A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)

Abstract

The deployment of solar photovoltaics (PV) and electric vehicles (EVs) is continuously increasing during urban energy transition. With the increasing deployment of energy storage, the development of the energy sharing concept and the associated advanced controls, the conventional solar mobility model (i.e., solar-to-vehicles (S2V), using solar energy in a different location) and context are becoming less compatible and limited for future scenarios. For instance, energy sharing within a building cluster enables buildings to share surplus PV power generation with other buildings of insufficient PV power generation, thereby improving the overall PV power utilization and reducing the grid power dependence. However, such energy sharing techniques are not considered in the conventional solar mobility models, which limits the potential for performance improvements. Therefore, this study conducts a systematic review of solar mobility-related studies as well as the newly developed energy concepts and techniques. Based on the review, this study extends the conventional solar mobility scope from S2V to solar-to-buildings, vehicles and storage (S2BVS). A detailed modeling of each subsystem in the S2BVS model and related advanced controls are presented, and the research gaps that need future investigation for promoting solar mobility are identified. The aim is to provide an up-to-date review of the existing studies related to solar mobility to decision makers, so as to help enhance solar power utilization, reduce buildings' and EVs' dependence and impacts on the power grid, as well as carbon emissions.

Full text

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Sustainability2020,12,7035;doi:10.3390/su12177035www.mdpi.com/journal/sustainability
Review
ATechnicalReviewofModelingTechniquesfor
UrbanSolarMobility:SolartoBuildings,Vehicles,
andStorage(S2BVS)
PeiHuang
1
,XingxingZhang
1,
*,BenedettaCopertaro
1
,PuneetKumarSaini
1
,DaYan
2
,YiWu
2

andXiangjieChen
3

1
EnergyTechnology,DalarnaUniversity,79188Falun,Sweden;phn@du.se(P.H.);bcp@du.se(B.C.);
pks@du.se(P.K.S.)
2
SchoolofArchitecture,TsinghuaUniversity,Beijing100084,China;yanda@tsinghua.edu.cn(D.Y.);
y‐wu17@mails.tsinghua.edu.cn(Y.W.)
3
SchoolofArchitecture,CentreforRenewableEnergySystemsTechnology,LoughboroughUniversity,
LeicestershireLE113TU,UK;X.J.Chen@lboro.ac.uk
*Correspondence:xza@du.se;Tel.:+46‐(0)‐23‐77‐87‐89
Received:24July2020;Accepted:26August2020;Published:28August2020
Abstract:Thedeploymentofsolarphotovoltaics(PV)andelectricvehicles(EVs)iscontinuously
increasingduringurbanenergytransition.Withtheincreasingdeploymentofenergystorage,the
developmentoftheenergysharingconceptandtheassociatedadvancedcontrols,theconventional
solarmobilitymodel(i.e.,solar‐to‐vehicles(S2V),usingsolarenergyinadifferentlocation)and
contextarebecominglesscompatibleandlimitedforfuturescenarios.Forinstance,energysharing
withinabuildingclusterenablesbuildingstosharesurplusPVpowergenerationwithother
buildingsofinsufficientPVpowergeneration,therebyimprovingtheoverallPVpowerutilization
andreducingthegridpowerdependence.However,suchenergysharingtechniquesarenot
consideredintheconventionalsolarmobilitymodels,whichlimitsthepotentialforperformance
improvements.Therefore,thisstudyconductsasystematicreviewofsolarmobility‐relatedstudies
aswellasthenewlydevelopedenergyconceptsandtechniques.Basedonthereview,thisstudy
extendstheconventionalsolarmobilityscopefromS2Vtosolar‐to‐buildings,vehiclesandstorage
(S2BVS).Adetailedmodelingofeachsub‐systemintheS2BVSmodelandrelatedadvancedcontrols
arepresented,andtheresearchgapsthatneedfutureinvestigationforpromotingsolarmobilityare
identified.Theaimistoprovideanup‐to‐datereviewoftheexistingstudiesrelatedtosolarmobility
todecisionmakers,soastohelpenhancesolarpowerutilization,reducebuildings’andEVs’
dependenceandimpactsonthepowergrid,aswellascarbonemissions.
Keywords:solarmobility;electricvehicles;buildingcluster;energystorage;energysharing;
advancedcontrol

1.Introduction
1.1.Background
Buildingenergyusecurrentlyaccountsforover40%oftotalprimaryenergyconsumptioninthe
U.S.andE.U.[1].Thetransportationsectoralsorepresentsalargeenergyend‐userandconsumes
approximately25%oftheprimaryenergyworldwide[2].Tomeetthelargeenergyneedsinboththe
buildingsectorandtransportationsector,renewableenergy,whichhasmuchlowercarbonemissions
andrelativelylowercostscomparedwiththeconventionalfossilfuel‐basedenergy,offersa

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promisingsolution[3].Inthisregard,manycountriesandassociationshaveestablishedregulations
ortargetstopromotethedeploymentofrenewableenergy.Forinstance,theEuropean‘20‐20‐20
targets’aimtoachievea20%reductioninCO2emissions(comparedto1990levels),20%ofenergy
comingfromrenewables,anda20%increaseintheenergyefficiencyby2020.TheE.U.alsosetsa
targetof32%ofenergygenerationfromrenewablesby2030,andaminimumshareofatleast14%of
fuelfortransportpurposesmustcomefromrenewablesourcesby2030[1,4].Indifferentstatesofthe
U.S.,differentrenewableenergytargetshavealsobeendefined.Forinstance,Connecticutsetsatarget
of48%renewablegenerationshareofelectricitysalesby2030,andNewJerseysetsatargettoincrease
itsrenewableportfoliostandardstargetto50%.Amongallthestates,Californiaisthemostambitious
andsetsagoaltoachieve100%carbon‐freepowerby2045[5].China,astheworld’sbiggestenergy
consumer,alsoaimsfora35%ofrenewable‐basedelectricitygenerationby2030[6].Inorderto
achievetheserenewableenergytargets,twoimportantaspects,thewayrenewableenergyisused
andrenewableenergyself‐utilization,shouldbecarefullydetermined.
1.1.1.MarketTrendsofPVs
Theglobalsolarphotovoltaics(PV)marketisincreasingwithanapproximateexponentialtrend
[7].In2018,atotalof102.4GWPVpanelswereinstalledglobally,representinga4%year‐on‐year
growthoverthe98.5GWinstalledin2017.Thisledtoatotalglobalsolarpowercapacityofover500
GW.TheAsia‐Pacificregion(includingChina)wasleadingtheglobalPVmarket,anditownedmore
thanhalf(55%)oftheglobalsolarpowergenerationcapacity.Inthisregion,Chinaaloneoperated
nearly1/3rdoftheworld’ssolarpowergenerationcapacities.TheEuropeansolarpioneersranked
second,buttheirshareslippedto25%basedonacumulativePVcapacityof125.8GW.TheAmericas
weretheworld’sthirdlargestsolarregionin2018—withacumulativeinstalledcapacityof78.2GW
anda15%stake.
1.1.2.MarketTrendsofElectricVehicles(EV)
EVs,whicharepoweredbyelectricity,areconsideredasapromisingsolutiontoroadsideair
pollutionandassociatedhealthdamage,sincetheydirectlycutoffpollutionfromthesource.When
EVsarechargedbyrenewableenergy,suchasPVandwindturbines,theiroperationsaretotally
carbon‐freeandthusEVscanmakesubstantialcontributionstogreenhousegasemissions.Todate,
alotofgovernmentshaveestablishedpoliciesorgoalstopromotethedeploymentofEVs.For
instance,theSwedishgovernmenthassetagoalthat100%ofthenationalenergyusedinvehicle
fleetsshouldbeindependentoffossilfuelby2030[8].TheU.S.Federalgovernmenthasenacted
policiesandlegislationtopromotetheU.S.marketforEVs,suchasimprovementsintaxcreditsunder
currentlaw,andcompetitiveprogramstoencouragecommunitiestoinvestininfrastructure
supportingthesevehicles[9].TheHongKonggovernmenthasmadeeffortsinpromotingitspractical
applications,e.g.,taxreductions,aone‐for‐onereplacementscheme,subsidiesforEVpurchaseand
EVlicenses[10,11].TheSingaporegovernmenthasshowngreatinterestinadoptingEVs[12].The
EnergyMarketAuthority(EMA)andtheLandTransportAuthority(LTA)ofSingaporelaunchedthe
EVtestbedin2011todecideonthemassadoptionofEV.Followingpositiveresults,theyapproved
BlueSGPteLtd.[13],asubsidiaryofBolloréGroup,tolaunchanEVcar‐sharingprogramby2017[4].
TheFrenchgovernmentsetatargetoftwomillionEVsin2020[14].ThestockofEVs(i.e.,thenumber
ofEVsontheroad)isprojectedtoreach18.7millionin2030[15].Theauthorsin[16]stipulatedthe
introductionofaBuildingPlanstatingthat,witheffectfrom2020,thedeploymentofrechargeable
electricandhybridvehicles(HV)shouldrepresent30%ofallvehiclesalesby2020.Hence,thepublic
acceptanceofEVsandtheirswiftglobalmarketpenetrationsbecauseofthisareimposingincreased
impactsonthedeploymentofPVandsmartgrids.
1.1.3.MarketTrendsofStorage
AsreportedbytheKPMG(i.e.,KPMGInternationalCooperative),in2016,theUnitedStateshad
thelargestmarketforenergystorage,bothbynumberofprojectsandinstalledcapacity.Insome

Sustainability2020,12,70353of37
states,innovativeenergystorageincentiveprogramshavebeenimplemented.Atotalcapacityof62
MWofenergystoragehadbeeninstalledby2014,andthecountryhassetthetargetofa1325‐MW
energystoragecapacityby2020.Japanhassetanambitioustargettoproducehalfoftheworld’s
batteriesby2020.Thecountryhasasubsidyprogramfor66%ofthecostforhomesandbusinessthat
installlithium‐ionbatteries.Japanalsohasatargetof30%renewablesimplementationby2030.India
hasatargetof40GWofrenewableenergycapacityby2030.Amongthedifferentenergystorage
types,electricitystorageisaneconomicsolutionoffthegridinsolarhomesystemsandinmini‐grids
whereitcanalsoincreasethefractionofrenewableenergyinthesystemtoashighas100%[17].The
InternationalRenewableEnergyAgencyreportedatotalbatterycapacityinstationaryapplications
of11GW∙hin2017.Thetotalcapacityisexpectedtoreach100~167GW∙hby2030inthiscase.The
largebatterystoragemarketiscontributedbypairingabatterystoragesystemwiththeinstallation
ofnewsmall‐scalesolarPVsystems.Forexample,motivatedbythefinancialsupportforbattery
storage,nearly40%ofsmall‐scalesolarPVsystemsinGermanyhavebeeninstalledwithbattery
systemsinthepastfewyears.InAustralia,althoughthereisnoanyfinancialsupport,nearly7000
small‐scalebatterysystemswerestillinstalledin2016.Theeconomicsofbatterystorageinsuch
applicationsarealsoprojectedtoincreasesignificantlyinthefuture.Thegrowingcapacityofenergy
storageprovidesgreatopportunitiesforrenewableenergyutilizationandpromotessolarmobility.
1.1.4.BuildingProsumersRole
Buildingsconsumeabout40%ofenergyworldwide[18],andthispercentageisevenlargerin
high‐densitycities(e.g.,over90%inHongKong)[19].Toreducetheenergyusageinthebuilding
sector,renewableenergysystems,suchasPVpanelsandwindturbines,arewidelyinstalledin
buildings[20].Bysuchrenewableenergysystemsintegration,buildingsaretransferringtheirroles
fromconventionalelectricityconsumerstoelectricityprosumers.Asdefinedin[21,22],electricity
prosumersareelectricityconsumerswhoproduceelectricityfortheirownconsumptionusing
distributedenergytechnologies.Fromtheperspectiveofbuildings,thistransformationcanhelpcut
downgridpowerusage,therebyreducingtheelectricitycostsaswellasreducingcarbonemissions
ifgridpowerisproducedfromfossilfuels[23].Fromtheperspectiveofthepowergrid,thereduced
demandsonthebuildingsidecanhelpalleviatethegridstressandtherebypromotethepowergrid’s
stableandreliableoperation[24].Commontypesofelectricityprosumersarezeroenergybuildings
(ZEBs),whichproducethesameamountofenergytheyconsume.
TofacilitatetheapplicationofZEBs,manygovernmentshaveestablishedpoliciesandgoals.For
instance,Directive2010/31/EU,theEnergyPerformanceofBuildingsDirective(EPBD),setsthegoal
thatallnewbuildingsbuiltfromthebeginningof2021mustbenearlyzero‐energyandcost‐optimal
[25].Thenearlyzeroenergybuildingstrategy2020(ZEBRA2020)waslaunchedby17countriesin
2014,forthepurposeofcreatinganobservatoryfornetzeroenergybuildings(NZEBs)basedon
marketstudiesandvariousdatatoolsandthereforegeneratesdataandevidenceforoptimization
andpolicyevaluation[26].TheU.S.governmentsetsatargetthat50%ofcommercialbuildingswill
achievezero‐energyby2040,andallcommercialbuildingswillachievezero‐energyby2050[20].The
CaliforniaPublicUtilitiesCommissionoftheUSAhassetanetzeroenergytargetforallnew
residentialbuildingsby2020andforallnewcommercialbuildingsby2030[27].Similarpromotion
policiesandtargetscanalsobeobservedinChina,Korea,JapanandAustralia[28].Asreportedby
Tronchinetal.,thebuiltenvironmentrepresentsasuitableintermediatescaleofanalysisinMulti‐
LevelPerspectiveplanning,collocatedamonginfrastructureandusers[29].Temporalandspatial
decouplingofsupplyanddemandisanimportantelementthatshouldbeconsideredforthe
evolutionofbuiltenvironment,especiallywhencreatingsectorial‐levelplanningstrategiesand
policies.Theyalsodeterminedtheneedforresearchintodevelopinginnovationpathwaysfortheco‐
evolutionofthebuiltenvironmentandinfrastructure.Insuchacontext,theanalysisof
complementaritiesisparticularlypowerfulandshouldreceivemoreattention.Solarmobility
development,whichseekscomplementaritiesinmultiplesystems(i.e.,buildings,EVs,PVsand
energystorage),isinlinewiththiscontext.


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1.2.DefiningtheConceptofSolarMobility
AsproposedbyCEA‐INES(namelytheFrenchNationalInstituteforSolarEnergy)[30],the
conceptofsolarmobilityseeksasynergybetweenthefollowingthreesystems:EVs,PVsystemsand
theelectricitynetwork.Thebasicideaistocombineastandardgrid‐connectedPVsystemwith
standardEVs,alsoconnectedtothegrid[31].Inordertoensurethesolarchargingofthevehiclesand
minimizethegridimpact,alocalEnergyManagementSystemdecidesontheenergyflows.This
processiscalledsolar‐to‐vehicles(S2V)insomestudies[32],representingchargingEVsdirectlyusing
electricityfromPVs.Vehiclescanbechargedathomeusingresidentialchargingstationsoratpublic
chargingstationsinprivatebusinessorpubliccarparks.Theyconsidersuchaprocessreasonable
sincetheaveragecarisparked95%ofthetimeandchargingcantakealongtimebasedoncurrent
usagemodels.Intheirproposedconcept,theelectricityproducedbytheresidentialPVpanelsis
firstlyusedtosupplythehomeelectricalequipment(e.g.,householdappliances,multimediadevices,
etc.),andthentochargetheEVbattery,asshowninFigure1.Ifthereisanysurplusgeneration,such
anamountisfedintothepowergrid.Thesmartgridwillcollectdataonthegridloadsandpower
needsandredistributethesurplusgenerationtomeettheseloads/needs.Insuchacontext,buildings,
equippedwithPVsystemsandenergystoragesystems,arebecomingenergyproductionsiteswhere
EVscanbecharged.ThisconvergencebetweenbuildingsandtransportwillenableEVbatteriestobe
usedasameansofstorageandsupplyoflow‐carbonelectricitytomeetfluctuationsinproduction
andconsumption.NotethattheEVbatteryisalsoallowedtodischargeelectricitybacktothe
building/powergridinsuchamodel.Thisisadvantageousforgridmanagementandespeciallyfor
peaksmoothing.Thisconcepthasbeenextensivelystudiedfromatechnologicalviewpointin[33–
38].

Figure1.Conceptofsolarmobilitywithself‐consumption[31].
1.3.Values,ProblemsandChallengestotheSolarMobility
Values:WiththeincreasingdeploymentofPVs,EVsandenergystoragesystems,itisimportant
tosmartlyintegratethemtomaximizetheenergyefficiencyandcostbenefitsand,meanwhile,
minimizetheimpactonthepowergrid.Undersuchacontext,solarmobilitycanhelpimprovethree
values:autonomy,sustainability,andaffordability.Specifically,autonomyindicatesreducingthe
dependenceandimpactsonthepublicpowergrid.Ideally,withinabuildingcommunity/microgrid,
byactingasanelectricityprosumerandconsideringtheEVdemand,buildingscanbelargelycovered
bytheirownPVsystem.Sustainabilityindicatesincreasingtheself‐consumptionoflocallyproduced
PVpower,andthustheneedforpowerfromthepublicgrid,whichlargelydependsonfossilenergy
inmanycountries.Affordabilityindicatesincreasingtheeconomicbenefitsofthewholesystem.
Problems:AlthoughtheimportanceofPVs,EVs,andenergystoragehasbeenwellrecognized
globally,howtointegrateandmanagetheminaholisticway,simultaneouslytakinginto
considerationbuildingloadsandoccupants’livingrequirements,needstobeaddressed.Problems
suchaslargepowerpenetrationinthepowergrid,lowenergyefficiencyandloweconomic
performanceurgentlyneedtobesolved.Moreover,withthedevelopmentoftheenergysharing
conceptandassociatedadvancedcontrols,theconventionalsolarmobilityconceptandcontextare

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becominglesscompatibleandlimited.Forinstance,energysharingwithinabuildingclusterenables
buildingstosharetheirsurplusgenerationwithotherbuildings(includingtheirEVdemands)with
insufficientsupply,therebyhelpingimprovetheoverallrenewableenergyutilizationandreducing
gridpowerdependence.However,suchenergysharingnetworks,includingthesystemarchitecture
andassociatedadvancedcontrols,arenotconsideredintheconventionalsolarmobilitymodels.This
willlimitthepotentialforperformanceimprovementsthatcanbeotherwisebearticulatedand
demonstratedbythenewlydevelopedconceptsandmethods.Anotherexampleisthelackofenergy
storageintegrationintheexistingsolarmobilitymodel(notethat,inthisstudy,EVsareconsidered
tohaveaseparaterolefromenergystorage).
Challenges:Intermittencyisoneofthemajorshortfallsofsolarpower,whichhasadirect
influenceonthevoltagestabilityandtheoverallpowersystemsecurity,while,forEVs,theircharging
loadsaredifficulttopredictastheyarehighlyaffectedbydrivingpatternsanddrivingdistances.
BothPVpowerproductionandEVpowerdemandarehighlyuncertain.Forinstance,anEVcanbe
usedforcommutingpurposesduringthedaywhereaccesstochargingfacilitiesisnotavailable.This
meansthatchargingcouldonlyhappeninanEVowner’spremisesduringthenighttimewhenno
electricitycanbegeneratedbyPV.Suchtimemismatcheswilllimitthedeploymentofsolarenergy
inthemobilitysector.Thus,itischallengingtobridgethetemporalandspatialsupply–demand
mismatchtofacilitatesolarmobility.Whenbuildingsandenergystorageareintegratedintothesolar
mobilitycontext,anotherchallengeisthepropermanagementofdifferenttypesofsystemswith
variousresponsecharacteristicsandoperatingconstraints.Thisreviewpaperwillaimtopropose
someusefulsolutionsfromexistingstudiestoaddressthesechallenges.
1.4.AimandContributionsofThisReview
Thisstudyconductsatechnicalreviewofsolarmobility‐relatedstudiesaswellasnewly
developedenergyconceptsandtechniques.Byreviewingtheexistingstudies[39–41],thisstudy
extendstheconventionalsolarmobilitymodelfromS2Vtosolar‐to‐buildings,vehiclesandstorage
(S2BVS).Intheextendedcontext,solarmobilityinvolvessolarenergyflowandexchangethrough
buildings,vehiclesandstorageandtherenewableenergysharingnetwork.Theelectricitygenerated
byPVpanelsisappliedtoprovideelectricitytobuildingsandchargebatteries/thermalenergy
storage(e.g.,byheatpump(HP)),whileEVscanbechargedatresidentialchargingstationsorat
publicchargingstationsinprivatebusinessorpubliccarparks.TheassociatedS2BVSsystem
architectureandmodelsareproposed,andtheassociatedadvancedcontrolsintheexistingliterature
arereviewed.Theaimistohelpimprovethesolarmobilityconceptbyintroducingup‐to‐dateS2BVS
models,toenhancerenewableenergyutilization,reducethedependenceandimpactsofbuildings
andEVsonthepowergrid,andreducethecarbonemissionsinresponsetoafuturescenariowith
increasedPVcapacity,EVnumbersandstoragecapacity.Themajorcontributionsofthisrevieware
summarizedasfollows:
•Assessvalues,problemsandchallengesofsolarpowerdeploymenttopromotesolarmobility.
•Extendtheexistingsolar‐to‐vehicles(S2V)concepttosolar‐to‐buildings,vehiclesandstorage
(S2BVS)withtheintegrationofrenewableenergysystems,buildings,energystoragesystems,
EVsand,moreimportantly,therenewableenergysharingnetwork.
•Identifytheresearchgapsthatneedfutureinvestigationtopromotesolarpowerutilizationand
solarmobility.
2.OverviewoftheExistingStudiesonSolarMobility
Extensiveeffortshavebeendevotedtopromotingsolarmobility,andmanypapershavebeen
publishedregardingthistopic.Figure2definestheextendedscopeofsolarmobility(comparedwith
Figure1)andhighlightsthelocationofreviewsforeachsub‐system.Table1summarizesthemain
existingstudieswithsuchascope.


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Table1.Summaryoftheexistingstudiesonsolarmobility.
AuthorsRegion
System
ModelingToolsMainWorkDoneSpecialPoints
BuildingPVStorageEVsOther
Techniques
Bertholdetal.,
(2011)[42]FranceYYNYWind
energy—
Developedageneralcontrolstrategywhichaimsat
minimizingthebuilding’stotalenergycostsby
optimizingthecharging/dischargingofPHEVs’
batteries.Theconsideredsystemsincludethepower
grid,localproductionfromrenewables,andvehicles.
UsingtheEVbatterytopowerhomeappliancesis
allowed.
Unlikeconventionalhome‐to‐
vehicle(H2V),thisstudyalso
enablesvehicle‐to‐home
(V2H)fordemandresponse
control.
Querinietal.,
(2012)[43]
Germany,
Denmark,
Sweden,
Spain,France,
UK,Italy.
NYNYWind
energyGabi4
1.Studiedthelifecycleofgreenhousegas(GHG)
emissionslinkedwithEVsusingPVandwind
electricityindifferentregionsofEuropeancountries.
2.AnalyzedthelifecycleofGHGemissionsusing
windenergy,solarenergy,andconventionalfossil
fuel.
WhenusingPVelectricity,
GHGemissionsarealways
lowerthanconventional
thermalvehicles
Zhangetal.,
(2012)[35]Kansai,JapanNYNYHeatpump
(HP)
VisualStudio
C#.net2008
1.Developedanhour‐by‐hoursimulationmodelto
deriveareal‐timesupply–demandbalance.2.
EvaluatedtheimpactsofintegratingPVpowerinto
futureelectricitysystemswithEVsandHPsunder
smartcontrolstrategiesinKansai.3.Analyzedasetof
scenarioswithdifferentpenetrationsofPV,EVand
HP.
TheEVsareconsideredas
virtualbatteries,similarto
electricitystoragesystems,
whichcannotonlybe
chargedbygridpower(G2V),
butcanalsodischarge
electricitytothepowergrid
(V2G).
Dallingeretal.,
(2013)[44]
Germanyand
U.S.
(California)
NYNYNPowerACE
1.Developedamethodtocharacterizethefluctuating
electricitygenerationofrenewableenergysourcesand
comparethedifferencebetweenCaliforniaand
Germany.2.Analyzedthepotentialcontributionof
grid‐connectedvehiclestobalancethegenerationfrom
renewableenergysourcesfora2030scenarioin
CaliforniaandGermanybasedonthedeveloped
method.
1.Correlationbetween
renewableenergysystem
generationandtheloadcurve
affectingtheintegrationof
RES.2.EVsplayanimportant
roleinreducingresidualload
fluctuationifsmartcharging
isused.
Suetal.,(2014)
[45]Illinois,U.S.NYYYWind
energy
CPLEX+Matlab+
OpenDSS
1.Formulatedastochasticproblemformicrogrid
energyscheduling,whichaimsatminimizingthe
expectedoperationalcostofthemicrogridandpower
lossesbyoptimallydispatchingtheEVchargingload
andschedulingdistributedgeneratorsanddistributed
energystoragedevices.2.Investigatedtheimpactof
EVsonmicrogridenergyschedulingundervarious
chargingschemes.
CombinedschedulingofEV
chargingloadsandenergy
storagesystems.

Sustainability2020,12,70357of37
Chaouachietal.,
(2016)[46]ItalyNYNYNMatpoweropen
sourcepackage
1.Proposedaconceptualsmartgridframeworkand
assessmentmethodology,toenabledecentralized
operationalsynergybetweenintermittentPV
generationandEVs,basedoncoordinatedEV
charging.2.Testedtheproposedmethodologywitha
realdistributionsystem,wheredifferentPVandEV
penetrationscenariosareassessedagainstcharging
behaviorvariants.
Impactsofcoordinated
chargingonPVpenetration
andcarbonemission
reduction.
Islamand
Mithulananthan
(2017)[47]
AustraliaNYNYNMatlab
1.Developedanon‐iterativePVoutputmodelthat
doesnotrequireadditionalmeasurementsor
meteorologicaldata,whichsavesmoneyandtime.2.
Developedacombined,StageofCharge(SOC)‐based,
fairchargingstrategywhichsimultaneouslyreduces
theruntimebyloweringthenumberofvariables
involvedandincreasesthechargingfairness.The
reducedruntimemakesitsuitableformorefrequent
controlofchargingofalargeEVpopulation.
Considergrid‐side
parameters,suchasvoltage
topology,structure,etc.
ThePVoutputmodeland
chargingstrategytogether
lessentheprobabilityof
voltagelimitviolationsand
enhancethePVharvest.
Sunetal.,(2018)
[48]Glasgow,UKYYYYNMatlab(GA
optimizationtool)
1.Developedamodelforminimizingtheenergycost
ofaresidentialhouseholdwithanEV,asharedenergy
storagesystem(ESS),andotherresidentialloads,
wheretheEV’susagepatternsaredescribedby
probabilitylevels.2.Conductedapracticalsurveyof
EVdailyusageincludingdrivingpurposesandusage
atdifferenttimeperiods.3.Investigatethetotalcost
savingthroughcasestudiesforvariousscenarios
underfixedandtimeofuse(TOU)tariffs.
Theoptimizationresults
basedonthismodelcanbe
usedtodeterminewhether
V2GisbeneficialforEV
ownersundertheoptimal
charginganddischarging
strategy.
Taşcıkaraoğlu
(2018)[39]
Austin,TX,
USAYYYN
Energy
sharing
network
GeneralAlgebraic
ModelingSystem
(GAMS)with
solverCPLEX
1.Developedtheconceptofenergysharing‐enabled
neighborhoodareanetworks,whicharecomposedof
asharedenergystoragesystemandmultiple
consumerpremises.2.Developedanovelenergy
managementstrategybasedontheimplementation
andschedulingtheuseofthissharedenergystorage
system(ESS)withtheobjectiveofexploitingtheESS
unitinthecontextofanenergycredit‐baseddemand
responseprogram.
Energysharing‐enabled
neighborhoodareanetworks
(NANs)forcluster‐level
performanceimprovements.
Suchenergysharingcan
reducetheenergycostsand
peakdemandsignificantly.

Sustainability2020,12,70358of37
Huangetal.,
(2019)[49]Yuxi,ChinaYYNY N
HOMER(for
demand/supply
calculation)
Matlab(forcontrol)
1.ProposedaretiredEVbattery(REVB)modelbased
onthemathematicalmodelofcapacityfadeofLi‐ion
batterycellstosimulateREVB’scapacityloss.2.
Developedapowermanagementsystemtomitigate
thedegradationofREVBandprotectothersystem
components.3.Constructedatri‐objective
optimizationmodelconsideringreliability,energy
wasteandcost.
UseretiredEVbatteriesfor
energystorageinbuildings.
Baroneetal.,
(2019)[50]Naples,ItalyYYNYNMatlab
Proposedanovelenergymanagementsystemfor
buildingsconnectedinamicrogrid,byconsidering
EVsasactivestoragecomponentsofsuchanenergy
scheme.
SuchB2V2B(i.e.,Buildingto
vehicletobuilding)
integrationenablesrenewable
sharingamongdifferent
buildings.

Sustainability2020,12,70359of37
Intheextendedsolarmobilityscope,theenergyprosumersareequippedwiththeirown
renewableenergysystems,electricalstorage,EVsandotherelectricalappliances.Thebuildingsare
connectedinarenewableenergysharingmicrogrid,inwhichthesurplusrenewableproductioncan
bedeliveredfromonebuildingtoanother.Suchanenergysharingnetworkprovidesaplatformfor
thebuildingsinamicrogridtosharetheirsurplusrenewableenergygenerationwithotherbuildings,
thushelpingenhancetheoverallcluster‐levelperformances.Theenergysharingmicrogridisalso
connectedtothepowergrid,incasethereissurplus/insufficientcluster‐levelrenewablegenerations
andelectricityexchangeswiththepowergridareneeded.Thepowerexchangeofthebuildingcluster
withthepowergridismeteredbyadvancedmeteringfacilities.

Figure2.Scopeofsolarmobilityandthemajorsub‐systems.
2.1.PVandEVInteractionviathePublicGrid
Makinguseofthecharging/dischargingcapabilityofEVbattery,theEVscanbeusedasflexible
electricitystorageinthepowergridandinteractdirectlywiththepowergrid.Forinstance,Zhanget
al.,investigatedtheenergyandenvironmentalimpactsofintegratingPVpowerintoelectricity
systemsinKansai,Japan,undervariousscenarioswithdifferentEVpenetrationsandheatpump
capacities[35].ItwasfoundthatEVsandheatpumpswerehelpfulforkeepingmorePVpowerin
thesmartelectricitysystems.Intheirstudy,theEVswereconsideredasvirtualbatteries,similarto
electricitystoragesystems,whichcannotonlybechargedbygridpower(G2V),butcanalso
dischargeelectricitytothepowergrid(V2G).Sunetal.,investigatedtheeconomyviabilityof
dischargingEVpowerbacktothegrid,whichiscalledvehicle‐to‐grid(V2G)[48].Theydevelopeda
modelfortheminimizationoftheenergycostofaresidentialhouseholdwithresidentialloads,an
ESS,andanEVwithitsusagepatternsdescribedbyprobabilitylevels.Usingthedevelopedmodel,
theystudiedthetotalcostsavingforvariousscenariosunderfixedandtimeofuse(TOU)tariffs.
Theirstudyresultsrevealthatcertainthresholdlevelsoffeed‐intariffsareexpectedtoallowusers
benefitfromV2Gtechnology.NoussanandNeirotticomparedthreearchetypalchargingprofiles(i.e.,
home,publicandwork)evaluatedon10Europeancountriesoverfouryears,toinvestigatetheeffects
ofnationalelectricitymixesandofthetypeofcharginglocationontheaverageemissionfactorofthe
electricitysuppliedtoelectricvehicles[51].Theirstudyresultsshowthatthevariabilityrelatedto
chargingprofilesisgenerallylimited(withanaveragevariationrangeof6%)inalltheselected
countries,whileinseveralcountriesthevariabilityindifferentyearsismuchlarger(withanaverage
rangeof18%).


Sustainability2020,12,703510of37
2.2.PVandEVInteractionviatheBuildings
Besidesbeingusedforelectricitystorageinthepowergrid,theEVscanalsobeusedasflexible
electricitystoragesystemsinbuildings.Forinstance,Bertholdetal.,developedacontrolstrategy,
whichaimsatminimizingthebuilding’stotalenergycostsbyoptimizingthecharging/discharging
ofthebatteriesofplug‐inhybridelectricvehicles(PHEVs)[42].Theconsideredsystemsincludethe
powergrid,localproductionfromrenewableenergysystems,andvehicles.Unliketheconventional
controlswhichonlyenablehometoEV(H2E)powertransmission,thisstudyalsoenablesEVtohome
(V2H)powertransmission,whichextendstheutilizationofEVsintermsofthebuildingdemand
response.InordertomaximizethevalueofEVbatteries,Huangetal.,proposedaretiredEVbattery
(REVB)modelbasedonthemodelofcapacityfadingoflithiumbatterycells[49].Usingthedeveloped
REVBmodel,apowermanagementstrategy(PMS),whichconsidersmultipleobjectivesincluding
minimizingthelossofpowersupply,systemcostandpotentialenergywaste,wasdevelopedto
regulatetheenergyflowtoprotecttheREVBandothersystemcomponents.Amulti‐objective
evolutionaryalgorithm,NSGA‐II,wasusedtogeneratetheParetosetoftheoptimalsolution.The
applicationofthedevelopedmethodinaresidentialbuildingindicatesthataPV–hydrogen–REVB
hybridenergysystemisapromisingwaytoexploitREVBs’residualcapacities.Similarly,Baroneet
al.,proposedtheconcept‘Building‐to‐Vehicle‐to‐Building’(B2V2B),whichenablesthebidirectional
electricityexchangeofEVbatterieswithbuildings[50].Theyalsodevelopedanovelenergy
managementsystemforbuildingsconnectedinamicrogrid,byconsideringEVsasactive
componentsofsuchanenergyscheme.Renewableenergysources(i.e.,PV),energystoragesystems
andbidirectionalelectricityexchangewiththebuildingsandthegridweretakenintoaccount.A
highlightoftheirproposedsystemisthatPVpowersharingisenabledamongdifferentbuildingsby
applyingbidirectionalEVcharging/discharging,asshowninFigure3.Suchenergysharingcan
significantlyimprovePVpowerutilization,andthusbringeconomicandenvironmentalbenefits.
InFigure3,Case1representstheconventionalunidirectionalBuilding‐to‐Vehicle(B2V)system
operation.Here,theplug‐inEVislinkedwiththepowergridbyactingasapowerload.TheEVis
chargedthroughahomechargerandnorenewableenergysystemsandbatteriesareinstalledonsite.
Case2representsanovelconceptofbidirectionalBuilding‐to‐Vehicle‐to‐Building(B2V2B)system
operation.Theplug‐inEVislinkedwiththepowergridactingasapowerloadaswellasasource
forthehousebuilding,andasasourcefortheofficespace.Arenewableenergysystem,consistingof
PVpanels,isinstalledonsiteonthetiltedroofofthehousebuilding.Thehouseisalsoequippedwith
astationarybattery(HSB),whichcanalsofeedtheEVbattery(incaseofavailablestoredenergy,
otherwisetheEVbatteryisconventionallysuppliedbythegrid).Anadditionalnoveltyisrepresented
herebythetransfertotheoffice,throughanEVbattery,oftheelectricitypotentiallyproducedbythe
houseʹsPVpanels.TheEVbatterycanalsobechargedattheoffice,ifnecessary.Case3alsorepresents
anovelconceptofbidirectionalBuilding‐to‐Vehicle‐to‐Building(B2V2B)systemoperation,basedon
swappablebatteries.ThesystemoperationfollowsthatofCase2.ThedifferencewithCase2liesin
thebatteries;specifically,inCase3thehouseisequippedwithabatteryidenticaltotheEVoneand
aquickswapofbatteriesisallowedbetweentheEVandthehouse.Theswappingoptionprevents
theneedforenergytransferfromtheHSBtotheEVbattery(whenEVbatterychargeisrequired),
andthusrelatedlosses.Case4representsadifferentnovelconceptofbidirectionalV2Bsystem
operation.ThemaindifferencewiththepreviousCases1and2isrelatedtothesiteofthePVpanels,
whichareinstalledonthefaçadeoftheofficespace,wherenodedicatedbattery(i.e.,HSB)is
considered(solarenergyisstoreddirectlyintotheEVbattery).Theplug‐inEVcommunicateswith
thepowergrid,acting,inthiscase,asapowerloadaswellasasourcefortheofficespace,andasa
sourceonlyforthehousebuilding.InCase4,thenoveltyisrepresentedbythepossibletransferto
thehouse,throughanEVbattery,ofelectricityproducedbytheoffice’sPVpanels.TheEVcanbe
chargedbothatthehouseandofficebuildings.

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Figure3.Fourdifferentmethodsofbuilding–electricvehicle(EV)–solarphotovoltaics(PV)–grid
integration[50].
2.3.PVandEVInteractionviatheEnergySharingNetworkConsideringBuildingsandEnergyStorage
Inadditiontomakinguseoftheflexibilitycharging/dischargingcapabilityofEVstoenable
energysharing,amoredirectway(i.e.,micropowergrid)canalsobeusedforalargeamountof
energysharing.Forinstance,Taşcıkaraoğludevelopedasystemstructureforasharedenergystorage
system(ESS)inaneighborhoodcommunity,asshowninFigure4[39].Intheirstudy,eachbuilding
isequippedwithatopPV‐baseddistributedgenerationsystemandisconnectedtoasharedESS.The
sharedESS,thetransformerandallthehouseholdsareconnectedtoacommonpoint,whichisnamed
thepointofcommoncoupling(PCC).Bi‐directionalpowerflowisenabledbetweenPCCandthe
powergridviaaneighborhoodtransfer,betweenPCCandthesharedESS,andalsobetween
buildingsandPCC.Suchsystemconfigurationmakesthreetypesofpowerexchangeavailable,i.e.,
internallocalpowerexchangesamongtheneighborhoodbuildings,powerexchangesbetweenthe
neighborhoodbuildingsandthegrid,andpowerexchangesbetweenthesharedESSand
grid/neighborhoodbuildings.Inotherwords,thepowerconsumedbyabuildingcanbeproduced
byitsPVsystem,beproducedlocallybythePVsystemofotherbuildingsand/orbedrawnfromthe
powergrid/sharedESS.TheEVs’chargingloadisconsideredasanormalelectricityloadinthisstudy.
BysharingtheESS,thebuildingscandelivertheirsurplusrenewableenergytootherbuildingswith
insufficientsupply,thusincreasingtheoverallrenewableself‐utilizationratesand,meanwhile,
reducingtheinteractionswiththepowergrid.Theirstudyresultsshowthatsharedstoragecanhelp
decreasethepeakelectricitydemandofabuildingclusterbyasmuchas30%and,meanwhile,reduce
theelectricitycostsofthebuildingclusterbyover10%.However,theinvestmentinasharedESS
withalargecapacitywillbemuchhigherthandistributedESSwithsmallcapacities.Inaddition,the
energylossesmaybelargeduetothelongtransmissiondistancefromthebuildingstotheshared
ESS.

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
Figure4.Schemesofthesharedenergystoragesystem(ESS)unitservinganeighborhoodwith
multiplehouseholds[39].
Zhangetal.,alsodevelopedanovelstructureforpromotingsolarmobilityinresidential
buildings,asshowninFigure5[40].Intheirstudy,eachresidentialbuildinghasamicrogrid,which
connectstheelectricityproductionfacilities(e.g.,PVpanels)andelectricityconsumptiondevices(e.g.,
lighting,washingmachine,EVs,etc.).TheEVsareusedforflexibleelectricitystoragewhichcanbe
chargedbythePVsystem/gridelectricityinperiodswithsufficientsupplyordischargepowerto
buildings/thepowergridinperiodswithinsufficientsupply.Anaggregatorisutilizedtoconnect
multiplemicrogrids,whichcoordinatestheenergysharingamongdifferentmicrogridsaswellas
theirinteractionswiththepowergrid.Basedonthedevelopedsystemstructure,theydevelopeda
two‐stagecontrolmethodtocontroltheEVcharging/dischargingratesaswellastheenergytrades
withinthemultiplemicrogridsandwiththepowergrid.Comparedwiththeconceptproposedby
Baroneetal.[50],whichusesEVbatterieswithlimitedcapacityasthemediumforenergysharing
amongdifferentbuildings,Zhangetal.’sdevelopedstructureismuchmoreflexibleandenables
largeramountofenergysharing.However,thestochasticchargingbehaviorofEVs,theintegration
ofthermalenergystoragesystemsanddynamicelectricitypricesarenotconsideredintheirstudy.
Moreover,theinitialcostsforconstructingsuchmicrogridwouldbehigh,whichmaycreateahurdle
forthismethod’slarge‐scaleapplication.

Figure5.Thestructureofmultipleresidentialmicrogrids[40].

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Similarly,Huangetal.,appliedadvancedenergyconceptsforretrofittingaresidentialbuilding
clusterinSweden[41].ThestudiedsystemincludesPVpanels(installedinindividualbuildings),
centralizedthermalenergystorage,aheatpump,andEVs.Adirectcurrent(DC)microgrid‐based
energysharingnetwork,whichisdevelopedbyFerroamp,isconstructedinthebuildingcluster.The
excessivePVproductioncanbestoredintheformofheatenergyinthethermalstoragebypowering
theheatpumptowork.Theirstudyresultsshowthatbyenablingrenewableenergysharingand
integratingenergystorageandEVs,thePVpowerself‐utilizationcanbeashighas77%inthebaseline
case.
Tosummarize,existingstudieshavedevelopedthreeapproachesfordeployingPVpowerinthe
EVs,i.e.,viapublicpowergrid,viabuildings,andviaenergysharingnetworksconsideringbuildings
andenergystorage.Amongthesethreeapproaches,thethirdapproachissuperiortotheothertwo
approaches,astheenergysharingnetworkmakestheEVchargingmoreflexible(i.e.,fromdifferent
PVpowersources)andefficient(i.e.,withenhancedPVpowerlocalusage),andallowsthe
integrationoftwootherimportantplayers(i.e.,buildingsandenergystorage)intheenergysystems.
Suchanextendedscopeofsolarmobility,withPVs,EVs,energystorage,buildings(i.e.,S2BVS),and
energysharingnetworks,isafuturedevelopmenttrend.
3.ModelingofSub‐Systems
Thissectionreviewsthemodelingtechniquesintheessentialcomponentsrelatedtosolar
mobility,includingbuilding‐sidemodeling,EV‐sidemodeling,gridmodelingandadvancedcontrol.
Designandcontroloptimizationaretwomainmeanstohelpimprovethedeploymentandutilization
ofsolarenergy.Thissectionwillreviewthesetwoaspects.
3.1.BuildingSideModeling
3.1.1.SolarResourceMapping
Thereareseveralcommercialdatabasesavailableforsolarresourcemappingsuchas
Meteonorm[52]andglobalsolarAtlas[53].Thesetoolsmakeuseofdatainputsfromgeostationary
satellitesandmeteorologicalmodelssuchasairtemperaturemodelsandclear‐skymodelstopredict
theincidentenergyonearthsurfaceatadefinedspatial–temporalresolution.Zhangetal.,carried
outacriticalreviewandcomparedvariousmodelswhichareusedtoestimatesolarirradiationon
basisoftimescaleandestimationmethods[54].Basharatetal.,compared78differentmodelsused
forglobalsolarirradiationestimation[55].Theyproposedasystematicclassificationofthesemodels
basedontheinputparameterswhichcanbeusedtodoasimilaranalysis.Thesolarresourcedata
obtainedfromvarioustoolsareoftendetachedfromsurfacetopographyandthespatialdistribution
ofthebuildingstocks.However,whileestimatingthesolarresourcepotentialinanurbancontext,it
isimportanttoconsidertheeffectofvariousobjectssuchasneighboringbuildingsontotalincident
surfaceirradiation.
Mostofthecommerciallyavailabledatabasesdonotconsidertheeffectofurbanclimateonthe
solarresources.Theatmosphericthermodynamicsinanurbanclimateareaffectedbyseveralfactors
suchastopography,shadingobjects,vegetation,urbaninfrastructureandtheheatislandeffect[56].
Thesimulationofanenergysystembasedonaweatherdatabase,whichdoesnotconsiderthese
factors,canresultinmismatchesbetweenthesimulatedandrealenergysystemperformances.To
addresssuchissues,researchershaveproposedtocouplethegeographicinformationsystem(GIS)
toolandmeteorologicaldatabasestoassessthesolarpotentialinanexistingurbancontext.For
instance,Quanetal.,proposedaGIS‐basedenergymodelingsystemfortheurbanenergycontext
whichintegratesbuildingenergymodelingandsolarresourcemodelingusingathree‐dimensional
urbanenvironmentalengine[57].Bergamascoetal.,proposedandappliedahierarchicalprocedure
whichmakesuseofGISdata,availablesolarradiationmapsandstatisticaldataonenergy
consumption,todeterminethePVenergypotentialforanItalianclimaticlocation[58].Withthe
developmentintheavailabilityofhigh‐qualitylightdetectionandranging(LIDAR)data,thereis
significantinterestfromvariousstakeholderstointegrateurban‐scale3DmodelsandLIDARdatafor

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high‐accuracyenergypotentialestimationsontheurbanscale[59].Jochemetal.[60]proposeda
methodologyforsolarpotentialestimationinurbanclimatesusingairborneLIDARdataand3D
informationfromthepointcloud.
3.1.2.PVDesignOptimization
TheinstallationofPVarrays(e.g.,theirpositiononbuildingfacadesandtheirtiltangles)has
significantimpactsonPVpowerproduction.Existingstudieshaveinvestigatedtheimpactsofthese
factorsanddevelopedpropermethodstooptimizethem.Forinstance,Abdul‐Wahabetal.,employed
aHybridOptimizationModelforElectricRenewables(HOMER)tofindthebestPVsystemamong
15availablealternativesandthebestlocationforinstallingPVarraysforOman’sconditionsby
analyzingandcomparingtheircostsandthecarbonemissionreductions[61].Ningetal.,developed
ageneticalgorithm‐basedoptimizationmethodtodesigntheposition,tiltanglesandazimuthofPV
panels,withfactorssuchasshapesandorientationsofbuildingexteriorsandthesurrounding
obstaclesconsidered[62].
TheirmethodcaneffectivelyimprovethePVsystempoweroutputby36.1%
andreducethecapitalinvestmentperunitpoweroutputby4.5%,meanwhilesignificantlyreducing
thehumanlabor.Similarly,MagnorandSaueralsodevelopedageneticalgorithm‐based
optimizationmethodtooptimizePVsysteminstallation,includingthetiltangleandazimuthangle
ofthePVgeneratorundervariousboundaryconditions.Ullahetal.,developedamethodtooptimize
thePVtiltangleunderdifferentscenarios(fixed,seasonal,monthly,daily)forLahoreandsomeof
theothermajorcitiesinPakistan[63].Theyalsoproposedamodeltoestimatetheupper/lower
boundsofsoilinglossesandexploredthetiltangleeffectonthesoilinglossesbydoingsoiling
experiments.Shirazietal.,proposedanintegratedtechno‐economicevaluationtooltoidentifythe
mostappropriatePVinstallationfaçadesinurbanareasinTehran,Iran[64].Theyfoundthatthe
properselectionoftheanglesandbuildingfaçadesforinstallingPVpanelscouldsignificantly
increasethesolarpowerproductionandtheinternalrateofreturn.Huangetal.,developedan
iterativemethodbasedonageneticalgorithmtooptimizethecapacityandpositionsofPVmodules
attheclusterlevel,withthepurposeofmaximizingtheself‐consumedelectricityunderanon‐
negativenetpresentvalueduringtheeconomiclifetime[41].BoecklandKienbergerdevelopeda
Fourierseriesapproximation‐basedmethodforsizingagrid‐connectedPVstoragesystemto
maximizesolarenergyself‐utilization[65].
3.1.3.ElectricandThermalEnergyDemand
Theenergydemandmodelingapproachesforbuildingscanberoughlydividedintophysical
modeling[66]andstatisticalmodeling[67].Physicalmodelsaremathematicalrepresentationsofheat
andmasstransferphenomenabetweenbuildings,people,andtheenvironment.Forinstance,
Palacios‐Garciaetal.[68]developedahigh‐resolutionmodelforcalculatingtheelectricitydemand
ofheatingandcoolingappliances,consideringvariablessuchasthenumberofresidents,location,
typeofday(weekdayorweekend)anddate.In[69],amodelforsimulatinglightingpower
consumptionprofilesinSpainwasdeveloped,consideringthenumberofhouseholdresidentsand
differentiatingbetweenweekdaysandweekends.In[70],Widéndevelopedamodelforcomputing
theoccupancyandelectricityloadinSweden.Physics‐basedmodelsusuallyreporthighaccuracyat
theexpenseofhighdegreesofcomplexityanddatarequirements.Statisticalmodelsaremathematical
representationsoftherelationshipbetweenanobservedsetofhistoricalvariables.In[71],a
systematicreviewoftheregressionanalysis‐basedstatisticalmodelingapproachwasconducted.A
simpleandmultiplelinearregressionanalysisalongwithaquadraticregressionanalysiswere
analyzedandcompared.In[72],asystematicreviewofthedata‐drivenstatisticalmodelingapproach
wasconducted.Thedata‐drivenstatisticalmodelingapproachwasfurtherclassifiedintoartificial
neuralnetwork‐basedapproaches,clustering‐basedapproaches,statisticaland