Identifying Critical Factors in the Cost Effectiveness of ... · Los Angeles Los Angeles Department...

1

Iden%fyingCri%calFactorsintheCost-effec%venessofSolarandBa:eryStorage

inCommercialBuildings

JoyceMcLaren([email protected])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

2

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.

3

Questions Addressed

Ques%onsAddressed

Ques%onsansweredbythisresearchinclude:

•Aresolarand/orstorageeconomicalinmylocaGon?•Whichcommercialbuildingtypesaremostlikelytoseecost-savingsfromsolarand/orstorage?•Wherearetheemergingmarketsforsolarand/orstorage?•WhichuGlityratestructuresencouragesolarand/orstoragedeployment?•Howdocost-opGmalsystemsizesvaryacrossbuildingsandlocaGons?•WhatistheroleofpoliciesandincenGvesinsolarand/orstorageeconomics?

NREL|3

4

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

5

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

7

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


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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

57

NoDemandCharges

RateComponentsRepresentedbytheRatesModeled


The73uGlityratesmodeledrepresentavarietyoftariffstructures.ThemajorityofrateshaddemandchargeelementsorGme-of-useelements,andsomehadboth.Severalflatrateswerealsomodeled.AllofthetariffsweretakenfromNREL’sUGlityRateDatabaseandwereuptodateasofJanuary2017.Netenergymetering(NEM)isnotincludedinthecalcuaGons,eveniftheuGlityoffersNEM.

9

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.


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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.


12

Cost Effective Technology Combinations by Location and Building Type

CostEffec%veTechnologyCombina%onsbyLoca%onandBuildingType

Atthehighertechnologycostpoint,solar-onlysystemsarealreadyeconomicalinmanylocaGonsandbuildingtypes.Astechnologycostsdecline,solarcombinedwithstoragebecomeseconomicalinmorelocaGonsandbuildingtypes.

Fast

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AlbuquerqueAnaheimAtlantaBalGmoreBoulderChicagoDuluthFairbanksHelenaLasVegasLosAngelesMiamiMinneapolisNewYorkPhoenixSanFranciscoSeaUle

StretchTechnologyCostPoint

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AlbuquerqueAnaheimAtlantaBalGmoreBoulderChicagoDuluthFairbanksHelenaLasVegasLosAngelesMiamiMinneapolisNewYorkPhoenixSanFranciscoSeaUle

HighTechnologyCostPoint

Note:MissingiconsindicatenodataisavailablebecausetheloadforthereferencebuildingwasnoteligibleforanyoftheratesmodeledforthatlocaGon.


NotEconomical SolarOnly Solar+Storage StorageOnly

13

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

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osts

avin

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Eachlineonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).

StorageOnly Solar+Storage SolarOnly


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Impact of Location on Expected Savings

ImpactofLoca%ononExpectedSavings

San

Fran

cisc

o

Anah

eim

LosA

ngel

es

New

Yor

k

Fairb

anks

Albu

quer

que

Hele

na

Phoe

nix

BalG

mor

e

LasV

egas

Dulu

th

Boul

der

Mia

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Chic

ago

Atla

nta

Min

neap

olis

SeaU

le

0%

10%

20%

30%

40%

50%

Expe

cted

life

-cyc

lec

osts

avin

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Eachlineonthechartrepresentsoneoftheindividualcasesmodeled(e.g,.onebuildingtypeinonelocaGon).


LocaGonhasanotableimpactonexpectedsavingsfromsolarandstoragesystems,likelyduetothevariaGoninratestructureandelectricitypriceacrosslocaGons.Acrossallscenariosmodeled,solar-with-storagesystemsweremostovencosteffecGveinSanFrancisco,Anaheim,andLosAngeles.Solar-with-storagealsowasfoundcosteffecGveinsomebuildingsinFairbanks,Albuquerque,Boulder,andMiami.Solar-onlyprojectsprovidedsavingsinmanyoftheotherlocaGons.


15

Impact of Building Type on Expected Savings

ImpactofBuildingTypeonExpectedSavings

Strip

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Mid

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Apar

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0%

10%

20%

30%

40%

50%

Expe

cted

life

-cyc

lec

osts

avin

gs

Eachlineonthechartrepresentsoneoftheindividualcasemodeled(e.g.,onebuildingtypeinonelocaGon).

StorageOnly SolarOnly Solar+Storage

Solarcombinedwithstoragewasfoundtoprovidecostsavingsineverybuildingtype,andsolar-onlyprojectswereeconomicalinmanyaddiGonalscenarios.ThepercentsavingsislessvariableacrossbuildingtypethanacrosslocaGon,indicaGngthatthebuildingloadprofilemayhavelessinfluenceonsavingspotenGalthanothervariables,suchasratestructure.


16

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


17

Impact of Rate Structure Components on Cost-Optimal Technology Combination

ImpactofRateStructureComponentsonCost-Op%malTechnologyCombina%on

Acrossthescenariosmodeled,solarcombinedwithstorageismorelikelytobeeconomicalunderdemandchargesandunderrateswithGme-of-usecomponents.

0%10%

20%

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Perc

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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).


18

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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30%

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50%

Expe

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Eachpointonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).

HighTechnologyCostPointLowTechnologyCostPoint

MidTechnologyCostPointStretchTechnologyCostPoint

StorageOnlySolar+Storage

SolarOnly


19

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

3K

4K

5K

6K

7K

8K

BaU

ery

Capa

city

(kW

h)

Eachpointonthechartrepresentsoneoftheindividualcasesmodeled(e.g.,onebuildingtypeinonelocaGon).CasesforwhichnobaUerywasbuiltarefilteredout.

OpGmalbaUerycapacityincreasesunderhigherdemandchargesandfallingtechnologycosts.





20

Impact of Demand Charge Level and Technology Cost on Solar and Storage Economics


$0 $20 $40DemandCharge

($/kW)

0%

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$0 $20 $40DemandCharge

($/kW)

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MidTechnologyCostPoint

$0 $20 $40

DemandCharge($/kW)

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LowTechnologyCostPoint

$0 $20 $40

DemandCharge($/kW)

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$10 $20 $30 $40DemandCharge

($/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.

21

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


22

Savings from Demand Charge Reductions versus Energy Charge Reduc-tions by Location and Building Type

SavingsfromDemandChargeReduc%onsversusEnergyChargeReduc%onsbyLoca%onandBuildingType

San

Fran

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LosA

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0%

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Savi

ngso

verS

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mL

ifeGm

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Loca%on


Smal

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BuildingType

Note:Includesresultsforprojectsthatincludestorage.Averageofallcostpointsmodeled.


23

Impact of Cost Declines on System Sizes

ImpactofCostDeclinesonSystemSizesAveragesystemsizesincreasewithdecliningcosts.

0

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PVSize(kW)

0K

2K

4K

6K

8K

BaU

ery

Capa

city

(kW

h)




SolarOnly





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


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


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


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


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


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


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.



Averageexpectedsavings1.93%



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


NoNEMNEMat

wholesalerate

NEMatretailrate

31

Impact of ITC on Expected Savings

ImpactofITConExpectedSavings


MidCostPointwith10%ITC

MidCostPointwith0%

ITC


LowCostPointwith10%ITC

LowCostPointwith0%

ITC


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).


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<[email protected]>.


34

Components Included in the Cost Assumptions


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


36

Policy and Financing Assumptions


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/


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.


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.

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