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Iden%fyingCri%calFactorsintheCost-effec%venessofSolarandBa:eryStorage
inCommercialBuildings
JoyceMcLaren(joyce.mclaren@nrel.gov)KateAnderson,NickLaws,PieterGagnon,NicholasDiOrio,XiangkunLi
NREL/PR-6A20-70813
February2018
ContentsIdentifying Critical Factors in the Cost-effectiveness of Solar and Battery Storage in Commercial Buildings . . . . . . . . . . . . . . . . . . . 2
Questions Addressed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Locations Modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Scenarios Modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Commercial Building Types Modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Commercial Building Loads Modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Utility Rates Modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Solar PV and Storage Price Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Impact of Technology Cost Reductions on Solar + Storage Economics by Location . . . . . . . . . . . . . . . . . . . . . . . . . 11
Cost Effective Technology Combinations by Location and Building Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Impact of Technology Cost Reductions on Expected Savings . . . . . . . . . . . 13
Impact of Location on Expected Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Impact of Building Type on Expected Savings . . . . . . . . . . . . . . . . . . . . . . . 15
Average Potential for Savings from Solar or Solar + Storage in Commercial Buildings for Locations Modeled . . . . . . . . . . . . . . . . . . . . . 16
Impact of Rate Structure Components on Cost-Optimal Technology Combination . . . . . . . . . . . . . . . . . . . . . . . . . 17
Impact of Demand Charge Level and Technology Cost on Expected Percent Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Impact of Demand Charge Level and Technology Cost on Optimal Battery Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Impact of Demand Charge Level and Technology Cost on Solar and Storage Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Savings from Demand Charge Reductions versus Energy Charge Reductions by Technology Combination . . . . . . . . . . . . . . . 21
Savings from Demand Charge Reductions versus Energy Charge Reductions by Location and Building Type . . . . . . . . . . . . . 22
Impact of Cost Declines on System Sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Impact of Building Energy Consumption on Economic System Sizes . . . . . . 24
Load Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Impact of Load Variability on Expected Savings . . . . . . . . . . . . . . . . . . . . . . 26
Impact of Load Variability on Expected Saving from Solar Combined with Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Impact of Load Variability on Battery Configuration . . . . . . . . . . . . . . . . . . 28
Impact of Electricity Price Increases on Expected Savings from Solar and/or Storage Systems . . . . . . . . . . . . . . . . . . . . . . . . 29
Impact of Net-Metering Policy on Solar and Storage Economics . . . . . . . . . 30
Impact of ITC on Expected Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Modeling Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Renewable Energy Optimization Model (REopt) . . . . . . . . . . . . . . . . . . . . . 33
Components Included in the Cost Assumptions . . . . . . . . . . . . . . . . . . . . . 34
Battery and Inverter Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Policy and Financing Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Citations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
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Identifying Critical Factors in the Cost-effectiveness of Solar and Battery Storage in Commercial BuildingsIden%fyingCri%calFactorsintheCost-effec%venessofSolarandBa:eryStorageinCommercialBuildings
ThisanalysiselucidatestheemergingmarketfordistributedsolarpairedwithbaUeryenergystorageincommercialbuildingsacrosstheUnitedStates.Itprovidesinsightintothenear-termandfuturesolarandsolar-plus-storagemarketopportuniGesaswellasthevariablesthatimpacttheexpectedsavingsfrominstallingbehind-the-metersystems.
NREL|2
Thisworkistheresultofatwo-yearresearchprojectconductedattheNaGonalRenewableEnergyLaboratoryfundedbytheU.S.DepartmentofEnergy'sSolarEnergyTechnologiesOffice.PleaseseetheprojectwebsiteathUps://openei.org/wiki/Solar+Storage.
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Questions Addressed
Ques%onsAddressed
Ques%onsansweredbythisresearchinclude:
•Aresolarand/orstorageeconomicalinmylocaGon?•Whichcommercialbuildingtypesaremostlikelytoseecost-savingsfromsolarand/orstorage?•Wherearetheemergingmarketsforsolarand/orstorage?•WhichuGlityratestructuresencouragesolarand/orstoragedeployment?•Howdocost-opGmalsystemsizesvaryacrossbuildingsandlocaGons?•WhatistheroleofpoliciesandincenGvesinsolarand/orstorageeconomics?
NREL|3
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Locations Modeled
Loca%onsModeled
SeaUle
SanFrancisco
Phoenix
NewYorkMinneapolis
Miami
LosAngeles
LasVegas
Helena
Duluth
ChicagoBoulder
BalGmore
Atlanta
AnaheimAlbuquerque
Cost-opGmalsolarand/orbaUerystoragesystemconfiguraGonswereidenGfiedfor17locaGons,73uGlityrates,16commercialbuildingtypes,andmulGpletechnologycostpoints.
NREL|4
Fairbanks
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Scenarios Modeled
ScenariosModeled
ClimateZone City UGlity NumberofRatesModeled
NumberofBuildingTypes
Modeled
NumberofScenariosModeled
1A Miami FloridaPower&LightCo
2B Phoenix SaltRiverProject3A Atlanta GeorgiaPowerCo
3B
LosAngeles LosAngelesDepartmentofWater&Power
LasVegas NevadaPowerCoAnaheim SouthernCaliforniaEdisonCo
3C SanFrancisco PacificGas&ElectricCo
4ANewYork ConsolidatedEdisonCo-NYIncBalGmore BalGmoreGas&ElectricCo
4B Albuquerque PublicServiceCoofNM
4C SeaUle CityofSeaUleWashington5A Chicago CommonwealthEdisonCo5B Boulder PublicServiceCoofColorado
6A Minneapolis MinnesotaPowerInc6B Helena NorthWesternCorporaGon7 Duluth NorthernStatesPowerCo-Minnesota
8 Fairbanks GoldenValleyElecAssnIncGrandTotal
1,0501541,2601641,645164
5951631,9601652,0991610
2,5521681,1191631,120164
7001542,3101681,680163
9801621,1201622,240164
1,085163630162
24,14527073
Morethan24,000scenariosweremodeledtoidenGfycost-opGmalsolarand/orbaUerystoragesystemconfiguraGonsfor73commercialelectricityratesfortheuGliGeswiththelargestnumberofcustomersineachclimatezone.
hUps://openei.org/wiki/Solar+StorageNREL|5
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Commercial Building Types ModeledCommercialBuildingTypesModeled
Hourlyannualloadprofilesweregeneratedfor16commercialbuildingtypes,basedontheDepartmentofEnergy'sCommercialReferenceBuildings.
BuildingType AnnualEnergyConsumpGon(kWh) PeakAnnualDemand(kW)
Hospital
LargeOffice
SecondarySchool
LargeHotel
Supermarket
OutpaGent
PrimarySchool
MediumOffice
SmallHotel
RetailStore
StripMall
Restaurant
MidriseApartment
Warehouse
FastFood
SmallOffice 26
38
75
82
71
152
153
173
350
380
370
435
606
1,138
1,831
1,620
87,369
192,700
222,718
272,544
342,943
509,387
514,380
764,771
925,051
1,079,781
1,601,198
1,979,115
2,488,769
2,689,236
6,524,278
8,654,762
Note:FiguresshownhereareanaverageofalllocaGonsmodeled.hUps://openei.org/wiki/Solar+StorageNREL|6
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Commercial Building Loads Modeled
CommercialBuildingLoadsModeled
Thehourlyannualloadprofileswereadjustedfortypicalmeteorologicalyear(TMY)data.RatesandbuildingtypeswerematchedbasedontheloadprofileofthebuildingandtheeligibilityrequirementsstatedintheuGlity’sratetariffsheet.
May14 15 16 17 18 19 20
0
200
400
600
800
1000
1200
1400
1600
Load
(kW
)
ExamplesofAnnualLoadProfiles
LargeOfficeHospital
LargeHotelWarehouse
FullServiceRestMidriseApartment
OutpaGentRetailStore
SecondarySchoolSupermarket
hUps://openei.org/wiki/Solar+StorageNREL|7
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Utility Rates Modeled
U%lityRatesModeled
51
22
Time-of-UseEnergyCharges
69
4
TieredDemandCharges
24
49
FixedDemandCharges
68
5
TieredEnergyCharges
0
10
20
30
40
50
60
70
Num
bero
frat
es
21
52
FlatEnergyCharges
24
49
Time-of-UseDemandCharges
FlatEnergyRate-TheperkWhchargeisindependentoftheGmeitisusedoramountthatisused.TimeofUse-ThechargeisbasedontheGmeofdayand/oryeartheenergyisused.Tiered-Eachunituptoabaseamountischargedatoneamount,andeachaddiGonalunitusedischargedatahigheramount.DemandCharge-InaddiGontoanenergycharge($perkWh),thereisachargebasedonthehighestlevelofdemand(kW)overabillingperiod,typicallymeasuredover15-minuteintervals.Note:Severaloftheratesarecategorizedinmorethanoneenergyrateordemandchargecategory.Thisisbecausecoreratehasonetypeofcomponentwhileariderofthesameratehasadifferenttypeofcomponent.
Componentnotpresent Componentpresent
16
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NoDemandCharges
RateComponentsRepresentedbytheRatesModeled
hUps://openei.org/wiki/Solar+StorageNREL|8
The73uGlityratesmodeledrepresentavarietyoftariffstructures.ThemajorityofrateshaddemandchargeelementsorGme-of-useelements,andsomehadboth.Severalflatrateswerealsomodeled.AllofthetariffsweretakenfromNREL’sUGlityRateDatabaseandwereuptodateasofJanuary2017.Netenergymetering(NEM)isnotincludedinthecalcuaGons,eveniftheuGlityoffersNEM.
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Solar PV and Storage Price Assumptions
SolarPVandStoragePriceAssump%ons(CostPoints)UsedinCost-op%miza%onModeling
Inordertounderstandtheimpactoftechnologycostonsolarandstorageeconomics,mulGplecostpointsweremodeledforeachscenario(buildingtypeandlocaGoncombinaGon).Eachcostpointrepresentstheinstalledcostofsolarandstoragetechnologies(includinghardware,engineering,labor,andO&Mcosts).TheREoptmodelselectsthecost-opGmalsizeofsolarand/orbaUerysystemforeachscenario,basedontheseprojectcostinputsandtheotherinputvariables(e.g.financing,ratestructure,buildingload,etc.).DetailedlistsoftheelementsincludedinthecostinputsbelowandothermodelinginputsandassumpGonsareprovidedattheendofthispublicaGon.
hUps://openei.org/wiki/Solar+StorageNREL|9
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Results
Results
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Impact of Technology Cost Reductions on Solar + Storage Economics by Location
ImpactofTechnologyCostReduc%onsonSolar+StorageEconomicsbyLoca%on
HighTechnologyCostPoint MidTechnologyCostPoint LowTechnologyCostPoint StretchTechnologyCostPoint0%
5%
10%
15%
20%
25%
30%
35%
40%
Perc
ento
fCas
esM
odel
ed
23cases
58cases
80cases
106cases
HelenaNewYork
DuluthMiami
FairbanksBoulder
AlbuquerqueLosAngeles
AnaheimSanFrancisco
AssolarandbaUerycostsdecline,solarwithstorageprojectsbecomeeconomicalin10ofthe17locaGons.
hUps://openei.org/wiki/Solar+StorageNREL|11
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Cost Effective Technology Combinations by Location and Building Type
CostEffec%veTechnologyCombina%onsbyLoca%onandBuildingType
Atthehighertechnologycostpoint,solar-onlysystemsarealreadyeconomicalinmanylocaGonsandbuildingtypes.Astechnologycostsdecline,solarcombinedwithstoragebecomeseconomicalinmorelocaGonsandbuildingtypes.
Fast
Foo
d
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aura
nt
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eO
ffice
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ium
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rmar
ket
War
ehou
se
AlbuquerqueAnaheimAtlantaBalGmoreBoulderChicagoDuluthFairbanksHelenaLasVegasLosAngelesMiamiMinneapolisNewYorkPhoenixSanFranciscoSeaUle
StretchTechnologyCostPoint
Fast
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aura
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AlbuquerqueAnaheimAtlantaBalGmoreBoulderChicagoDuluthFairbanksHelenaLasVegasLosAngelesMiamiMinneapolisNewYorkPhoenixSanFranciscoSeaUle
HighTechnologyCostPoint
Note:MissingiconsindicatenodataisavailablebecausetheloadforthereferencebuildingwasnoteligibleforanyoftheratesmodeledforthatlocaGon.
hUps://openei.org/wiki/Solar+StorageNREL|12
NotEconomical SolarOnly Solar+Storage StorageOnly
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Impact of Technology Cost Reductions on Expected Savings
ImpactofTechnologyCostReduc%onsonExpectedSavings
Ascostsdecline,systemsbecomeeconomicalformorelocaGonsandbuildingtypes,andtheaverageexpectedcostsavingsacrossallscenarios(indicatedbygreyline)increasesslightly.
HighTechnologyCostPoint LowTechnologyCostPoint MidTechnologyCostPoint StretchTechnologyCostPoint
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Expe
cted
life
-cyc
lec
osts
avin
gs
Eachlineonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).
StorageOnly Solar+Storage SolarOnly
hUps://openei.org/wiki/Solar+StorageNREL|13
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Impact of Location on Expected Savings
ImpactofLoca%ononExpectedSavings
San
Fran
cisc
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Anah
eim
LosA
ngel
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New
Yor
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Fairb
anks
Albu
quer
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Phoe
nix
BalG
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egas
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Atla
nta
Min
neap
olis
SeaU
le
0%
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Expe
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life
-cyc
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osts
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Eachlineonthechartrepresentsoneoftheindividualcasesmodeled(e.g,.onebuildingtypeinonelocaGon).
StorageOnly Solar+Storage SolarOnly
LocaGonhasanotableimpactonexpectedsavingsfromsolarandstoragesystems,likelyduetothevariaGoninratestructureandelectricitypriceacrosslocaGons.Acrossallscenariosmodeled,solar-with-storagesystemsweremostovencosteffecGveinSanFrancisco,Anaheim,andLosAngeles.Solar-with-storagealsowasfoundcosteffecGveinsomebuildingsinFairbanks,Albuquerque,Boulder,andMiami.Solar-onlyprojectsprovidedsavingsinmanyoftheotherlocaGons.
hUps://openei.org/wiki/Solar+StorageNREL|14
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Impact of Building Type on Expected Savings
ImpactofBuildingTypeonExpectedSavings
Strip
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0%
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50%
Expe
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osts
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Eachlineonthechartrepresentsoneoftheindividualcasemodeled(e.g.,onebuildingtypeinonelocaGon).
StorageOnly SolarOnly Solar+Storage
Solarcombinedwithstoragewasfoundtoprovidecostsavingsineverybuildingtype,andsolar-onlyprojectswereeconomicalinmanyaddiGonalscenarios.ThepercentsavingsislessvariableacrossbuildingtypethanacrosslocaGon,indicaGngthatthebuildingloadprofilemayhavelessinfluenceonsavingspotenGalthanothervariables,suchasratestructure.
hUps://openei.org/wiki/Solar+StorageNREL|15
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Average Potential for Savings from Solar or Solar + Storage in Commercial Buildings for Locations ModeledThemapbelowsummarizestheresultsforallbuildingsandlocaGonsmodeled.Thedarker-shadedstateswerefoundtohavehigher
potenGalforsavings.ThepiechartsindicatethedegreetowhicheachtechnologycombinaGoncontributedtothecostreducGon.SavingswerehighestinCalifornia,NewYork,NewMexico,andAlaska.SolaralonewaseconomicalforsomeofthebuildingtypesineverylocaGon,whilesolarcombinedwithstorageprovidedcostsavingsinmorethanhalfofthelocaGons.Somestates,suchasGeorgiaandWashington,hadfewcasesinwhichsolarand/orstoragewasfoundtoprovidesavingspotenGal.
AveragePoten%alforSavingsfromSolarorSolar+StorageinCommercialBuildingsforLoca%onsModeled
Solar+StorageSolarOnly
StorageOnlyNotEconomical 1% 25%
AverageExpectedLife-cycleCostSavingsAcrossAllCasesModeled
hUps://openei.org/wiki/Solar+StorageNREL|16
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Impact of Rate Structure Components on Cost-Optimal Technology Combination
ImpactofRateStructureComponentsonCost-Op%malTechnologyCombina%on
Acrossthescenariosmodeled,solarcombinedwithstorageismorelikelytobeeconomicalunderdemandchargesandunderrateswithGme-of-usecomponents.
0%10%
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ithR
ate
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Time-of-UseEnergyRate
TieredEnergyRate
FlatEnergyRate
TieredDemandCharge
FixedDemandCharge
NoDemandCharge
Time-of-UseDemandCharge
NotEconomical StorageOnly SolarOnly Solar+Storage
Ratecomponentsarenotmutuallyexclusive.Atypicalcommercialrateconsistsofanenergycomponent(kWh)andademandchargecomponent(kW).
hUps://openei.org/wiki/Solar+StorageNREL|17
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Impact of Demand Charge Level and Technology Cost on Expected Percent Sav-ings
ImpactofDemandChargeLevelandTechnologyCostonExpectedPercentSavings
Projectsthatincludestoragearemostfrequentlyeconomicalatdemandchargelevels>$10,regardlessoftechnologycost.Astechnologycostsdecline,theexpectedpercentsavingsacrossallprojectsincreases.
$0 $2 $4 $6 $8 $10 $12 $14 $16 $18 $20 $22 $24 $26 $28 $30 $32 $34 $36 $38 $40 $42 $44
MaximumDemandCharge($/kW)
0%
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Expe
cted
life
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osts
avin
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Eachpointonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).
HighTechnologyCostPointLowTechnologyCostPoint
MidTechnologyCostPointStretchTechnologyCostPoint
StorageOnlySolar+Storage
SolarOnly
hUps://openei.org/wiki/Solar+StorageNREL|18
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Impact of Demand Charge Level and Technology Cost on Optimal Battery Capac-ity
ImpactofDemandChargeLevelandTechnologyCostonOp%malBa:eryCapacity
$0 $2 $4 $6 $8 $10 $12 $14 $16 $18 $20 $22 $24 $26 $28 $30 $32 $34 $36 $38 $40 $42 $44
MaximumDemandCharge($/kW)
0K
1K
2K
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BaU
ery
Capa
city
(kW
h)
Eachpointonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).CasesforwhichnobaUerywasbuiltarefilteredout.
OpGmalbaUerycapacityincreasesunderhigherdemandchargesandfallingtechnologycosts.
HighTechnologyCostPointLowTechnologyCostPoint
MidTechnologyCostPointStretchTechnologyCostPoint
StorageOnlySolar+Storage
hUps://openei.org/wiki/Solar+StorageNREL|19
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Impact of Demand Charge Level and Technology Cost on Solar and Storage Economics
HighTechnologyCostPoint
$0 $20 $40DemandCharge
($/kW)
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rcen
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ases
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$0 $20 $40DemandCharge
($/kW)
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$0 $20 $40
DemandCharge($/kW)
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NumberofCasesModeledwithDemandChargesof
DifferentLevels
ImpactofDemandChargeLevelandTechnologyCostonSolarandStorageEconomics
NotEconomical StorageOnly SolarOnly Solar+StoragehUps://openei.org/wiki/Solar+StorageNREL|20
Percentofscenariosineachcostpointforwhichsolarand/orstoragewasfoundtobecost-effec%ve.
Astechnologypricesdrop,solar-with-storagebecomeseconomicalinmorecasesandatlowerdemandchargerates.
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Savings from Demand Charge Reductions versus Energy Charge Reductions by Technology Combination
SavingsfromDemandChargeReduc%onsversusEnergyChargeReduc%onsbyTechnologyCombina%on
Solar+Storage SolarOnly StorageOnly0%
2%
4%
6%
8%
10%
12%
14%
Expe
cted
Per
cent
Sav
ings
ove
rSys
tem
Life
Gme
AverageofalllocaGons,buildingtypesandcostpointsmodeled.
Onaverage,savingswerehighestforprojectsthatcombinedbothsolarandstorage.Themajorityofsavingsfrombothsolar-onlyandsolarwithstorageprojectswerederivedfromreducGonsinenergycharges.Thelimitednumberofstorage-onlyprojectsresultedinmostlydemandchargesavings,thoughsavingsweremarginal.
$/kWhSavings $/kWSavings
hUps://openei.org/wiki/Solar+StorageNREL|21
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Savings from Demand Charge Reductions versus Energy Charge Reduc-tions by Location and Building Type
SavingsfromDemandChargeReduc%onsversusEnergyChargeReduc%onsbyLoca%onandBuildingType
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ngso
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ifeGm
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$/kWhSavings $/kWSavings
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ket
Larg
eO
ffice
Hosp
ital
Smal
lHot
el
Larg
eHo
tel
BuildingType
Note:Includesresultsforprojectsthatincludestorage.Averageofallcostpointsmodeled.
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23
Impact of Cost Declines on System Sizes
ImpactofCostDeclinesonSystemSizesAveragesystemsizesincreasewithdecliningcosts.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2200
2400
2600
2800
3000
3200
3400
3600
3800
4000
4200
4400
4600
PVSize(kW)
0K
2K
4K
6K
8K
BaU
ery
Capa
city
(kW
h)
HighTechnologyCostPointLowTechnologyCostPoint
MidTechnologyCostPointStretchTechnologyCostPoint
StorageOnlySolar+Storage
SolarOnly
HighTechnologyCostPoint
MidTechnologyCostPoint
LowTechnologyCostPoint
StretchTechnologyCostPoint
PVSize(kW)BaUeryPower(kW)BaUeryCapacity(kWh)CapitalCostofAllProjects($)CapitalCostofSolar-onlyProjects($)CapitalCostofSolar+StorageProjects($)CapitalCostofStorage-onlyProjects($) $131,682
$366,250$117,614$232,723329kWh
51kW408kW
$120,563$358,018$91,430
$189,828146kWh
27kW324kW
$107,352$311,516$66,256
$146,19235kWh12kW
239kW
$131,724$390,458$53,973
$113,59315kWh
6kW156kW
AverageSystemSizesandCapitalCostsAcrossAllBuildingsandLoca%ons
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24
Impact of Building Energy Consumption on Economic System Sizes
ImpactofBuildingEnergyConsump%ononEconomicSystemSizes
OpGmalbaUerycapacityincreaseswithbuildingload,especiallyatlowertechnologycosts.ThelargestbaUerysystemswerecosteffecGveinhospitalsandlargeoffices.
0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 7,000 7,500 8,000
BaUeryCapacity(kWh)
0M
2M
4M
6M
8M
10M
Annu
alE
nerg
yCo
nsum
pGon
(kW
h)
FastFoodHospitalLargeHotelLargeOfficeMediumOffice
MidriseApartmentOutpaGentPrimarySchoolRestaurantRetailStore
SecondarySchoolSmallHotelSmallOfficeStripMallSupermarket
Warehouse
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25
Load Factors
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70%
LoadFactor
FastFood
Hospital
Restaurant
Supermarket
SmallHotel
LargeHotel
OutpaGent
MidriseApartment
LargeOffice
RetailStore
StripMall
SmallOffice
Warehouse
PrimarySchool
MediumOffice
SecondarySchool
LoadfactorindicatesthedegreeoffluctuaGoninthebuildingload.Itiscalculatedbydividingthemeandemandbythepeakdemandoverthecourseofayear.Alowpercentageindicateshighervariabilityintheload.Thechartbelowshowstheloadfactorsofthebuildingsmodeled.
LoadFactors
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26
Impact of Load Variability on Expected Savings
ImpactofLoadVariabilityonExpectedSavings
36% 38% 40% 42% 44% 46% 48% 50% 52% 54% 56% 58% 60% 62% 64% 66% 68% 70% 72% 74%
LoadFactor(lower%indicatesmorevariabilityinload)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Expe
cted
%S
avin
gs
StorageOnly SolarOnly Solar+StoragehUps://openei.org/wiki/Solar+StorageNREL|26
AcommonassumpGonisthatloadprofileswithpeaksarethemostlikelycandidatesforsavingsfromstorageduetotheopportunityfordemandchargereducGon.Ourresultsindicatethatbycombiningsolarwithstorage,buildingswithlessvariabilitymayalsoachievesavings.ThisislikelyduetotheenergycostreducGonsresulGngfromthesolargeneraGon.
27
Impact of Load Variability on Expected Savings from Solar Combined with Storage
ImpactofLoadVariabilityonExpectedSavingsfromSolarCombinedwithStorage
hUps://openei.org/wiki/Solar+StorageNREL|27
35% 40% 45% 50% 55% 60% 65% 70%0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Expe
cted
Per
cent
Sav
ings
ove
rSys
tem
Life
Gme
$/kWhSavings $/kWSavings
LoadFactor
Breakingoutenergychargeanddemandchargesavingsbybuildingloadfactorshowstheextenttowhichvariabilityintheloadimpactssavings.Demandchargesavingsarehigherincaseswithmorevariabilityinloadprofile;however,totalsavingsfromcombinedsolarandstorageprojectsisnotrelatedtoloadvariability.
28
Impact of Load Variability on Battery Configuration
ImpactofLoadVariabilityonBa:eryConfigura%onNorelaGonshipwasfoundbetweenloadvariabilityandthebaUeryconfiguraGon.OpGmizaGonmodelingresultedinvastlydifferentbaUeryduraGonsforbuildingsofthesametypeandofsimilarloadvariability.Othervariables,suchastechnologycostandratestructure,weremoreinfluenGalonthecost-opGmalbaUerysizingandduraGon.
36% 38% 40% 42% 44% 46% 48% 50% 52% 54% 56% 58% 60% 62% 64% 66% 68% 70% 72% 74%
LoadFactor
0
2
4
6
8
BaU
ery
Dura
Gon
(kW
h/kW
)
FastFoodHospitalLargeHotelLargeOffice
MediumOfficeMidriseApartmentOutpaGentPrimarySchool
RestaurantRetailStoreSecondarySchoolSmallHotel
SmallOfficeStripMallSupermarketWarehouse
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29
Impact of Electricity Price Increases on Expected Savings from Solar and/or Storage Systems
ImpactofElectricityPriceIncreasesonExpectedSavingsfromSolarand/orStorageSystems
0.02%CAGR 0.38%CAGR 0.69%CAGR0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Perc
ento
fCas
esM
odel
ed
Note:Allvariablesexceptcompoundannualgrowthrateofelectricityareheldconstant.Resultsareforanaverageofallcostpoints.
Varyingelectricityprices(compoundannualgrowthrates)haveliUleimpactonexpectedsavings.Acrossallscenariosmodeled,lowannualelectricitypricegrowthof0.02%resultedineconomicalsystemsin17%ofthecases,whilehighannualpricegrowthof0.69%resultedinsystemsbeingeconomicalinabout19%ofthecases.
StorageOnly Solar+Storage SolarOnly
hUps://openei.org/wiki/Solar+StorageNREL|29
Averageexpectedsavings1.93%
Averageexpectedsavings2.15%
Averageexpectedsavings2.38%
30
Impact of Net-Metering Policy on Solar and Storage Economics
ImpactofNet-MeteringPolicyonSolarandStorageEconomics
0%
5%
10%
15%
20%
Aver
age
Perc
entS
avin
gs
0%
5%
10%
15%
20%
Perc
ento
fCas
esM
odel
ed
PercentofCasesModeledwithEconomicTechnologyCombina%onsandAveragePercentSavings
Note:Allvariablesexceptnet-meteringavailabilityareheldconstant.Resultsareforasinglecostpoint.Solarsystemsizeiscappedat100%ofbuildingload.
Netenergymetering(NEMornet-metering)isnotincludedintheresultspresentedintheotherslidesofthisreport.NEMisnotavailableinalllocaGonsandNEMofferingsconGnuetoevolve.WhenNEMisavailable,thegridservesthesamepurposeasabaUery.Whennet-meteringisnotavailable,storageprojectsarefoundtobeeconomicalinmorecases.ThechartbelowshowsthatreducGonofthenet-meteringratefromaretailtowholesaleratealsosGmulatesstorage.AveragingacrossalllocaGonsandbuildingtypesforonecostpoint,theaverageexpectedlifeGmesavingsishighestwhennet-meteringisavailable.
SolarOnly StorageOnly Solar+Storage
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NoNEMNEMat
wholesalerate
NEMatretailrate
31
Impact of ITC on Expected Savings
ImpactofITConExpectedSavings
MidTechnologyCostPoint
MidCostPointwith10%ITC
MidCostPointwith0%
ITC
LowTechnologyCostPoint
LowCostPointwith10%ITC
LowCostPointwith0%
ITC
StretchTechnologyCostPoint
StretchCostPointwith10%ITC
StretchCostPointwith0%
ITC
0%2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
22%
Expe
cted
%S
avin
gs
Thegraphbelowcomparestheaverageexpectedsavingsfromsolarand/orstoragesystemsunderdifferenttaxcreditsensiGviGesandtechnologycosts.AveragingacrossallbuildingtypesandlocaGons,expectednear-termorstretchgoal
technologycostreducGonsdonotmakeupforacompleteremovaloftheinvestmenttaxcredit(ITC).
hUps://openei.org/wiki/Solar+StorageNREL|31
with30%ITC with30%ITC with30%ITC
32
Modeling Assumptions
ModelingAssump%ons
33
Renewable Energy Optimization Model (REopt)
RenewableEnergyOp%miza%onModel(REopt)
NREL'sRenewableEnergyOpGmizaGonModel(REopt),whichprovidessite-specificcost-opGmaltechnologysoluGons,wasusedforthisanalysis.
REoptisamixedintegerlinearprogramthatoutputsopGmaltechnologysizingandhourlydispatchstrategiesalongwithfinancialdata.REoptlooksatsolarandstorageinintegraGonwithotherenergyassets,atasinglesiteoracrossaporyolioofsites,andcalculatessystemsizesandoperaGngstrategiestomaximizeeconomicbenefit.
NRELprovidesanalysisservicesusingthefull,in-houseREoptmodel.TheREoptLitewebtoolisasimplified,publiclyavailabletooltoevaluatesolarphotovoltaicsandbaUerystorageatasite.
FormoreinformaGonaboutREoptandtousetheREoptLitetool,visit:hUps://reopt.nrel.gov/oremail<REopt@nrel.gov>.
hUps://openei.org/wiki/Solar+StorageNREL|33
34
Components Included in the Cost Assumptions
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ComponentsIncludedintheCostAssump%ons
EPCOverhead&Profit
SovcostsDevelopercost(customeracquisiGon)InterconnecGon
Engineering,Planning&Construc%on(EPC)Costs
Controlsystem/SCADASitepreparaGonLoading&transportfrommanufacturerLiving&hoisGngbycraneonsiteProfessionalengineerstampedcalculaGons&drawingsManufacturertesGngandcommissioningElectricalbalanceofsystemsoutsideofcontainerElectricallaborStructuralbalanceofsystems(e.g.,fencing)
Ba:ery&HardwareCosts
BaUery(lithiumion)Inverter-powerconversionContainerorhousingContainerextras(insulaGon/walls)Electricalconduit(insideofcontainer)CommunicaGondeviceHeaGng,venGlaGon,air-condiGoning(HVAC)Meter(revenuegrade)FiredetecGonFiresuppressionLaborACmainpanelDCdisconnectIsolaGontransformerAuxillarypower,lighGng,etc.
35
Battery and Inverter Assumptions
Ba:eryandInverterAssump%ons
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Policy and Financing Assumptions
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PolicyandFinancingAssump%ons
NetEnergyMetering(NEM):NOTINCLUDEDThemodelingresultspresentedheredonotincludeaprovisionfornetenergymetering.NEMisnotavailableineverystate,andthepolicyisunderrevisionorreviewinsomestates.AsensiGvityanalysisispresentedthatindicatestheimpactofNEMonsystemeconomics.
InvestmentTaxCredit:Included,30%Aninvestmenttaxcreditof30%forsolartechnologyisincludedinthecalcuaGons.AsensiGvityanalysisispresentedthatindicatestheimpactofanITCstep-downorremovalonsystemeconomics.
ModifiedAcceleratedCapitalDeprecia%on(MACRS):5year+bonusdeprecia%onforsolarandba:erysystemcomponents
NootherFederalorStateincen%vesareincludedinthecalcula%ons.
Infla%onRate:2.5%
SystemLife:20years,ba:eryreplacementatyear10
DiscountRate:10.2%Theassumeddiscountrateusedforthemodeling(10.2%)istheweightedaveragecostofcapital(WACC)usedintheNaGonalRenewableEnergyLaboratory's2016AnnualTechnologyBaseline(ATB).Intheupdated2017ATB,thesameWACCisusedtorepresentlong-termaveragemarketcondiGons,whilecurrentmarketcondiGonsarerepresentedbya8.2%WACCinaccordancewiththeEnergyInformaGonAdministraGons's2017AnnualEnergyOutlook.
ItisnotedthatsomeindustryparGcipantsusediscountratesaslowas6%.Federally-fundedprojectsalsouselowdiscountrates,ovenaround3%.Usingalowerdiscountratewouldresultinmoreprojectsbeingeconomical.Thus,theresultspresentedinthisanalysiscouldbearguedtorepresentaconservaGveviewofsolarandstoragetechnologyeconomics.
37
Citations
Cita%ons
PVCostAssumpGonsarebasedonNREL’s2016"AnnualTechnologyBaseline(ATB)".Golden,CO:NaGonalRenewableEnergyLaboratory.hUp://www.nrel.gov/analysis/data_tech_baseline.html
StoragecostassumpGonsarebasedoncostdatacollectedbyNREL,summarizedin"BaUeryEnergyStorageMarket:CommercialScale,Lithium-ionProjectsintheU.S."byJoyceMcLaren,PieterGagnon,KateAnderson,EmmaElgqvist,RanFu,TimRemo,October2016.hUp://www.nrel.gov/docs/fy17osG/67235.pdf
UGlityRateDatabasehUp://en.openei.org/wiki/UGlity_Rate_Database
RenewableEnergyOpGmizaGonModelhUps://reopt.nrel.gov/
UnitedStatesClimateZoneshUp://apps1.eere.energy.gov/buildings/publicaGons/pdfs/building_america/4_3a_ba_innov_buildingsciencecli-matemaps_011713.pdf
LoadprofilesarebasedontheDepartmentofEnergyCommercialReferenceBuildingshUps://energy.gov/eere/buildings/commercial-reference-buildingsandcreatedusingEnergyPlusSovwarehUps://www.energyplus.net/
hUps://openei.org/wiki/Solar+StorageNREL|37
38
Related Work
RelatedWork
Simpkins,Travis,KateAnderson,DylanCutler,andDanOlis.2016.Op#malSizingofaSolar-Plus-StorageSystemforU#lityBillSavingsandResiliencyBenefits.NREL/CP-7A40-66088Golden,CO:NaGonalRenewableEnergyLaboratory.h!ps://www.nrel.gov/docs/fy17os5/66088.pdf.
hUps://openei.org/wiki/Solar+StorageNREL|38
McLaren,Joyce,andSethMullendore.2018.ValuingtheResilienceProvidedbySolarandBaBeryEnergyStorageSystems.Golden,CO:NaGonalRenewableEnergyLaboratory.h!ps://www.nrel.gov/docs/fy18os5/70679.pdf.
McLaren,Joyce,andSethMullendore.2017.Iden#fyingPoten#alMarketsforBehind-the-MeterBaBeryEnergyStorage:ASurveyofU.S.DemandCharges.NREL/BR-6A20-68963.Golden,CO:NaGonalRenewableEnergyLaboratory.h!ps://www.nrel.gov/docs/fy17os5/68963.pdf.
Whitepaper:hUps://www.nrel.gov/docs/fy17osG/68963.pdfData:hUps://data.nrel.gov/submissions/74Webinar:hUps://www.cleanegroup.org/webinar/nrel-demand-charges-storage-market/
McLaren,Joyce,PieterGagnon,KateAnderson,EmmaElgqvist,RanFu,andTimRemo.2016BaBeryEnergyStorageMarket:CommercialScale,Lithium-ionProjectsintheU.S.NREL/PR-6A20-67235.Golden,CO:NaGonalRenewableEnergyLaboratory.h!ps://www.nrel.gov/docs/fy17os5/67235.pdf.