1063 800 115 2*15,060"|Coffman Prince of Wales- ove Hyder(CA)0438 018251 13.31806 207 ee.350,619| ColdBay AleutiansEast=68 1B 865 13.54 AO110.2 64,504 Cordova Valdez-Cordova(CA)==0.34024 2.23 13-40 000 ST2,266 257,983 Prince of Wales- rag Hyder (CA)0-220-162.30 1036 S044194.3____52,410| Crooked A (cc -56-March 14,2012 Fuel Average Community Residential Effective Prices kWh Average Household Median ; .Rate Residential .income Name Census Region Rate 2010S 2010S _-s per Population -_Income,2010$Monthly (2004)*per kWh er kWh per -_gallon Consumption 2004 2010$P gallon P (2010$S) Creek 1.01 ;0.26 5.25 11.77 282 106 4 20,248 Deering NorthwestArctic0.78 03500 470 1A BD126 a.3____38,567| DillinghamDillingham(CA)44S0.16 3.60)15.2000 AMS2,245 3___.59,538 Diomede Nome (CA)occOBEO14 5859.88 258.180.3__.27,479|Southeast Fairbanks Dotlake (CA)ec ceeeee eee 933.0 OV 208 BABees.1*_38,461* Southeast Fairbanks Fagle (CA)cece ceeee eee eee O83!0.19 2.88 12:30 0 209 82!2°25,047" Fek Bethel (CA)0:69!0.20 3.831203 269...283 ee.420,248| Egegik Lake and Peninsula.9.93036.430009.6200265 ee 3._...53,223 Ekwok Dillingham(CA)O54!0.14 370 eeB38 i...V7.3____18,801__ _ElfinCove___Hoonah-Angoon(CA)0-57 0.18 4.420 12-86 0 82 23 ee 2...39,049 Elim a...Nome (CA)0840.19 4.07 13.67 3938 i:302 ee.446,488 _Emmonak Wade Hampton (CA)0-64.0.20)3-90 13-520Aa 766 eee 438,085_ Fort YukonYukon-Koyukuk(CA)0 O61 0.2200 3.78 1492002604.333,987. GalenaYukon-Koyukuk(CA)0:57!0.23.4.30 13.03 0 365 $39 cee 370,722_Gambell Nome (CA) -57-:March 14,2012 Fuel Average Community -Residential Effective Prices kWh Average Household Median .Rate Residential .Income Name Census Region Rate 2010$20108 per Population Income,2010$Monthly (2004)*per kWh er kWh per gallon Consumption 2004 2010$P gallon P (2010$$) oo 0.62 0.19 3.93 13.38 370 680 4 36,397 Golovin Nome(CA)OT019 5.10 12.23 0 8154.336,880__Goodnews Bay Bethel (CA)64020 3.838 12.90 82247 a.3____18,801| Grayling Yukon-Koyukuk(CA)O72 020 4710.83 1820.4 25,310| Gustavus Hoonah-Angoon(CA)=0.58 0.282.72 1547 I 464 i...2 40,225| Haines Haines020TS 818 13-24 50:1,673 2*44,877" Southeast Fairbanks 11,2953 Healylake =(CA)06 A253 ABOF Be!2 oo ceeeeee *Prince of Wales- Hollis Hyder (CA)8210162800 401:118 2*27,866" Holy Cross Yukon-Koyukuk (CA)0.68.19.4.10 1263 322 1860.4 25,310| Hoonah Hoonah-Angoon(CA)048 0.20 240 14.27 AeA762.345,156 Hooper Bay Wade Hampton (CA)0-62)0.19 4.00 13.53 388:1,054 i.430,854 Hughes Yukon-Koyukuk(CA)0.72 0.34 4.450 12.76 28 7A.328,202| Muslia Yukon-Koyukuk(CA)064 0.204 403...267 nn...331,239PrinceofWales- Hydaburg Hyder (CA)0.21 0.16 2.88 (3.84)505 386 3 36,591 -58-March 14,2012 en A Fuel . Average Community Residential Effective Prices kWh Average Household Median : .Rate Residential .Income Name Census Region Rate 2010$2010$_-sper Population Income,2010$Monthly (2004)*|perkWh -er kWh per gallon Consumption 2004 2010$P gallon P (2010$$) lgiugig Lake and Peninsula 0.7500.17 6.33 10-65 0 BN 8.3__.25,165 Make.Petersburg(CA)0-480.20 2.71 13.3400 374$78.3____45,868| _Kaktovik North Slope 018!0.16 3.70 45.78 862 oe 3____64,359 _Kalskag Bethel (CA)0.0:60 0.19397.13.42 0 398 196.4 ___32,782 Kaltag Yukon-Koyukuk(CA)0-64 0.19 4.03 14.23 388.187.333,747| Karluk Kodiak Island 0:62 O14 358155 AO.38 eee 3.__.22,176| _Kasighuk Bethel (CA)055!0.18 3-97 13-53 82:$48 5...36,446 | Kiana.Northwest Arctic 069 0.19 4-40 12-75 A238 356 i.445,920| King Cove AleutiansEast202501S 236 1013 a824.353,099 Kipnuk Bethel (CA)085!0.26 3.65.6.37 0 AMO!640 i.9____39,772| _Kivalina NorthwestArctic0-72!0.20 4:40 12.78 AF.370 5...35,674 Prince of Wales- "Klawock Hyder(CA)OPE06 285 0 S20723.340,496 _Klukwan Hoonah-Angoon(CA)0.48 0.20 320 BL.76 2*27,760" Kobuk Northwest Arctic 0.88 0.30 422 133 4 35,578 -59-March 14,2012 Fuel Average Community Residential Fffective Sees kwh Average Household Median- .Rate Residential .Income Name Census Region Rate 2010S 2010S per Population Income,*2010S Monthly (2004)per kWh er kWh per gallon Consumption 2004 2010SPgallonP(2010$$) Kokhanok Lake and Peninsula =0.92 0.27)457 12.15 887 170.322,658| _KoliganekDillingham(CA)ST0.14 5.06 836 2B185.351,583__ _Kongiganak Bethel (CA)S626 408 12.722440...338,471_ Kotlik Wade Hampton (CA)=059 0.19 8.67 13.57 ASS74.543,677| Kotzebue Northwest Arctic ==O48 0183.94 15.16 5033310000 366,138 Koyuk Nome (CA)068 019 4.07 13.85 338 4 35,193_ _Koyukuk Yukon-Koyukuk(CA)046 S400 99 ee.3__.22,417| _Kwethluk Bethel (CA)0530248.78 1244292692...5____29,408 _Kwigillingok Bethel(CA)051078.90 13.230 330.541,942| _barsen Bay KodiakIsland=OAT 0228.59 11.56 80 85.347,244| _tevelock Lake and Peninsula 0.72,0.138 850 0 0 95 oe eeeeeeee 3____21,694| time Village Bethel (CA)1.27 0.67 8.20)56200re1*14,039"|Lower _Kalskag Bethel (CA)6098 299270.429,648 Manley Hot Springs Yukon-Koyukuk (CA)1.05 0.27 2.38 10.83 122 85 4*76,260* -60-March 14,2012 .Fuel Average . Community Residential Effective Prices kWh Average Household Median .Rate Residential .Income Name Census Region Rate 2010$2010$_-s per Population -_Income,*2010$Monthly (2004)per kWh er kWh per gallon Consumption 2004 20105 . P gallon P (2010$S) _ManokotakDillingham (CA)051 019 3-88 1232 334422,4 31,095_ Marshall Wade Hampton (CA)0.64 0.20)3:57 14.27 A838.396 4 38,085__ McGrath Yukon-Koyukuk(CA)0.61 0.17 3-820 13.19 368.327.349,816_ _Mekoryuk Bethel (CA)066 0.19 3.70 13.08 270 We 3 35,674 Mentasta lake Valdez-Cordova(CA)==0.53 |0.19 2.330 12:35 000 274 122,3*22,3357 Minto Yukon-Koyukuk(CA)0.59 0.20.3.47 1267 8A203,3*32,227"| Mountain Village Wade Hampton (CA)61 |0.20 3-93 1463 428 806 4 36,157| Naknek BristolBay 044 017 350 15S BI!545 3 61,776 _Napakiak Bethel (CA)098O25 269 307s345.4 33,264| Napaskiak Bethel (CA)O62!0.18 3-768.44.448 410).5____36,800__ Prince of Wales- _NaukatiBay Hyder(CA)045O18 2055041227 AOA Wo .2____31,818 Nelson _dagoon Aleutians East.066 0.27 4.32 1098304 Bee.3____50,619| New _Stuyahok Dillingham (CA)0-63 0.19 4.130 12.79 B80:510.4___.30,131__ Newtok Bethel (CA)0.81 0.40 4.68 10.25 308 351 5 37,242 -61-March 14,2012 Effective Fuel Average Community Residential Prices kWh Average Househola Median .Rate Residential .Income Name Census Region Rate 2010S 2010$_-sper Population Income,x2010$Monthly (2004)per kWh er kWh per gallon Consumption 2004 2010SPgallonP(2010$$) Nightmute Bethel(CA)OSS BB 279.4 41,581 Nikolai Yukon-Koyukuk(CA)081042 48388.19 8D 86.3 __.17,355__ Nikolski Aleutians West(CA)=0.61 0.22,450 9.72 0 888 23 eee 344,834| Noatak NorthwestArctic===O81 0196.70 13.86 0 SL490 i.4 35,674| Nome Nome (CA)0:38 0.20 3.80 15.91 458 3,610 368,729| NondaltonLake and Peninsula ==0.59)0.28 4.75 10.340 88162 3...22,658 | Noorvik NorthwestArctic===0.700.20 447 1174 S25 619 nn...5...60,123 _Southeast Fairbanks Northway =(CA)O490.18 2.25 13-66 3820 84 3*36,109"| _Nuigsut NorthSlope 017 O113.50 1190 640 410...4 _.95,978| Nulato Yukon-Koyukuk(CA)0.63 0.19 3.93 13.72 0 8B249 eee 4 __.29,057 _Nunam Iqua Wade Hampton (CA)054 0.25 3.85 13-15 8 183 5__..33,553.. Nunapitchuk Bethel(CA)55 18 88 B98!483.433,884 Old Harbor KodiakIsland=0610.19 8.77 18.33 804219 3____37,603 Ouzinkie Kodiak Island 0.40 0.21 3.33 14.06 318 169 3 60,743 -62-March 14,2012 /.Fuel 7 }Average .7 -Community Residential Effective Prices kWh Average Household Median : .Rate Residential .Income | Name Census Region Rate 2010S 2010$_-per Population Income,2010$Monthly (2004)*|per kWh erkwh Per gallon umption 2004 20108 |P gallon P (2010$$) Pedro Bay ___Lake and Peninsula 0.93!0.49 4:65 12.20)289 620.342,520__ Pelican Hoonah-Angoon(CA)0.44 0.16 33212-2902 11200 2 56,404 Perryville Lake and Peninsula 0.58 0.43 30003800 130,00 3____60,020 _ Pilot Point Lakeand Peninsula0.51!0.14 4.77 128200348 4.347,727 _Pilot Station Wade Hampton (CA)0.63 0.19 3.80 12.66 423 344 5____35,950 _ _Pitkas Point Wade Hampton (CA)0.62.0.18 350 2.920.4 48,450 _PointHope NorthSlope 018 0.17)3.70 14.99)7988!660 4 ___73,037| _Pointlay North Slope.O16!0.15 3-55.13.24 000 683 196 4 79,545 Port _Alsworth Lake and Peninsula 0.66.0 0.197 4-16 10.8000 388.129,3 67,975| _PortHeidenLakeandPeninsula0.69 0.36 484288 Ie 3____36,880__ _QuinhagakBethel (CA)6S 0.20.3-90 13.78 363 |680...4 29,106| Red Devil Bethel (CA)ee1.01!0.26 05:25)812285 330.3 12,655_ Ruby Yukon-Koyukuk(CA)0.92 058 401 460 8 20.3____28,202 Russian Mission Wade Hampton (CA)0.63 0.20 3.90 13.87 480 314 4 31,818 -63-March 14,2012 Fuel Average Community Residential Effective Prices kWh Average Household Median .Rate Residential .Income Name Census Region Rate 2010S 2010S per Population Income,x2010SMonthly.(2004)per kWh er kWh per gallon Consumption 2004 20108PgallonP(2010$$) Saint Marys Wade Hampton (CA)=0.62 0.18 3.50 1402,8548...445,557|Saint Michael Nome (CA)062 0.20 400 1468 5320!407 4 38,223| Saint Paul AleutiansWest(CA)0.480.23 3.63 1412000587 439 i.358,718| Sand PointAleutiansEast==OAD 2829 13.99 AT4,050 0 364,118 _Savoonga Nome(CA)059 0203.93 14.2000 9660 4 27,118|Scammon Bay Wade Hampton (CA)063 0.19 3.90 13848 BF474.5__._29,648 _Selawik Northwest Arctic ===066 019 47 1354 AS825 4 29,648| _Shageluk Yukon-Koyukuk(CA)75 0.20 4.00 12.3200 Mo.4 ___30,854| _Shaktoolik ==Nome(CA)GT0.19 3.93 13.81 517 245 ne eeeee 4 ____36,880| _Shishmaref Nome (CA)0600.18 4.07 1448 412 559.435,537. _ShungnakNorthwest Arctic ==0.710.200 4.47 13.52 5882600 5.31343 Skagway Skagway 220-151931439 TF8813*72,795"| lanaValdez-Cordova(CA)=0.53 0.19 2.36 12.86 8144:3*_46,106*| Sleetmute Bethel (CA)1.01 0.26 5.25 10.54 245 77 3 17,355 -64-March 14,2012 .Fuel Average . -Community Residential Effective Prices kWh Average Household Median - .Rate Residential .Income . Name Census Region Rate 2010$2010S _-per Population -_Income,2010$Monthly (2004)*-per kWh erkwh P&gallon Consumption 2004 20108 -:P gallon P (2010$$) Stebbins Nome (CA)062 0.19 3.90.13.290 847 574.4 26,756. Stevens Village Yukon-Koyukuk(CA)1.10 90.63)5.20.10.99 02 86 3*42,713* _Stony River Bethel(CA)1.01.9.26 5.30)964 0 4 47!2*_11,486* _Takotna Yukon-Koyukuk(CA)4.15 000.41 5008 9.5400204 55.316,873_ _Janana Yukon-Koyukuk(CA)0.74 0.26 3.38 13.4200 227.242.334,421 _Tatitlek Valdez-Cordova(CA)0.67.0 0.42)3.109.93B02 920.3 42,665_ Teller Nome (CA)072 0.20 4438 1035 0 8A2530.4 26,611 Tenakee Springs Hoonah-Angoon(CA)0.64.0.30.3.581280066 129.238,326_Southeast Fairbanks Tetlin (CA)933!0.17 2d B84.126!4*42,544* Prince of Wales- ThorneBay Hyder(CA)0 O24!0.16 2-85.13.40 00 402 442.3 ___52,789__ _Togiak Dillingham (CA)061 018 3.90 13.16 808 4 27,742|Southeast Fairbanks Tok (CA)ee 0330-17 2-220 14 OI1218):3*_55,122* _Toksook Bay Bethel (CA)0 O55!0.18 4.03 14.45 AMO 601.5 34,951_ Tuluksak Bethel (CA)0.61 0.24 4.38 13.20 244 365 5 36,519 -65-March 14,2012 :Fuel Average : Community Residential Fffective pices kwh Average Household Median .Rate Residential teas Income Name Census Region Rate 2010S 20105 per Population Income,-2010$Monthly (2004)per kWh erkwh Pe gallon Consumption -2004 2010$P gallon P (2010$$) _TuntutuliakBethel (CA)06526860 1350 0 8ST380.4 29,504| _Tununak Bethel (CA)55018 408 8B318...4 28,925 Twin Hills Dillingham (CA)056 016 578744 8B 78 cece 333,987. Unalakleet_=Nome(CA)4B0.19 3-61 13-48 AAA685 348,691| _Unalaska___Aleutians West (CA)0.330.24 2.04 13.704838A092 380,458 Wainwright North Slope 0 OAZ 0-15 440 12-43 OMA9360.4 ___63,314| Wales Nome (CA)0:670.194.07 12.56 8D153 338,567. Prince of Wales- Whale Pass Hyder(CA)0 OAT 0.21 2.14 1234 208 ee2°43,714" White Mountain Nome(CA)oo 092 050 8.01957 288 209 oooeeeeeeee 3...29,889 Yakutat Yakutat 0.46 0.24 3.10 13.38 446 742 3 54,132 -66-March 14,2012 Appendix G.Monthly Customer Payments under Current PCE Formula and Seasonal Fixed Payment Formula s.§5 S Ze ss <2 -] Ee #e #8 £.5 #2 ¢&g E E 3S €35 #G 55 2 =3 asx 2 Pe SE 2'£Ee 3S3ceSeooOUPDSc>see L 9 9 a Ess @as SES-Lv)s y E => a 2 Eat Qu 6ey.az Ss 68 £5 c¢SasEgeSs *232 s32 SEEESc«£¢=a ea 5X2 222 E68222$86 §&83 EER GER EBS om seb 28 28 EE asd 23 283ResidentialPCEFuelo5£o 3 °3 £5 2763 8653 @&5 2 Net:.Pe he --Community rate,level,price,ges gs os ww ws E ws E @ 2 >annual name Census region $/kWh kWh =$/gallon *9 <a <a aa ane ane £52 change Adak AleutiansWest 0072,049 3.59.244 27d 258 so 01 118109.85%_ Akiachak Bethel 0-63.040 3.72!269 344.306 i...7V 105 124 115 61% Akiak Bethel 0-630320!4.55.219 256 238 i.73129 1520140.87%_ _Akutan AleutiansEast.0.32.)O19 3.22:365 424.394.33s91.107.99 86% _Alakanuk Wade Hampton 0.62.0.433.90:374 A459 447.80.Ald 130:120 50%_ _Allakaket______Yukon-Koyukuk 90.70.0.512 4.38!204.270 237 45 424 146 135___.201%_ _Ambler ________NorthwestArctic000.75.)0.54 4.47:360.437.398 84127 149 138 63% _Anaktuvuk Pass North Slope 220-15...0.01 5.20...948680.604 ww.88 a7 173 160 83%_ _Angoon ____._..Hoonah-Angoon 0.47.0.27)2.78:391433.442.81.79.93 ew.86!6%| Aniak Bethel 074047 3.62 394.310 4520s121102 1211120 8%_ _Anvik -____Yukon-Koyukuk00.67 0.49 7 417:317.337.327 we.610118 139128 110% Atka Aleutians West 4.19 394 395 395 93 39% -67-March 14,2012 c c -Pas (>)o »wo .=5 ss sso <>5 r=)E Be #5 -S5¢ee €5Fo]5 35 #9 36 v2 2 sf 2 os €Eon32>c™=>.&o&e'£>OWFs}cs 5s GS €Fe-GFRFe BX.aa Sze o2 3S =)sS ci avo»&-&elo foe EGE -OHS£2 o \ Ss su"a3 9 FDS S SEESc«€G =o Ee 5X2 882 E65=2 '=c o=to eo ca O ;Ze 3 E oc E £2 €E Bun gh&w 6 6 an eee o 2 o 2 SE €nae ERG OBEResidentialPCEFuelPesEo3o3SS3§353 B63 o 5 ge NetCommunityrate, . level,price,Y cs Ys Ys Bw Wy S E w %E ez annual _name __Census region $/kWh ss kWh_s S$/gallon FT O¥FF ao oo ane ane £54 change 0.70 0.46 119 140 129 _AtmautluakBethel077 AT3.59.319 362 340:124.102 120.111 710% _Atgasuk __...NorthSlope0.19 0.02 3.00 723 844 783s140885.100.93...734%. Beaver ____.....Yukon-Koyukuk0.55 0.42 3.80 179210 195.26 108 127.117 __349% Bethel Bethel =050089.05:444 566 $05 ww...80.148 168:156 95% _Bettles ...Yukon-Koyukuk 0-610.42 2.65 319 446 382.72eee.M3.88.82 ______13%_ _.Brevig Mission =Nome 0590.41 4.00 367,468 418.78113 133 ww.123 __.57%_ _Buckland __/____NorthwestArctic 0.52,0.29 9.00:464 582 $23.127,142 167:154 22% _Central.Yukon-Koyukuk 0.600.29 2.27 600179 167.ol!64...76.70-36% _Chalkyitsik |Yukon-Koyukuk=0.95 0.37 4.18 112)134 123 72118.139:129,81%_ _Chefornak Bethel =0-638 0.37 4.13:398 450 424:SS ee 138 127,_____15%_ _ChenegaBay ____Valdez-Cordova 0-46 0.30|330:323362 343.56!94...110.102 ___81%_ _Chevak -...WadeHampton065 0.46 4.03:3620 A497 430 ow...824 134.124 51%. Chignik Lake and 2.75 333 238 286 51 66% -68-March 14,2012 5.§5 s 4 o <@ es es 5 3 o 2 a a cEes-€5 §E,.54 22 §&3 SE Z£38 #28 3 9 EuFr]coc <x oo >c>x Lo.9°=9 2 3S Eas Yas $F Goo==x cli -2e2 E@QE ZAG€2 ©\-Si Su avso 7790 8 6 FSE§Sc«x 2a =@¢Ee 5SX2 282 E6535==Ee ce os E iz a -ic a cua 2S2969=96 EE =.$=".®Ge edanti BEE %2 %&ee EGS £€ES OnG5ResidentialPCEFuelese93y38S236338653852 Net.-_Ww ra te -_Community rate,level,price,ges os os we ow Ss E ws E ¢3 >annual _name Census region $/kWh =-«kWh__$/gallon <<9 ¥ion <a ao ane ane <5 change Peninsula 0.51 0.33 78 92 85 eee Lake and _Chignik Lagoon Peninsula)0-440.29 3.93!456 AO1 428 i...65 0,13100121 87% _Chistochina ______Valdez-Cordova 0.51.0.33 2.310:258 327.292 ww.54..!65.77.71.32%. _Chitina -____Maldez-Cordova 0.54.0.29 2.73 ws261292 277 i.69ww.Ww.9.84 22% _ChuathbalukBethel0:99.0-74 3:15.175259 217.5500 146 72:159 187%| Circle...Yukon-Koyukuk 0 0.67.0.48 2.43:260 340 300 i.57S69.81.73...31%_ Prince of Wales- Coffman Cove Hyder O42024251:299 3B.306.93:A.84.77...45%, _ColdBay ________AleutiansEast.0.62)0.44 3.65:384 427.405 ow.70.103 122 11360%_ Cordova _________Valdez-Cordova,0.33.0.10 2.23 498.536.317:124!6374 69:"44% Prince of Wales- Craig Ayden 020.2008:2.30!463545.$04.79!65 IT.71_____-10%_ Crooked Creek Bethel 00099.0.74 3.29.261304 282 0.72149 175:162 125% Deering _______.NorthwestArctic0000-77.)0.43:471:326 AAT.381:130.133.00.157:145 12%_ _Dillingham -______Dillingham 2 O440.28 3.60:448 |...503...475 76.102,120 111 47%_ Diomede Nome 5.85 233 283 258 35 417% -69-March 14,2012 >6 S.¢G 1 s S xo]=E ee f£&§£Se fe €&2 SE 5S 5 25 #a 3G eH 2waoocEu¥as =-&OE 2 €>oSFe}=<coc oo >c >ao xX558s83teE&s ¢-EE Siig-2 aX BX 35 805 Fu5 SEZESc£9 =o te 5%as 25Es2-_£c £oO &vow A Cs can Ooawe3oe-2@ €eu gHeuU oatovE2a2i)2 >E EBs ERR YOREResidentialPCEFuelwmEEpo2wo3®5 sSs s§s ™io@ Net .fe Fd =".Vv "VU Qa ”bd &s bd €"&@ &Community rate,level,price,gs vs vs ye YS 5 os 5 22 >annual -name _Census region -$/kWh kWh $/gallon <9 ¥<2 <0 oo one ane £54 change 0.60 0.47 166 195 180 Southeast NE FagleFairbanks 0620A2.88 1952.223.209 38 82.96.89132% Fek Bethel 0.68.0.48 3.83:258...280 269 we...53109 128:118121% Lake and _Fgegik.Peninsula.092 056 4.30:229 302.265 95122.143:133 ____39% _Ekwok Dillingham 500.37 3.70:360 315 338.46 105 123:114150% Elfin Cove.Hoonah-Angoon 0.56.0.38 442s233 B81.182.31128 ae136|,333%_ FlimNome 06004 4.07 354 481.393 74 MS.136:125 70%| .Emmonak |Wade Hampton 0-63.0.43 3.90:398 |486 442,87 AN.130:120 ____39%_ -Fort Yukon _Yukon-Koyukuk=0.600.39 3.78 249 _....300 275.99.107.126:116 97% _Galena...Yukon-Koyukuk 90.56 0.34 4.30:312 430.365 wi.82122 143.133 62% _Gambell Nome 0-61042|3.93:316425 370 ww.69 AM.131:121 75%. Golovin Nome 0.70051!3.10 284 304.319.618.170:157____159% ..Goodnews Bay Bethel 0:63.0.43 3.83:311392 352.69109.128:118 72%. Grayling Yukon-Koyukuk 4.17 285 302 294 60 113% -70-March 14,2012 5.§: --£ar]x ond 4 @ _£2 Be 82 s 28,$$.+€3S €0 -o Se ZE ct o+Ss Ee 3 £ow +w 3 ow ="ae 4m c =rs £Eva3arccso2?5.c 5 zeu .&Ss 8s os Es S Yes GEG :o @ vz -z cf Fee EGE TES;€2 o ss:3yv avo FU O Ss =Ess ae =o Ea ®S a%sSs -26§E552BEcEesEGSing$22"aS (=)8 ¢E = .2 SF Ga®¢E o oe >E ECs c£eECwm YRAEResidentialPCEFuelese$0 3 oo 3 8s 363 282653 &%2 Net.a7,)pa he FeatCommunityrate,level,_price,Y S S 25 Gs we Ww 8 E Ww 3 E 2<t2 annual ,hame Census region -$/kWh kWh =$/gallon <=9 <a <8 ao eure ane £354 change , 0.70 0.49 118 139 128 Gustavus Hoonah-Angoon 0-57.030|271.166 182 159 44:77.90 84 92% Haines Haines 0220005 3.13.0!404.496 450 ww.68 89.104.96 42% Southeast _Healylake Fairbanks064 0412.53...220 318 269 64:720.84 78 22%. Holy Cross _Yukon-Koyukuk 0-67.0.48 4.10 297 346.322...61.116 137,126106% _Hoonah _________Hoonah-Angoon 9.47.0.27 2.40ow!404.AAG.424.84 68.80.74:712% _Hooper Bay ______WadeHampton 0-61...0.43.4.00...301378.338.63113.133:123,94%, Hughes.Yukon-Koyukuk 0.710.38445.262320.291.982.126.148 137 41% _Huslia Yukon-Koyukuk 0-63.0.434.130:373...433...403.79 Tn .138!127,61% Lake and _lgiugig Peninsula 0073087!6.33w.:301.328.314.349,211195____280%_ _Kake Petersburg0 0470.27 271:359.390.374 74i.Wi.90 84 13%_ _Kaktovik =_NorthSlope0 0-17.0.02 3.70...!625.698 662 108.105 123 114.6%| _Kalskag Bethel 059.040:3.97:356 435 695 ow:208 12 132.0.122:"41%| Kaltag Yukon-Koyukuk 4.03 312 364 338 64 95% -71-March 14,2012 c <PoFin3AS}+7 s @ g ===5 2 o =E £5 ES E S¢2¢5 &£SE 3 £35 #49 3 0 2 = "an c Eu3umc™.£ro)£©'E UY[s)cs ot oo £>c >Oo KM 4 are 8s 3s Us S85 ¢8S cisvo9.&=%eX poe E@®E -AS-2 oO.gs.5uv 23 GO FUSS EB =ES =G =o Ee sX2 282 E65ISEfevsqasizangsze"e656 26 ®6 £E=£=°oe enti gee g2 2 EF EBS ERE g32ResidentialPCEFueleseo3go3®o9 2635 £63 rey +2 NetCommunityrate,level,_price,g cs Ys vs ye S E w 8 E a =annual_name Census region $/kWh kWh =$/gallon *9 *<a <2 aq ane ane 3%change 0.63 0.44 114 134 124 _Karluk oo...KodiakIstand 0 060)0473.58 416 523.470 oo...63.102,119:110.74% _Kasigluk Bethel 054036 3.97 459 AAS 847 279 2 132:122 756% Kiana Northwest Arctic 0-68 0.49 4.40 365.481 423 ww...re 147!136 68% _KingCove AleutiansEast.0.25 0.10 236:380470.425 64!67.79 73 14% _Kipnuk Bethel 064 038 3.65.391 44d 416:105.103.122 113.2%| _Kivalina ___.....NorthwestArctic 0.700.50 4.40!470 324.497 ww.99425.147.136 38%_Lake and _Kokhanok =Peninsula 0.900.64 4.57:309.365.337.89129.152.141 59% _Koliganek Dillingham 0-50.0.375.06 266 280 273 we.37 M43.169 156323% _Kongiganak Bethel 055.03004.03!419 489.452:41514.134 124.!8%| _Kotlik ooo...WadeHampton 0590.40|3.67|384 526 455 oo.85 104 122:113 33%_ _Kotzebue NorthwestArctic 0.470.380 3.94 579 720,650.158142 ee122 723%_ _Koyuk Nome 0:62044 4.07 428 44.47d.88 NS 136:125...42%. Koyukuk Yukon-Koyukuk 4.00 160 203 181 27 358% -72-March 14,2012 s.§:Ping bad wv <=a es ees ©3 a 2 E -Ss ES 5S.SE g¢5 3333&S86 e8 32 Eve3ef££.3585 SE.£€E_Faee)9 Exec G@Ae FX35eS2322FazEZSES2.5 =ws a9 8 5 >§B8B2£2 go.*#agS e388 SBEEssacocoee+22 af2 E6&aze 36 s&22 FES gts EESog2ovrooSetueowResidentialPCEFuelPEE83$23 #5 558 $58 $2 o NetCommunityrate,level,price,y -Ys Ys yuow %E W 8 E ou =annual _name Census region $/kWh |kWh $/gallon <=9 <2 fa a@ aun aun £54 change 0.45 0.30 113 133 123 _Awethluk Bethel 0 052029 3.73 ooo.268-316,292 ow...68 106 124:115.69%_ _KwigillingokBethel00 0-500340.3.90!443 AMD.446.740M 130:120.63%_ _larsenBay ___KodiakIsland 0-40.0.19 3.59:311292 302.64 102 120:141 74%. Lake and _tevelock Peninsula 0-70O57!8.50 164208 190.25 24d.283:262 __.959% _time Village Bethel 228059!8.20...78 oe!86.820.94232 273 ws253____.372%_Manley Hot Springs 2...Yukon-Koyukuk 00204O77.2.38oo.420 122 oe.33!689.73__._.125%_ _Manokotak Dillingham 0-50...0:322:3.88:313 359,334 oo...62.110 129 ww:120 94% _Marshall ___.._.WadeHampton 0-63.0.44 3.57:385 480.433.83.101 119:110_32%. _McGrath _Yukon-Koyukuk00 0.60.0.44.3.82...334392.363 ow...61.108 127:118 94% _Mekoryuk |Bethel 005.046:3.70...245 2.294.270 oo...310105 123:114 _.124%| _.Mentastalake _Valdez-Cordova,0.52.0.33 2.33...252 297.274 ow...rn66.78.72...40%_ _Minto ooo...Yukon-Koyukuk 00.58...0.390:347:271______.383...327 i.64!98...1160.107 68% Mountain Wade Hampton 3.93 370 487 428 82 47% -73-March 14,2012 .§8 2 &<=o et 6 5 3 o =£ae c -S CBw c Ooro)-&o E 6 5 ra cs cece oO s33£Z£os )6h UE UU 38 Eu3fe§2 355 2&£E,FE%55 83 83 ge EF8 BSE SESg85%BX S55 805 #05 BBEESc£G EG €¢@ 5X2 2282 E6535323Ece$5 £25 5ptun gze"26 9 6 E¢- .£2 8 Ew ..J)EE o +o +>&£8 c 8 &VA CcResidentialPCEFuelboPspSSo353ss§s Be.Net ..cat ae)£G ae 292 392 aECommunityrate,level,price,v SS Ys vs yy ys :gs 5 22 >=annual_name Census region $/kWh kWh $/gallon <9 <a <a 092 ane ane <5 2 change Village 0.60 0.41 111 131 121 NaknekBristolBay=044 0273.50|393.401 397 65!99.17:108.66% Napakiak Bethel =096 0724.37.268 347 307 i.75 124 146:135._____80%. _Napaskiak Bethel =0600423.76 421 AA 443 81 106 125 116 (43%. Prince of Wales- _NaukatiBayHyder44 026 255 365 443 404 i...72.72.85.79!9%| _.Nelson Lagoon __AleutiansEast==0.65 0.39 4.320:288 320 304.80122.144 133...66% _.New Stuyahok Dillingham =0620.484.130:406 453 430.81.138:127.57%_ _Newtok Bethel 0 0-800.42468 283 333.308 422232 136 144 18% _Nikolai Yukon-Koyukuk=0.800.394.830.335 382 359:447 N37 161149 2%| _Nikolski AleutiansWest 0.600.39 4.50!329 346.338...72 128.150:139...93%. _Noatak ..Northwest Arctic =0.79 0.616.70.503619 361.143 2190.223 i:207 45%. Nome Nome 037.018 3.80 4150501 458 89.108.127:117 32% Lake and _Nondalton Peninsula)058 0.31475.359 4300 394:109 2352.158:14634%. Noorvik Northwest Arctic 4.47 444 606 525 114 21% -74-March 14,2012 415.§, 2 .&sastesc3o3 a wo P=)iEeS£€s §£,3#Ee §8Fas&3£2 $2 2 EBS3Sss=oo 6Uf CS 5 >se .©$=83 us E®S 886 SEsoo &-xX cl - 2%&EGQE AS-2 ®\-3 3M atOo 73 9 S$@eEE§cx =G ca eae 5 Se akfse £622236EE$3 225 sea EBS ;weg ov 2 v2 SE €Gae ERG OBEResidentialPCEFueleseeSbo®6 S§&s s§s #2 Net : .ence .O oO Qe 7)bd FS 3 9 =SaEeCommunityrate,level,_price,gs Ys vs ob S85 best SER annual _name Census region |$/kWh-kWh $/gallon "9°*¥f2 fa aoa aur ane <5 change 0.69 0.50 127 149 138 rn Southeast _Northway Fairbanks048 0372.29 ow:261380 320...S77!64...73.69.22% _Nuigsut North Slope 0-170005:3.50!533.748.640 ow...8099.7:108 |..35%_ _Nulato _...__Yukon-Koyukuk9 0-62)0.433.93.326.371 348.66 1M 13100:121 84%_ _Nunamiqua|.Wade Hampton 0-53.0.29 3.85.301.388 344.84.109 128:119 41% Old Harbor Kodiak Island 0 0-60.0.41.3.97:271337.304.$8107,126 116_____100%| _Ouzinkie Kodiak Island 00 0-40.0.19 3.33...303.333...318.67 4.Se103 54%_Lake and Pedro Bay...Peninsula)0-910.48 4.65:270.308...289 1402320 155 ww.143:2%| Pelican _____..,Hoomah-Angoon 0-43.0.27 3.32:385443.402.64 4 11:102.59% Lake and Perryville 0.Peninsula 8087.OTS.3.00:302 298.300...126 BL.100.93.27%. Lake and _Pilot Point Peninsula 050.0:37|tkrn321.394 345 oo...46135.159:147 __220%_ _Pilot Station Wade Hampton 0.62.0.43 3:80:346,500.423 oo.81.108 127:117,45% _PointHope _____NorthSlope 0.18)0.02 3.70...749 |,842.796 oo:1352205.123:114716%_ Point Lay North Slope 3.55 616 749 683 101 8% -75-March 14,2012 £c _ =°oO amd o <x2£2 82 ¢g »€eo Eo c 3 ce 5 223SSva.3 a v = a 3 £ZE r=)c o Eupjc-c=.£vu £c E ownFs}Sx Sx 6S €Fee GFFe BX.55 os os Ze She Eke Sis£2 Gs s*SG Bu 5 Fu 5 BBeEsc£S 25 #£e S$&PE Z25E52%SE e€35 PER,-zen £2 vee7es28asEFEGG25528eResidentialPCEFueloEEo3o3®&S 263 3853 &s 2 NetCommunityrate,level,_price,gv _vs es oo 8 %E Oo 8 E 22 ze annualnameCensusregion$/kWh kWh =$/gallon *9 ¥<a <a ao ane ane £54 change 0.16 0.02 101 118 109 Lakeand ee neneeen nnn nnn nS _PortAlsworthPeninsula065 AT4.16 0.321.348 335 62018 139:128106% Lake and _PortHeiden Peninsula.068 0.324.34.283284 283 102.223.145 ww:134.31%. _Quinhagak Bethel =4 0A3.90.326.399 363 720M.130:120.67% Red Devil Bethel =99 0743.25 219)250 235 60.149 175:162171%_ _Ruby.Yukon-Koyukuk 0.910.34 4.01.118 145 1310.75 Aa.134.124 ____65% _.Russian Mission WadeHampton==0.620.42 3.90 422)538 480 94.130:120 _____28% _Saint Marys |__WadeHampton=0.610.438 3.50.309 388 646 178!99.V7:108:739%| Saint Michael =Nome 61 0414.00 435 (630 9320.1600 3 133 123!6%| _Saint Paul AleutiansWest 0.470.24 3.63:520.354 937:130 _...103_121:112 714% _Sand Point AleutiansEast=0480.28 3.29 426 488 457 93ws93.2.110:101!9%| _Savoonga Nome i 058.039 3.93!441 526 469 i.94.131:121..33%_ _Scammon Bay ___WadeHampton=0.62)0.43 3.90.398 480 439 820.130:120 47%_ Selawik Northwest Arctic 4.47 392 557 475 89 S4% -76-March 14,2012 s.§: i °2 o <@ 2S ss c 3s o re] E #5 £5 §&€.Se Ee ¢€83£Sec on 55 2 _s3F=2 =oe €£2 =EatFe}cc Sc oo ¢>5 >ax o ov Lz -X%©7-ae EaQe TES£2 os sc.3H avs F395 8 6 FS£ESc =<=<oO fe@e +8 ats 2ZS§E222FE§£E 83 EER SER ERSo22ofofEEEGaeGEEGOSEResidentialPCEFuelo3o3o®S5 353 353 8S z Net.pw r 4 -a --Community rate,level,price,v ss 3 5 3 5 yy ys E w 8 E 22 2 annual,name __Census region $/kWh =kWh_s S/gallon TO |oa aa e020 aur ane £54 change | 0.65 0.46 127 149 138 _Shageluk -_____Yukon-Koyukuk 0-740.54 4.00:230 273 252.50.113.133.123 145%_ _Shaktoolik ===Nome 060.0.42 3.93.0:481593.247:104 td 131)121.17%, _Shishmaref_=Nome 059042s4.07:364 461 4420.720000A 136125 75% _Shungnak _____NorthwestArctic 0-79.0.54 AAT!475 2294.955...483.002 127 149 13871%_ Skagway Skagway 0-220.05 1.93.437 497 467 i...70530.64 59:-16%_ _Slana______._,Maldez-Cordova,052...0.34 2.36:241322,281.$2!67.79 73.39%. _Sleetmute Bethel 099074:3.25 ws227 264 245 wwe 63149 175!162159% _Stebbins Nome 0-69 0-42 3.90:304 390.347 ww.64 130.120)87% __Stevens Village Yukon-Koyukuk 207,0.46 5.20 .....9......,102 102...62.147.173:160157% _Stony River Bethel 0990745:30...133.158.145 ow...37._.....150.0.V7:163341% _Takotna______Yukon-Koyukuk 1.140074 5.08.198.210.204 i...82144,169 156 92%_ _Tanana__________Yukon-Koyukuk 0-73...0.48 3.38 200.254 227 i.$7ws96.113!104 82%. Tatitlek Valdez-Cordova 3.10 271 332 302 123 -22% -77-March 14,2012 c <_Poy Bod32626 &8 5 w =ES Eo =st ct 5 22Se3S£25 #24 3G 27)a=a=Se CE 2"f£Eu3ccSssolU2DScSaeéae8sgsosEst@886Sigoo-c a €¢Ea e¢TASte1xs_-o >©=]-e°2 3.Zé et 2 «we SEEESs£8 €8 Es S¥2 2¥2 E95axe3£3 §Fe ERM GEM BBS ;.o =9 os o =SE €&t cs €BG WSFResidentialPCEFuelmEE S s [5s 3S§3s B§s Ps.2 Net ;.Hg 3 =2 Ss re)Qe "a bd =E 9 =o£Community rate,level,price,9s es vs wy YS 5 4s :Y 2 >annual name Censusregion |$/kWh kWh =$/gallon <<9 ¥<0 <a aq ane ane £54 change - 0.66 0.25 88 103 96 Teller Nome 0.700504.43.292,358 325 65.126 148s137|.111%_ _Tenakee Springs Hoonah-Angoon0.63 0.34 3.58 170.163 1660.49 ....101 19:110127% _Jogiak Dillingham060 0.42 3.90 374.AM 410 4AM.130:120_____61% Southeast TOK Fairbanks 0.82016 2.22!413328 469 i.77!63...74.68 711% _Toksook Bay Bethel =0.54 0.36 4.03:421 Ar 1,281 513,414.134.124 776% _juluksak |Bethel 060 0387 4.38:224.267 244 37124 146:135___.135%_ _Juntutuliak Bethel =064 0.89 3.60 344.370 357 91202.120:11.22%. _Jwin Hills Dillingham SSBD$.73 292,3638 328 $2 162 191.177,_____241%_ _Unalakleet_Nome 0470.29 3.61 441 AIT 444 i...81202 120:111 _37%_ _Unalaska___AleutiansWest_0.33.0.09 2.04 448 1.483:116.38.68.63 746% _Wainwright____NorthSlope 0170002440 610,677 644 100425 147:136 35% Wales Nome066 0.47 4.07 328 398.362.68 136:125 ______86%. Whale Pass Prince of Wales-2.14 214 201 208 43 55% -78- , March 14,2012 Net annual change . yUOW//$'ejnwis0yquawAeg paxiy jeuoseas Japun quawaAed jenuue asesaay yow/s'ejnusoyquawAeg paxiy jeuoseas . Japun juawAed saquIM 33d| YyWOIN/S 'ejnus0} quawAed paxiy jeuoseas - Japun juawAed sawwns 39d yUoW!/s 'eINW0} 33d quaiind sapun yuawAed 49d : yuoWw /YM "eWoysNd Aad| . Yonduinsuod jenuue adesaay yjuow/YyMy 'awojsnd Jad UuoI}dUINsUOD Ja]UIM asesaay - yuow/UM> | 'aalojsnd Jad uolduinsuod | Jans aselaayFuel price, $/gallon PCE level, kWh Residential rate, $/kWh_Census region -Community _name 71 66610.260.47Hyder White 268 324.296)1448510098-36%3.010.410.90NomeMountain 3.10 447 446 446 105 88 103 96 -9%0.210.45YakutatYakutat March 14,2012-79- Appendix H.Data sources and methods Power Cost Equalization program data information for this analysis was obtained primarily from existing reports and datasets.AEA has been collecting and publishing PCE program data since 1988.In 1988,the first Annual PCE Statistical report was published containing data from 1981 to 1988 (including PCA and PCCA).The Annual PCE Statistical reports are still available.For the years 1981 to 2000,PCE data is only available at the annual level. Annual reports contain data at the utility and annual level regarding kWh generated and sold,fuel prices,residential and PCE levels and effective rates and other useful information.Data from these printed reports was manually entered into an Excel dataset by ISER researchers.Currently,AEA uses a software tool called NAVISION to store program data.Information collected from Utility PCE Monthly reports is stored in the database in addition to disbursements and financial data;this information is used to publish the Annual PCE Statistical reports.Since 2001,PCE data is available on a monthly basis from the NAVISION database. Other sources Information regarding community characteristics such as income and average household size are from the U.S.Census American Community Survey estimates;other characteristics such as population and unemployment rate are from the U.S.Census Bureau and Alaska Department of Labor and Workforce Development.ISER recently completed Alaska Electric Energy Statistics reports which were also used as reference.In addition,in 2008,the McDowell Group prepared the Alaska Geographic Differential Study for the Alaska Department of Administration providing an analysis of cost of living differences in various regions of the state. Finally,a literature review was performed including previous reports and analyses regarding changes to policy and program guidelines,readings regarding subsidies and economic theory and a number of statistical,econometric and technical resources were used.” Data quality We assumed that PCE program data from PCE Annual Statistical reports were reviewed to at least a minimum level of statistical validity.However,because utilities may not participate in the program all year or because of failure to submit all monthly reports,data presented as annual data for that utility may actually be data for less than a full year.In addition,within that partial year of data,some variable may have even fewer months of reported data.These issues of inconsistent reporting and lack of documentation of missing data severely hinder the ability to conduct time series analysis.For analyses in which a complete data set was critical,we did an earnest effort to control for the number of months for each observation or using only cases with complete sets of data for calculations.Data from these complete sets were used when analyzing the program over time. 33 .aa :.A complete list of sources is listed in the "References”section. -80- ;March 14,2012 Variables such as residential and PCE electric rates,disbursements,number of customers and kilowatt- hours sold are of higher quality than other variables in the database.This information is reviewed by AEA staff against documentation submitted by the utility.Variables such as fuel and non-fuels costs, generation and others are not reviewed to the same level of scrutiny because they are not relevant to providing the disbursement to the utility and because that information is more carefully reviewed by the RCA.Because these agencies operate independently and no formal mechanisms exist to reconcile data submitted by the utilities to both agencies,data discrepancies are unfortunately common.PCE program data from AEA is more readily available and accessible than data from RCA.However,PDF copies of the Annual Re-calculation of PCE Level were provided by RCA staff.Data regarding fuel and non-fuel cost were used from this reports when possible. The U.S.Census American Community Survey (ACS)strives to produce high quality data,however because of the challenges of collecting data for Alaska given a relatively small population and sample sizes,it is not uncommon for ACS data to have large margin of errors.The ACS five year average data were used in an effort to use the most accurate estimates. Information from the Alaska Geographic Differential Study was of limited use because sample sizes were small and often did not match the communities considered in this report. Methods Data from all sources was digitally input into Microsoft Excel workbooks and/or STATA (statistical software)datasets.In addition,to the quality measures taken by all sources,all data sets were reviewed for consistency and accuracy.When data from different sources was merged,the match was done at the community level using the community identification number. Data calculations were done using both Excel and STATA.However,all analytical models were done using Excel because of its flexibility and potential ease of distribution to all interested readers and reviewers.A sensitivity analysis was done for all PCE formula models reviewed in this report for which worksheet models were created. Time series data from PCE Annual Reports is only available per fiscal year;hence it was presented in this way in the report.However,other data sources present data based ona calendar year so PCE Navision monthly data was aggregated to a calendar year level to allow proper analysis. Analysis regarding the program in its current form or for reviewing potential funding formula alternative was based on current monthly PCE data from the NAVISION system.For descriptions of the program history and changes over time,annual data were used. -81-March 14,2012 Appendix I.Map of Alaska Energy Regions Power Cost Equalization (PCE)Program Eligible Communities ia :acaaNorthSlope a!ae \Nee co \ine iies a?\ a.a \ ;Ee ANorthwest /Arctic . . ..Pam Sot maryd . . Paw 2 bot;,boo .Yukon-Koyukuk/Upper Tanana ;S Bering Straits "/.wpeee?" Ne,we.. -\v®|.->Fad {>5 Fad Qe,.\ ;eelsvaje.root / Railbelt |."\rf .by a i e eee --""Copper River?\se Lower Yukch-Kuskokwim ol fog”,Chugach |.BY oe et a Ro fete By ooIAEte"+Bristol Ba aedial .of i Gy xSiaTeFEANEWarne4"aay *'Nv 7 ex Sh eran ! ;?ae BEN ay \ .é rea Pe rah |"we aKodiak weesrgAlaskaEnergyRegions eo 4 'i -]Aleutians i ;North Slope ™ws,[_]Bering Straits [___]Northwest Arctic tye ¢ob «.r )pestol Bay --paiibetaiaP"Jeutians ["]Copper RiverChugach [|Southeast ,{4 Kodiak [4 Yukon-Koyukuk/Upper Tanana 7a ALASK Awe ___..|Lower Yukon-Kuskokwim *PCE Eligible Communities -82-March 14,2012