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THEUNIVERSITYOFNORTHCAROLINAATCHAPELHILL
Howtolookforwardwithoutlookingback:
Innovativeapproachestoforecastinggreenfinanceprogramdemand
AUTHORS
ChristineE.BoyleEnvironmentalFinanceCenter,SchoolofGovernment
Knapp‐SandersBuilding,CB#3330UniversityofNorthCarolinaatChapelHill
ChapelHill,NC27599(919)966‐4199
MichaelChasnowEnvironmentalFinanceCenter,SchoolofGovernment
Knapp‐SandersBuilding,CB#3330UniversityofNorthCarolinaatChapelHill
ChapelHill,NC27599(919)843‐4954
Michael_Chasnow@kenan‐flagler.unc.edu
JeffHughes
EnvironmentalFinanceCenter,SchoolofGovernmentKnapp‐SandersBuilding,CB#3330
UniversityofNorthCarolinaatChapelHillChapelHill,NC27599(919)843‐4956
1
ABSTRACT
Giventhelownumberofcustomersalesuptakerecordsforenergyefficiencyand
renewableenergy(EERE)loanproducts,traditionalmethodsofdemandormarketanalysis
arenotpossibleforemergingresidential,commercialandindustrialEEREloansectors.In
thispaperweask,givenlimitedhistoricmarketdataforEEREloans,howcancities,
counties,banksandstatesassesspotentialmarketsforEEREloanuptake?Toanswerthis
question,wedevelopanewmethodologyforassessingpotentialresidentialdemandfor
EEREfinancingproducts,andusetheCharlestonSAVESTMprogramtodemonstratehowthe
TrafficLightDemandRatingSystemmarketanalysismethodologyworks.
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I. INTRODUCTION
ResidentialbuildingsintheUnitedStatesaccountforabout20%ofgreenhousegas
emissions(EPA2010)androughly20%ofthenation’stotalenergyconsumption(EIA
2008).Meetinganationalgoalofreducinggreenhousegasemissionsbymorethan80%by
2050willrequirewidespreadcoordinatedefforttoreducetheenergyuseofourexisting
buildingstock,andincreasedregulatorycommitmenttomandateenergyefficiency
standardsinnewconstruction.Onekeyingredientinupgradingexistingbuildingstock
withenergyefficiencyretrofitsisdevisingstrategiestoenablebuildingownerstopayfor
thehighupfrontcostsassociatedwithenergyefficiencyandrenewableenergy(EERE)
construction.FinancingtoolsaimedatEEREprojectsrangefromrebates,grants,andloan
products,andarecurrentlygrowinginsizeandnumber.However,acurrentgapinthe
developmentofwide‐scaleEEREloanuptakeistheidentificationofkeygroupsof
residentialcustomerswithdemandforEEREfinanceproducts.Currently,thereisno
strategicapproachforeffectivelytargetingandmarketingEEREprogramstothecustomers
mostlikelytoparticipatein,andsuccessfullyrepay,EEREloans.
Inthispaperweintroduceamethodologywhereinwedevelopalternatemeasures–
categorizedas‘determinantsofdemand’–toforecastenergyefficiencyloanadoption,
usingdataandinformationfromcountyparcel‐leveldataandnationallyavailableenergy
efficiencydatarepositories.ThesedatasetsareusedtoestimatefuturedemandforEERE
financeprograms,basedonhousing,industryandproperty‐levelcharacteristicsthat
correlatewithlargeroomforenergyefficiencygains.Theseearlystagemarketanalyses
providecriticalplanningtoolsfortheprogramsalesforce,determiningprogrammatic
scale,andasaroadmapfortargetedmarketingcampaigns.Todate,marketanalysisof
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EEREfinanceproductsremainscoarseandhighlygeneralized,andthispaperaimstofill
thisgapinthegreendevelopmentfinancearena.
Wedeveloptwoseparatemarketanalysisprocesses,oneformeasuringpotential
residentialdemandforEEREfinancingproducts,andoneformeasuringindustrialdemand
forEEREfinancingproducts.WeusemarketanalysisfortheCityofCharleston’s
CharlestonSAVESTMprogram,whichfocusesontheresidentialsector,todemonstratethis
marketanalysismethodology.
Thismethodologyisinnovativeinseveralways.First,webaseEEREloanuptakeon
determinantsofdemandspecifictothehousingstock,industrialportfolioandother
economiccharacteristicsofthehouseholdsandbusinessesinthestudyarea.Speculation
onthescaleandscopeofdemandforenergyefficiencyupgradesisoftenbasedon
aggregatemeasuresofenergyusageandeconomicactivity.Intheanalysis,wedrilldown
toindividualhouseholdsandbusinessestomeasureandidentifyspecificlocaleswithlarge
potentialdemandforEEREloans.Next,thismethodologyisscalableforvariousmarket
sizes–fromcitytocountytostate–andusespubliclyavailabledatatotailortheanalysisto
theregionorarea.Finally,wecrosstabulateparcel‐levelhousingandindustrydatawith
energyefficiencymeasures,specifictotheparcel‐levelcharacteristics.Thisspatial
matchingwitheconomicandenergyefficiencycharacteristicsisaninnovationwithinthe
demandstudyspace.
Thispaperisorganizedasfollows.Inthenextsectionweprovidebackground
informationondevelopmenttodateofmarketdemandmethodologiesforgreenenergy
financeprograms.Next,weintroduceourcasestudylocation,theCityofCharleston,South
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Carolina,andthedatausedforanalysis.Inthenextsection,wedescribeTrafficLight
DemandRatingSystemmethodologyforutilizingpublicallyavailabledatatoassessdemand
forEEREfinanceprograms.ThismethodologywasdevelopedbytheEnvironmental
FinanceCenterandcommissionedbyAbundantPowerinsupportofthe
CharlestonSAVESTMprogram.Followingthis,wepresentfindingsfromthe
CharlestonSAVESTMDemandAnalysis.Lastly,wediscussfuturedirectionsforEERE
financingdemandstudies.
II. BACKGROUND
Loanproductdemandanalysestypicallymeasurepotentialloanuptakeeitherbyusing
historicaldataoncomparableproducts,orbyconductingasurveytoestimatecustomer
uptakeratesatvariouspricepoints.Asenergyefficiencyloanprogramsremaininearly
stagesofdevelopmentandhavefewcustomersalesuptakerecordsbywhichtoforecast
potentialdemand,traditionalmethodsofdemandormarketanalysisarenotpossiblefor
emergingresidential,commercialandindustrialenergyefficiencyandrenewableenergy
(EERE)loansectors.
Recentreportsoflessonslearnedinfirstgenerationhouseholdenergyefficiency
improvementprogramsemphasizethat“timespentstudyingthetargetpopulationis
important”(Fuller2010page2)but,itremainsunclearhowprogramsshouldfirstidentify
targetpopulationsforsuchprograms.Insimpleterms,whatcharacteristicscomprisea
potentialenergyefficiencyupgradecustomer?Inaddition,verylittleattentiononthe
relationshipbetweentargetcustomersandEEREfinanceproducts(e.g.,loans,rebates,
incentiveprograms).
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CurrentresearchintomarketingEERElendingprogramsfocusesonstrategiesfor
promotingEERElendingproductsandreachingthegeneralpopulationinagiven
jurisdiction.OurdemandanalysismethodologyenablesEERElendingprogram
administratorstouseresidentialorcommercialbuildingcharacteristics(andcredithistory
throughutilitybillrepayment)tounderstandandmeasuredemand.Thisallows
administratorstocreateactionableprogramrolloutstrategiesattheblock,zipcodeor
countylevel.Existingresearchidentifiesstrategiestoimprovemarketingefforts,andour
methodologyaddstothiseffortbyenablingprogramadministratorstobettertarget
locationsforEEREprogramrollouts,whichallowsforfurthercustomizationofmarketing
efforts(i.e.,thetworesearchstrandscomplementoneanother).
III. CASESTUDY:CITYOFCHARLESTON’SCHARLESTONSAVESTMPROGRAM
TheCharlestonSAVESTMProgram(theProgram)intheCityofCharleston,South
CarolinaisaMunicipalEnergyEfficiencyProgramdesignedtostimulategreencollarjobs
whileenablingtheCityofCharlestontopromotesustainableandverifiableenergysavings
toindividuals,andcommercialandinstitutionalentities.Giventhewidegeographical
spaceanddiversemunicipalpopulationofCharleston,Phase1oftheProgramwilltarget
residentialpropertieswithenergyefficiencyprojectloans.
ThisDemandAnalysisusessecondarydataontheCityofCharleston’sresidential
propertiestoidentifygeographicareasandpropertytypesthatarelikelytofinancean
energyefficiencyupgradeviatheCharlestonSAVESTMloanprogram.Byidentifyingtarget
locationsandproperty‐typeswithintheresidentialsector,theDemandAnalysiswillassist
inthedevelopmentofastrategicandcost‐efficientmarketingcampaign.
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Analysisofdemandforresidentialenergyefficiencyprojectloanswouldtypically
measurepotentialloanuptakeeitherbyusinghistoricaldataoncomparableprogramsor
byconductingasurveytoestimatecustomeruptakeratesatvariouspricepoints.Energy
efficiencyloanprogramshowever,remaininearlystagesofdevelopment.Thereforethis
analysisreliesonalternatemeasurescategorizedas‘determinantsofdemand’forenergy
efficiencyloanadoption,usingdataandinformationfromcountyparcel‐leveldataand
nationallyavailableenergyefficiencydatarepositories.Thesedatasetsareusedto
estimatefuturedemandfortheProgram,basedonhousingandproperty‐level
characteristics.Thisanalysisforecastsdemandforenergyefficiencyloansforresidential
homeownersbasedonauniquesetofdemandindicatorsdescribedinthisreport.
IV. DATA
Thisanalysisdrawsfromthefollowingdatasources:
CharlestonCountyAuditor(2010)Parcel‐levelpropertydataforCityofCharleston;
EnergyInformationAdministration(2005)OfficeofEnergyMarketsandEndUse,
FormsEIA‐457A‐Gofthe“2005ResidentialEnergyConsumptionSurvey”;
LEEDforHomesRatingSystem,Version2008;
USCensusBureau(2000)DecennialCensus.Accessedat:www.census.gov;and
USDepartmentofEnergy(2010)HomeEnergySavercalculator,Environmental
EnergyTechnologiesDivision,LawrenceBerkeleyNationalLaboratory.
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Figure 1 City of Charleston Housing and Energy Use Profile, Fiscal Year 2009‐10
Residential Housing and Energy Profile
City of CharlestonaFiscal Year 2009-10
Zip
Code
Median HHLD
Income
% Families
Below Poverty
Line
% of Zip
Code's
Housing that
are Rented
Average fair
market
housing value
Number of
residential
parcels
Average
housing area
(square feet)
Average build
year
29401 36,671 18% 47% 902,869 1,469 2,964 PRE‐190029403 17,843 37% 57% 273,200 2,673 1,744 193229405 23,200 30% 47% 82,351 4,185 1,311 195629406 32,127 19% 46% 106,947 3,281 1,451 198129407 37,436 13% 41% 206,722 8,101 1,842 196529412 45,762 9% 26% 240,861 10,071 1,785 197729414 48,251 7% 33% 181,487 8,062 1,893 198829418 35,424 12% 43% 120,779 2,484 1,468 198129420 46,366 12% 25% 108,585 1,261 1,501 197629449 32,958 20% 11% 177,634 1,930 1,754 198129451 75,847 3% 10% 1,089,866 1,415 2,551 198229455 40,175 12% 8% 619,638 5,550 2,152 198929464 57,014 6% 28% 347,119 11,389 2,213 198429466 67,492 6% 12% 304,132 7,825 2,497 1999
Zip
Code
% using
electricity as
primary fuel
% using gas as
primary fuel
% using oil as
primary fuel % forced‐duct
% forced ‐ no
duct% heat pump % otherc
29401 38% 62% 0.1% 53% 2% 37% 7.4%29403 19% 80% 0.9% 42% 25% 21% 11.0%29405 14% 85% 1.0% 57% 30% 11% 2.3%29406 61% 38% 0.8% 35% 9% 53% 2.2%29407 39% 58% 2.6% 60% 6% 30% 4.1%29412 63% 35% 1.9% 40% 4% 51% 5.3%29414 80% 19% 1.0% 20% 1% 76% 2.2%29418 65% 35% 0.0% 58% 1% 41% 0.2%29420 45% 54% 0.6% 63% 2% 34% 1.3%29449 65% 33% 1.1% 13% 21% 55% 10.9%29451 94% 3% 2.1% 14% 2% 82% 2.1%29455 83% 15% 1.9% 11% 8% 76% 4.1%29464 94% 4% 2.4% 9% 2% 88% 1.4%29466 79% 21% 0.2% 3% 2% 93% 2.3%
External Sources: Census Bureau, 2006 American Community Survey & 2000 Decennial Census; FY 2010 Property data for Charleston Countya Analysis includes greater Charleston area including: Mt. Pleasant, North Charleston, Hollywood, Hanahan, Isle of Palms and Kiawah Island.b Residential property defined as parcels with use code equal to 10R (n=69,515)c other heat / cooling systems: electricity radiant, solar, and baseboard heat
Zip codes with fewer than 500 residential parcels are excluded
RESIDENTIAL HOUSING ENERGY CHARACTERISTICS FUEL SOURCE HEATING‐COOLING SYSTEM
"ZIP CODE" DEMOGRAPHICS (CENSUS 2000 ZCTAs) RESIDENTIALb HOUSING CHARACTERISTICS
8
V. OVERVIEWOFTHETRAFFICLIGHTDEMANDRATINGSYSTEM
a.Methodology
Toidentifyconcentrationsofhighdemandpotentialloanrecipients,wecreateasetof
demandindicatorsbasedonexistingresearchfromtheHomeEnergySaverprogramto
categorizevarioushousingcharacteristics(seemeasuresofdemandbelow).
Next,weassigneachresidentialparcelpoints(1–3)foreachdeterminantofdemand,
basedonthedemandlevel,thensumeachparcel’spointstofitintotheTrafficLight
DemandRatingSystem.Followingthis,azipcode‐levelindexisgeneratedbymultiplying
numberofhousingunitsperpointvalue*pointvalue.Thiscreatesarankedorderingof
potentialdemand,forallthirteenzipcodesintheanalysis.
UsingourTrafficLightEnergyRetrofitDemandIndex,thefinalstepislocatingspatial
concentrationsofhighdemandcustomerswithinthegreaterCityofCharleston(seemap
onPage15).
b.MeasuresofDemand
TheTrafficLightDemandRatingSystemuses(4)housingcharacteristics,detailed
belowintheDeterminantsofDemandsection,identifiedasinfluencingahousehold’s
demandforenergyefficiencyretrofits.Foreachofthese(4)housingcharacteristics,we
estimatepotentialdemandforenergyefficiencyretrofitsaccordingtotwomeasuresof
demand.
Thefirstmeasureofdemandistheenergyefficiency/energyexpenditureforeach
housingcharacteristic.Forexample,althoughahomewithlargersquarefootageis
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moreefficientpersquarefootthanasmallerhome,ithaslargeroverallenergy
expenditures,andahigherdemandforenergyupgrades.Annualenergy
expendituresprovideabasisforacost‐benefitcalculationforthebreakevenpoint
wherepotentialenergyutilitysavingsbecomegreaterthanthetotalloanamount
Thesecondmeasureofdemandisthehome’senergyretrofitupgradeproject
potential.Thismeasuretakesintoaccountprojectpotentialspecifictothehousing
characteristics.Forexample,homesusingnaturalgasarealreadymoreenergy
efficientthanhomesusingelectricity,butduetotechnologiesspecifictonaturalgas
systems,possessmoreenergyefficiencypotentialassociatedwithupgradesthan
electricitypoweredhomes.
Eitherenergyefficiencyorretrofitprojectupgradepotentialisusedtoassignpointsto
eachresidentialparcel,asappropriateforeachhousingcharacteristic.
c.PointSystem
Eachofthe(4)housingcharacteristicshavespecificthresholdsidentifiedas
contributingtoahome’senergyefficiency,orretrofitupgradepotential.Fortheanalysis,
specificpointsareallottedtoeachcharacteristicinthefollowingstructure:
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Figure 2 Traffic Light Demand System point values
FortheCharlestonSAVESTMDemandAnalysis,pointsareassignedtoeachresidential
parcel,foreachofthe(4)housingcharacteristics,creatinga12pointscale(3maxpoints*
4characteristics=4–12pointscale).InthesummaryPotentialMarketforResidential
EnergyRetrofitUpgradesintheCityofCharleston,perparcelpointsareaggregatedtothe
zipcodelevel.
VI. DETERMINANTSOFDEMAND
Whenviewingthechartsbelow,lookforzipcodeswithmoregreenareatoidentifythe
concentrationsofhighdemandacrosstheCity’szipcodeareas.
a.YearofConstruction1:
Theyearapropertyisbuiltisonekeydeterminantofpotentialenergyandcostsavings.
Newerhomes,especiallythosebuiltwithinthelastdecade,aremorelikelytohaveenergy
1Energyefficiencyreferencefor‘YearofConstruction’isEnergyInformationAdministration(2005)OfficeofEnergyMarketsandEndUse,FormsEIA‐457A‐Gofthe“2005ResidentialEnergyConsumptionSurvey”
RED: Low Demand: Worth 1 Point
There is very little potential for dollar and energy savings.
YELLOW: Medium Demand: Worth 2 Points
There is potential for dollar and energy savings, but specific
retrofits would not increase energy efficiency as significantly as
in High Demand homes, meaning energy bill savings for retrofits
would be relatively low.
GREEN: High Demand: Worth 3 Points
A home with this characteristic possesses high potential savings
from energy efficiency improvements.
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efficientappliances,whileveryoldbuildings,suchasthosebuiltbefore1940,maybe
difficulttoretrofit.
Figure 3 Build year for residential housing in the City of Charleston, per zip code
b.HousingFloorSpace(Area)2:
Thesizeofahomealsoinfluencesthepotentialforenergyandcostsavings.Larger
homesaregenerallymoreattractiveformanytypesofretrofits(e.g.,airandductsealing),
duetotheincreasedenergysavingsacrosstheentirefootprintofthehome.However,
housesthatareverylarge,suchas4000+squarefeet,begintolosesomeofthebenefits
fromretrofitimprovements.Forexample,suchalargehomemayhaveoneheatpumpfor
thebasementandfirstfloor,andanotherheatpumpforthesecondandthirdfloor.
Therefore,payingtoreplacethesetwoheatpumpswithmoreenergyefficientoneswould
notprovidethesamesavingsopportunityasreplacingoneinefficientheatpumpthat
servesanentire2000‐2500squarefoothome.
2 Energyefficiencyreferencefor‘HousingArea’isEnergyInformationAdministration(2005)OfficeofEnergyMarketsandEndUse,FormsEIA‐457A‐Gofthe“2005ResidentialEnergyConsumptionSurvey”
0
2,000
4,000
6,000
8,000
10,000
12,000
number of parcels
before 1950 1950 to 1979 1980 to 1989 1990 to 2000 after 2000
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Figure 4 Residential floor space in the City of Charleston, by zip code
c.HeatingSystemType:
Thetypeofheatingsystemalsoinfluencesthepotentialforenergyandcostsavings
fromretrofits.Onthedrasticside,ahomewithnoheatingsystemhaslesspotentialfor
energyandcostssavings.Ontheotherhand,U.S.GreenBuildingCouncil(USGBC)research
demonstratesthatnewheatpumpsaresignificantlymoreenergyefficientthanolderheat
pumps,andtherefore,homeswithheatpumpsaspartoftheirheatingandcoolingsystem
possessrelativelyhighpotentialforenergyandcostsavings.Othercommonheating
systemtypesincludebaseboardheat,forcedduct,hotwaterandsolar,whichcanbe
standaloneoractasbackupheatsourcesforheatpumpsystems.
0
2,000
4,000
6,000
8,000
10,000
12,000number of parcels
more than 4000 sq ft 3000 to 3999 sq ft 2000 to 2999 sq ft
1000 to 1999 sq ft less than 1000 sq ft
13
Figure 5 Residential heat & cooling system types in the City of Charleston, by zip code
Note:otherheatingandcoolingsystemtypesincludesolar,baseboardheat,andelectric‐radiant
d.FuelforHeating&Cooling:
Thetypeoffuelusedforheatingandcoolinghomesisanotherkeydeterminant.
AccordingtoUSGBCresearch,homesthatareheatedandcooledbynaturalgashavethe
highestpotentialforsavingsfromenergyefficiencyimprovements,followedbyoiland
electric.
Figure 6 Fuel source for residential parcels in the City of Charleston
0
2,000
4,000
6,000
8,000
10,000
12,000number of parcels
heat pump forced‐duct forced‐no duct other
0
2,000
4,000
6,000
8,000
10,000
12,000
number of parcels
Oil
Gas
Electricity
14
Figure 7 Potential M
arket for Residential Energy Retrofit Upgrad
es for the City of Charleston
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VII. POTENTIALRETROFITSFORATYPICALHIGHDEMANDHOME
Toprovideasnapshotintothetypesofretrofitimprovementspotentialloanrecipient
householdswouldundertake,weusedtheDepartmentofEnergy’sHomeEnergySaver
calculatortocreateaprofileofcommonimprovementsforrepresentativehighdemand
householdsinCharleston,SC.
Anyprojectrecommendationswouldbebasedonanauditassessmentofcashflow
positiveorcashflowneutralpayback.Forresidentialenergyretrofitloans,themonthly
loanpaymentwillbeequaltoorlessthanthehousehold’smonthlyutility‐billsavings.
Tonote,theestimatedloanamountsassumethatthehomeownerdecidestomakeall
therecommendedimprovementswithintheupgradepackagecategory.Ifahomeowner
decidedtoonlytakeonsomeoftherecommendedretrofitprojects,thecostandloan
amountwouldbelower.
RepresentativeHigh“Green”DemandHouseholdinCharleston(12/12points):
Builtin1973,thishomeis2500Sq.Ft,usesanelectricheatpumpforitsheating/cooling
system,hasacentralairconditioner,andusesnaturalgasasfuelforitshotwaterheater.
Thehome’saverageannualenergybillisapproximately$2,450($204permonth).
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$120
Table 1. Annual energy bill savings for upgrade packages
VIII. KEYFINDINGSFORCITYOFCHARLESTON
Basedonourmethodologyandanalysis,wewereabletoprovide
CharlestonSAVESTMwithconcreterecommendationsforprogramrollout.These
recommendationsincludedspecificzipcodestotarget,retrofitupgradestofocuson,and
UpgradePackages UpgradeCost(Range)
AnnualEnergyBillSavings*
BasicEfficiencyPackage AtticInsulation
WallandCrawlSpaceInsulationAirSealing:25%airleakagereduction
$1,250‐$1,875$2,250‐$2,750$2,500‐$3,750
$260$250
DuctSealing:Reduceleakageto6% $2,500 $106 Total:$8,500‐
$10,875$736/yr
MediumRetrofitPackage AtticInsulationWallandCrawlSpaceInsulationAirSealing:25%airleakage
reductionDuctSealing:Reduceleakageto6%
SEER14HeatPump(4tonunit)
$1,250–$1,875$2,250‐$2,750$2,500‐$3,750
$2,500$5,000‐$6,000
$260$250
$120$106$513
GasWaterHeater(62%efficiency) $900‐$1,050 $60 Total:$14,400‐
$17,925$1,455/yr
DeepRetrofitPackage AtticInsulationWallandCrawlSpaceInsulationAirSealing:25%airleakage
reductionDuctSealing:Reduceleakageto6%SEER14HeatPump(4tonunit)
GasWaterHeater(62%efficiency)ClothesWasher(EnergyStar)2paneEnergyStarWindows
$1,250‐$1,875$2,250‐$2,750$2,500‐$3,750
$2,500$5,000‐$6,000$900‐$1,050$600‐$1,000
$11,000‐$15,000
$260$250
$120$106$513$60$146$184
Coolroof:Solarreflectance $3,000‐$5,000 $29
Total:$29,000‐$38,925
$1,668/yr
*Annualenergybillsavingsaretheestimatedreductioninenergybillamounts,perretrofit,fortherepresentativehome.Theseannualsavingsareestimatedascostsavingsoverandabovetheminimalbuildingcodemandatedfornewunits.Accordingly,savingsmaybeunderestimatedifresidentialunitsdonotmeetminimalnewconstructionstandardspriortoretrofit.
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heatingsystemsthathavethegreatestpotentialforupgrades.Belowarethe
recommendationstheEnvironmentalFinanceCenterprovidedtoCharlestonSAVESTM
basedonourDemandAnalysis:
1)ZipCodes29412and29464RepresentTopTargets
Usingourratingssystem,thesetwozipcodeseachhaveover9,800highdemand
residentialunitsforenergyefficiencyupgrades.MountPleasant’s29464zipcodehasthe
greatestnumberofhighdemandresidentialunits,totaling11,277.Bothoftheseareas
presentabigopportunityforprogramrollout.
2)ThreeCoreZipCodesProvideOpportunityforFocusedProgramRollout
29414,29407and29412eachhaveover8,000highdemandresidentialunits,andtaken
together,totalnearly26,000highdemandunitsforenergyefficiencyupgrades.
Accordingly,CharlestonSAVESTMcouldfocusitsmarketingandprogramrolloutinthese
adjoiningareasofthecitytoincreasepositivespilloverofprogrameffortstogain
homeownerparticipation.
3)HeatPumpsareaGreatOpportunitywithintheResidentialRetrofitMarket
Ouranalysisfindsupgradingheatpumpsinhomeswitholderheatpumpsisoneofthetop
dollarandenergysavingsretrofitmeasureshomeownerscanundertake.Heatpumpsare
verycommoninCharlestonhomes,andCharlestonSAVESTMcouldfocusonheatpump
upgradesaspartofmarketingandpromotionalefforts,specificallyinhighdemandzip
codeswithhighpercentagesofhomeswithheatpumps,including29412,29414and
29464.
4)HomesFueledbyNaturalGasarePrimeRetrofitProgramTargets
Homesfueledbynaturalgasareprimeretrofittargetsduetohighpotentialforenergyand
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dollarsavings.IntheCityofCharleston,twoadjoiningzipcodesthatpossesshigh
residentialdemandalsohaveabnormallyhighpercentageofgas‐poweredhomes,
specifically,29407and29412.Accordingly,marketingrolloutwithinthesezipcodescould
focusonthepotentialforcostsavingsfromupgradingoldgaswaterheatersand/or
furnacestomoreenergyefficientmodels.
IX. CONCLUSIONSANDNEXTSTEPS
ThesedeterminantsremainuntestedastheCharlestonSAVESTMProgramhasyetto
launch.Tocontinuetorefineanddevelopthismethodology,thenextstepistoevaluate
programperformanceandmeasureloanuptakeandrepayment–inmid‐streamfirst
generationprograms–inordertomodifyandimprovetargetedmarketinginearlystages
ofprogramdevelopment.Moreover,incorporatingothercriticalcomponentsofmarket
demand,includingcustomerrepaymenthistory(eitherthroughwaterorelectricutility
bills),wouldfurtherenhanceourcurrentmethodology.Asnotedinaprominentstudyon
residentialretrofitprograms,determinantsofdemandwillbeuniquetoeachplace(Fuller
2010,page4),therebymakingtheavailabilityoflocaldataandexamininglocation‐specific
customerandclimatecharacteristicscriticaltoforecastdemand.
Asgreenfinanceprogramscontinuetodevelopproducts,policiesandstrategies,ithas
becomeclearinthisstudyandseveralothers,thathighdemandfinancingcustomersare
notthecustomersmostinneedofenergyefficiencyupgradesandcostsavings(Fuller
2009,pagevii),astheytendtobeeconomicallysecureandliveinhigher‐endhomes.
Thereforewithincommunities,lower‐incomecitizensandtenantsmaybeburdenedwith
higherenergyusageandbills,andhavelessaccesstoresourcestomakeimprovementsin
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theirhomes.Furtherresearchcouldbuildoffourresidentialmarketdemandmodel,and
incorporateuniquewaysofassessingpotentialcustomer’sabilitytotakeonenergy‐saving
retrofitloans,possiblyincorporatingutilitybillormortgagepayments,tobettertarget
lower‐incometractsthatcouldbenefitfromfinancingforretrofitupgradesandcost
savings.
Moreover,therearelargepotentialmarketsforEEREloanprogramsoutsideofthe
residentialsectorthatrequireseparatedemandforecastingmodelsandstrategies,
principallythecommercialandindustrialsectors.Thecommercialsectorpossessesa
landlord‐tenantdisconnectwithregardstothepaymentofenergybills,withtenants
typicallypayingenergybills,whichcomplicateshowtoforecastandstimulategreen
financeprograms.Intheindustrialsector,identifyingspecificupgradesthatcompanies
wouldbenefitfromisacorecomponentofforecasting,butthereneedstobeabetter
understandingofhowindustrialsectorcompaniesmakestrategicfinancialinvestmentsto
moreeffectivelyrolloutindustrialEEREloanprograms.Themethodologydepictedinthis
paperprovidesagoodbasefordemandforecastingandprogramrolloutinresidential
sectorEEREloanprograms,andshouldbebuiltupontohelpforecastandstimulate
demandinthecommercialandindustrialsectors.
X.SUMMARY
Ourdemandanalysismethodologyenablesenergyefficiencyandrenewableenergy
(EERE)lendingprogramadministratorstouseresidentialorcommercialbuilding
characteristics(andcredithistorythroughutilitybillrepayment)tounderstandand
measuredemand.Thisallowsadministratorstocreateactionableprogramrollout
20
strategiesattheblock,zipcodeorcountylevel.Existingresearchidentifiesstrategiesto
improvemarketingefforts,andourmethodologyaddstothiseffortbyenablingprogram
administratorstobettertargetlocationsforEEREprogramrollouts,whichallowsfor
furthercustomizationofmarketingefforts(i.e.,thetworesearchstrandscomplementone
another).
Ourmethodologycurrentlypossessesfourkeydeterminantsofdemand,andtaken
together,thesedeterminantscanhelpprogramadministratortargetEERElendingprogram
rollout.Thesefourdeterminantsofdemandarerelatedtobuildingcharacteristics,and
compriseof1)Yearofconstruction,2)Housingfloorspace(area),3)Heatingsystemtype
and4)Fuelforheatingandcooling.Theseresidentialbuildingcharacteristicscouldalsobe
combinedwithcredithistory,eitherthroughFICOscoresorutilitybillrepayment,to
provideamorecomprehensivebuildingandfinancialpictureofpotentialclientsfor
programadministrators.
WeapplythisrelativelynovelmethodologytotheCharlestonSAVESTMProgramto
helpinformtargetareaswithinthecityandtoidentifykeypotentialupgradesthatwould
provideresidentialparticipantsmoreenergysavings.Usingtheratingssystembuiltoffthe
fourdeterminantsofdemand,ouranalysisenabledspecificrecommendationsfortheEERE
lendingprogramrollout,including:
ZipcodesCharlestonSAVESTMshouldinitiallytargetforprogramrolloutbecauseof
concentrationofhighdemandresidentialunits;
Specificretrofitupgradesthatwillprovidecustomerswiththelargestenergy
savings,whichcanguidemarketingandpromotionalefforts;and
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Typeofhomestotarget,thosefueledbynaturalgasforheatingandcooling,which
providehomeownerswiththehighestpotentialforfinancialandenergysavings.
AnalysisincludedidentificationofthetwozipcodesinCharlestonwiththedensest
concentrationofnaturalgas‐fueledhomes.