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Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage

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This paper analyses the degradation that is experienced by different types of Li-ion batteries when used as home solar storage systems controlled to minimize the electricity bill of the corresponding household. Simulating the annual operation of photovoltaic (PV) residential systems with batteries at different locations was undertaken to perform the study and it uses actual consumption values and real PV production profiles, as well as validated semi-empirical ageing models of the batteries. Therefore, the work provides a realistic prognosis around the lifetime expectancies for the different Li-ion chemistries.
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Energies2020,13,568;doi:10.3390/en13030568www.mdpi.com/journal/energies
Article
LifetimeExpectancyofLiIonBatteriesusedfor
ResidentialSolarStorage
HectorBeltran*,PabloAyusoandEmilioPérez
DepartmentofIndustrialSystemsEngineeringandDesign,JaumeIUniversity,SosBaynatAvenue,
CastellódelaPlana,12071Castelló,Spain
*Correspondence:hbeltran@uji.es;Tel.:+34964728178(H.B.)
Received:21November2019;Accepted:21January2020;Published:24January2020
Abstract:ThispaperanalysesthedegradationthatisexperiencedbydifferenttypesofLiion
batterieswhenusedashomesolarstoragesystemscontrolledtominimizetheelectricitybillofthe
correspondinghousehold.Simulatingtheannualoperationofphotovoltaic(PV)residential
systemswithbatteriesatdifferentlocationswasundertakentoperformthestudyanditusesactual
consumptionvaluesandrealPVproductionprofiles,aswellasvalidatedsemiempiricalageing
modelsofthebatteries.Therefore,theworkprovidesarealisticprognosisaroundthelifetime
expectanciesforthedifferentLiionchemistries.
Keywords:LiIonbatteries;residentialPVstorage;calendarageing;cycleageing.
1.Introduction
PVtechnologyhasbecomethemostimportantpowergenerationsourceworldwideintermsof
addedcapacityperyearsince2016,overtakingwindpower,whichwastheleadingtechnologyupto
then[1].Inall,newPVinstallationsrepresentedapproximately100GWin2018,achievingan
accumulatedcapacitythatgoesbeyond500GW[2].Thisevolutionhasbeenpossiblethankstothe
hugepricedecreaseexperiencedbythisindustryduetotheeconomiesofscaleinthelastdecade.In
accordance,thecostforresidentialgridconnectedPVsystemshasworldwideaverageddropped
downtoaround1.28€/W,beingapproximately20%higherthaninEurope,where1.13€/Wcanbe
generallyfound,and30%higherthaninAustralia,wherepricesplummetedto0.95€/W[3].Thanks
toit,theresidentialmarkethasalsoexperiencedabigdeploymentofPVinstallationsmainly
envisagedforselfgeneration,whichachievesveryhighsharesoftheenergy
productionconsumptionincertainlocallowvoltagegrids(Figure1).
However,largeamountsofbehindthemetersolarinstallationsthatproducestochastically
intermittentenergycanimplystabilityproblemsatthelowvoltagegridlevel[4].Hence,new
technicalandregulatorysolutionshavetobeimplementedtoavoidrunningintotheproblemof
systematicallyhavingtocurtailpartoftheirproduction.Theintroductionofenergystorage(ES)
systems,usuallybatteries,withinthehouseholds[5–7].Batteriesforenergystorageinbuildings
havebeenaroundforalongtimeinbothstandalone(offgrid)andcommercialbackuppower
systems(UPS).However,evenwiththestillrelativelyhighcostofbatteries,theircombinedusewith
solarsystemshasalsostartedtogainmomentumoverthelastfewyears.Thisisbecausesuch
systemsnotonlyallowforreducingtheintermittencyofthelocalproduction,stabilizingthelow
voltagegrid,butalsomakeitpossibletooptimizetheenergybillfortheinstallationownersand
evenprovideextendedsupplysecurity,whichcannotbetakenforgrantedeverywhere.Inthisway,
somespecializedconsultantsindicatethatoutofthe4GWofbatterieswithan8GWhcapacitytobe
deployedgloballyin2019(withcalculationstoachieve15GWwitha44GWhcapacityin2024and
between180and420GWhin2030),morethanhalfcouldbedistributed[8],i.e.,behindthemeterPV
residentialsystemswithbatteries,alsoknownashomesolarstoragesystems.Amongthem,these
Energies2020,13,5682of18
areclearlysettospreadacrossEurope.Italyseems,inthissense,tobeconsolidatingitspositionas
thesecondlargestmarketafterGermanyandSpainiswellpositionedtodevelopitsownsizable
market,althoughthisisalwaysverydependentonthechangingpoliticalframeworkofthecountry.
FranceandtheUnitedKingdomkeepbeingpromisingmarkets,althoughtheyhavenotclearly
emergedyet[9].BeyondEurope,theUSAisaconsolidatedmarket,mainlyinstates,suchas
California,andalsoAustraliaisstartingtotakeoff.Notehow,inthelatter,thereisgreatincentiveto
storesolarenergyasthesolarfeedintariffhasbeenlatelyreducedtoaslittleas5¢perkWh
(¢—cent),whilethecosttopurchaseelectricityiscloserto30¢perkWh.Thishasbecomeadriving
forceandgreatincentivetostoresolarenergy,ratherthansendittothepowergridforlittlereturn.
Figure1.CommonwealthGamesAthleteʹsVillageinGlasgow(Scotland),bySolarTradeAssociation
(CCBYSA2.0).
Ascanbeunderstoodinsuchacontext,agreatbunchofbehindthemeterPVresidential
systemswithbatteriesarecommerciallyavailable[10]andtheyhavebeenlargelydiscussedand
analyzedintheliterature.However,mostofthepreviousacademicworksarefocusedon
optimizationsthatarerelatedtothesizingofthebatterysystem[11–13]ortomaximizingthe
economicincomeofthePVinstallations[14–17].However,fewamongthepreviousworkshave
alreadytakenthedegradationofthebatteriesduringthelifespanofthesystemintoaccount.
Degradationevolutionisveryimportantfortheeconomicanalysisofthesesystems,whicharestill
costly,asalreadyindicated,andwhoseprofitabilityisstillunderdiscussion[18].Infact,degradation
isalreadyakeyparameterintheprofitabilityanalysesofbatteriesbeingproposedinapplications,
suchasrampratecontroloflargerenewablepowergenerationplants[19,20],ancillaryservices
[21,22],energyarbitrage,andpeakshavingprovidedbylargeenergystoragesystems[23,24],and
evenforelectricvehicleintegration[25].Amongthosepublishedfortheresidentialsolarstorage
sector,somecanbehighlighted.Forinstance,theauthorsin[26]analyzetheimpactoftheinternal
batterypackcircuitdesignonthesystemoperationanditscorrespondingdegradation.Another
approachisproposedin[27]andin[28],inwhichforecastingmethodologiesareincludedto
optimizetheoperationofthesystemwiththeaimtoenhancethebatterylifetime.Finally,an
economicoptimizationofthebatteriessizingtakingintoaccounttheageingofthebatteriesis
performedin[29].However,theyuseeithersimplifiedbatterydegradationmodels[27,28]orgeneric
onesthattheyadapttodifferenttypesofbatteriesbeingvalid,evenforleadacidmodels[29].
Thisworkassumesthatthesizingandcontrolofthesystemisamaturedomainnowadaysand
itfocusesontheanalysisofdegradationthatthedifferentLiionbatteriesusedinsuchan
applicationwouldexperienceunderawiderangeofoperationalconditions.Theanalysisisbasedon
wellknownaccepteddetaileddegradationmodelsforthespecificchemistriesunderdiscussion,
whichhavealsobeenadaptedheretoactualstateoftheartcommercialbatterypacks,whichallows
forprovidingaccurateandrealisticlifetimeexpectanciesforthoseparticularchemistriesincludedin
Energies2020,13,5683of18
currentcommercialproducts.Therefore,theresultsofthisworkareavaluablereferencefor
analyzingtheprofitabilityofthesestoragesolutions.
Thestructureofthispaperisasfollows.Section2isdevotedtothedefinitionofLiion
chemistriestobeusedinresidentialPVstorage,totheintroductionoftheircorresponding
degradationmodels,andtodescribethemodeofoperationofthebatteriesthataredesignedto
minimizetheoperationalcostofthesystem.Subsequently,Section3summarizesthedegradation
resultsexperiencedbythebatteriesaccordingtooneyearlongsimulationsthatwereperformed
whileusingMATLAB®(Natick,MA,USA)andthediscussionontheexpectedlifetimeestimations.
Finally,someconcludingremarksareintroduced.
2.Methods
ThecombineduseofLiionbatterieswithsolarPVsystemsisgainingmomentum,becausesuch
systemsnotonlyallowreducingtheintermittencyofthelocalproduction,butalsoprovideaboost
inthehandlingoflocalsolargeneration 𝑃 , i.e.,increasingtheamountofselfproductionthat
becomesselfconsumed[30].Moreover,solarstoragesystemsmakeitpossibletooptimizethe
energybillfortheinstallationownersbypeakshaving[5],[24]orbyprofitingatimeofuse
electricityratestructureforenergyarbitrage[31,32].Thisis,ascoupledwithsolar,batterysystems
canstoretheexcessgenerationandallowthecustomertodispatchthestoredenergyduringpeak
loadhourswhenelectricityismoreexpensive.Inthecomingfuture(alreadyarealityinthesocalled
VirtualPowerPlants,VPP)additionalrevenuescanbepassedontothebatteryuserswhenthe
systemiscentrallycontrolledbytheVPPoperatorandtheenergythatisstoredinthebatteriesis
accordinglydispatchedtoprovidegridsupportforhomeownersthatareinterestedinsharingthe
resourcewiththeutility.
Nonetheless,amongthedifferentpotentialapplicationsthataredefinedforhomestorage
systems,thesearemainlyinstallednowadaysforenergyarbitrageandpeakshaving(alsobackup
serviceincertainlocationssuchasCalifornia).Therefore,thisworkanalyzesthelifetimeexpectancy
thatisassociatedwithtwodifferentLiionchemistrieswhenusedundersuchcontrolstrategy.Todo
so,thedifferentLiionchemistriesarereviewedinthefollowingandsomearehighlighted.The
variousdegradationmodelsusedintheanalysisarethenintroduced.Finally,theoptimization
introducedcontrollingtheoperationofthehomesolarstoragesystemispresented.Theoperationof
differenthomestoragesystems,intermsofpowerandenergyratings,willbethensimulatedinan
annualcontextatdifferentlocations(radiationpatterns)andwithindifferenthouseholds(load
patterns).
2.1.LiionBatteriesandtheirDegradationModels
Nowadays,thegenericlabelLiionbatteriescoveruptosixdifferentbatterychemistrieswhile
usingsometypeoflithiumalloyintheirelectrodes.Thesecorrespondto:LithiumCobaltOxide
(LiCoO2),LithiumManganeseOxide(LiMn2O4),LithiumIronPhosphate(LiFePO4),LithiumNickel
CobaltAluminumOxide(LiNiCoAlO2),LithiumNickelManganeseCobaltOxide(LiNiMnCoO2),
andLithiumTitanate(Li4Ti5O12).ThevariousLiionfamiliespresentdifferentpropertiesand
characteristicsasafunctionoftheirinternalstructureandcomposition[33],whichinvolvevarying
capabilitiesintermsofspecificpower(W/kg),specificenergy(Wh/kg),thermalstability,cyclability,
andperformance.Theyalsodifferincostandlifetimeexpectancy.
Dependingontheapplicationandtheassociatedbatteryrequirements,adifferentchemistry
willbeofchoice.Forhomestorageapplications,wherebatterieshavebeendefinedtobemainly
usedtomaximizethePVproductionexploitationwhilereducingtheeconomiccostoftheelectricity
consumptioninthehouseholdviaenergyarbitrageorpeakshaving,safety,andspacelimitations
aregenerallyassumedtobethemostdefiningorlimitingparameters.Inthiscontext,LiFePO4(LFP)
andLiNiMnCoO2(NMC)cellsconstitutethebatteriesbestfittingtheseconstraints,whichcanbe
confirmedbyanalyzingthedifferentmodelscommerciallyavailablenowadays,asinFigure2.
Energies2020,13,5684of18
HomeStorageSystemLiionCells
(1) LGChemRESUNMC
(2) TeslaPowerwall2NMC
(3) VartaPulse6NMC
(4) SENECHomeLi10NMC
(5) AmpereEnergySquareNMC
(6) SonnenECOLFP
(7) BYDBBOXProLFP
(8) SimpliphiPHILFP
(9) PylonUS2000LFP
(10) PowerPlusEnergyL.Pr.LFP
Figure2.ListofmainhomestoragesystemsavailableinthemarketandtypeLiioncells
implemented.
Amongthem,althoughLFPbatterieshavebeentraditionallymoreexpensivethantheNMC
ones,nowpriceshavematched.Therefore,vendorsarelookingfavorablyatthemduetotheirlackof
Cobaltasfiresafetyregulationsbecomestricter,eventhoughenergydensityisadrawbackforLFP.
Attendingtothedifferentconsiderationsintroduced,thedegradationandthelifetimeexpectancy
forthesetwochemistriesareanalyzedinthiswork.Inthissense,althoughdifferenttypesofmodels
forpredictingthelifetimeexpectanciesareavailableintheliterature[34–37],semiempiricalmodels
(equationsbasedonreallabmeasurements)areconsideredtobethebestapproachintermsof
complexityandreliabilitytradeoffinthiswork,asitisusuallyassumedinstudiesanalyzingthe
degradationoftheLiionbatteriessubjecttorealoperationscenarios[38].Mostofthesemodelstake
differenttypesofstressfactors[34,39,40]thatdegradethecellsviathesocalledcalendarcycle
(associatedtotemperatureandstateofchargeduringstandbyoperation)orcycleageing(also
associatedtotemperature,andtothenumber,depthofdischarge,andaveragestateofchargeforthe
cycles,aswellastheCrate)intoaccount[39,41,42].Amongthedifferentproposalsofsemiempirical
degradationmodels,twodifferentmodelsthatdisregardtheCratestressfactorandfocusonthe
othershavebeenusedasreferencemodels.Thisisduetothefactthatmosthomesolarstorage
systemsusuallylimitviasoftwaretheirpowerexchangecapabilitytovaluesbelow1Cthatwould
beacertainlimitbeyondwhichCratebecomesasignificantstressfactor[43,44].Thesemodels,
togetherwiththecorrespondingimprovedmodelsthatareupdatedtostateoftheartcellsforeach
ofthechemistries,areintroducedinthefollowing.
2.2.ReferenceDegradationModelforLiFePO
4
Cells
Thesemiempiricaldegradationanalysisproposalusedasreferenceorbasemodelinthiswork
toestimatethelifetimeofLFPcellsisthatsuggestedbyStroeetal.[45].Thispaper,whichwas
publishedin2014,proposesamodelthatwasdevelopedforcylindricalbatterycellsasthosefrom
SAFTBatteries,modelVL41M[46].Themodelanalyzesthelossofbatterycapacityduetoboththe
useofthebattery(cycleageing)andthepassofthetimeitself(calendarageing).Thevalueofthe
capacityreduction(C
fade
)thatisassociatedtothelatterisdefinedby:
𝐶

_

𝑇,𝑡  𝛼
_
 𝑒

 𝑡.(1)
where𝛼_and𝛽aretwoparameterswhosevaluesdependontheprecisemodelofcell
beinganalysed,Tisthetemperature(inKelvin),andtisthetime(inmonths).Moreover,the
capacityreductionthatisassociatedtotheoperation(cycling),respondsto:
𝐶

_
𝑇,𝑁𝐶  𝛼
_
 𝑒

 𝑁𝐶.(2)
where𝛼_and𝛽areagainothertwoparameterswhosevaluesdependonthemodelofcell
beinganalysed,andNCrepresentsthenumberofequivalentfullcycles,whicharecalculatedfrom
theannualevolutionofthestateofcharge(SOC)ofthebatteryregisteredwhenoperatedinahome
Energies2020,13,5685of18
storageapplication.ThisSOCevolutionisintroducedtotheRainflowCountingAlgorithm(RFC)
[47],whichiscapableofgroupingthosecycleswithanequaldepthofdischarge(DoD)andaverage
SOC.Afterwards,bymeansofthePalmgren–Minerruleandthecapacityevolutioncurvesofthe
batteriesprovidedbymanufacturers,theNCvaluecanbeobtained,assummarizedinFigure3.
Figure3.Definitionoftheequivalentnumberoffullcycles(NC)fromapartiallycycledstateof
charge(SOC)evolution.
OncetheNCaredefined,itsvalueisintroducedintoEquation(1)and(2)togetherwiththeT
valuesandthetimerangeanalysed.TheresultingCfadevaluesarecombinedtofinallyprovidethe
lifetimeestimationprognosis,inyears,bymeansofthefollowingequation:
EOL% 𝐶
𝐶
year,𝑇 𝐶𝑁𝐶,𝑇𝑦𝑒𝑎𝑟𝑠
(3)
Notehowthisequationtakesintoaccountthatbatterymanufacturersusuallydefinethe
endoflife(EOL)oftheLFPbatteriesasthemomentwhenthecapacityretainedbythecellisequal
toagivenpercentageofitsinitialcapacity(C0)that,stilldependingonthecellmodel,canrangefrom
60%to80%(70%forthecellunderanalysis).Thesolution,inyears,tothisequationistheestimated
lifetimeexpectancyforthebattery.
2.3.ReferenceDegradationModelforLi(NiMnCo)O2Cells
Thesemiempiricaldegradationmodelused,asreference,analyzingthelifetimeofNMCtype
cellsisthatproposedbySchmalstiegetal.[48].Notehow,alsointhiscase,theworkpublishedinthe
sameyear2014focusesonthebehaviorofcylindricalcells.Moreprecisely,itisdevelopedforthe
SanyoUR18650Ecell[49].Again,asfortheLFPmodel,thedegradationisanalyzedasthelossof
batterycapacityassociatedtobothcalendarandcycling.Thefirstofthemisdescribedaccordingto:
𝐶
_
𝑉,𝑇,𝑡𝛼

_
 𝑉3.15𝑒
𝑡.(4)
where𝛼_isaparameterthatdependsonthemodelofcellunderconsideration,Visthe
averagedailyvoltage(inVolts),Tisthetemperature(inKelvin),andtisthetime(indays).
Conversely,thedegradationthatisassociatedtotheuseofthebatteryiscalculatedby:
𝐶Q, Ø𝑉,∆𝐷𝑂𝐷𝛼

_
 1.8 Ø𝑉3.667∆𝐷𝑜𝐷0.1862Q.(5)
Itcanbestatedagainthat𝛼_isaparameterthatdependsonthemodelofcellunder
consideration,Qstandsforthechargethroughput(inamperehour),
Vistheaveragevoltagefor
eachcycle(inVolts),andΔDoDisthedepthofdischargeofthecycle(inrangeof0–1).Subsequently,
𝑁𝐶  𝐷%∙𝑁𝐶
𝑀𝑎𝑥
100%
𝐷% 𝑁𝑐𝑦𝑐𝐷𝑜𝐷
𝑁𝑚𝑎𝑥𝐷𝑜𝐷
𝐷𝑜𝐷100
𝐷𝑜𝐷1
RFC
Palmgren
Miner
𝑁𝐶  𝐷%∙𝑁𝐶
𝑀𝑎𝑥
100%
𝐷%
𝑁𝑐𝑦𝑐𝐷𝑜𝐷
𝑁𝑚𝑎𝑥𝐷𝑜𝐷
𝐷𝑜𝐷100
𝐷𝑜𝐷1
Energies2020,13,5686of18
theresultingCfadevaluescorrespondinglyassociatedtocalendarandcycledegradationarecombined
tofinallyprovidethelifetimeestimationprognosis(𝑦𝑒𝑎𝑟,inyears),bymeansof:
EOL% 𝐶
𝐶
year,𝑇,𝑉 𝐶𝑄,∅𝑉,∆𝐷𝑜𝐷𝑦𝑒𝑎𝑟𝑠(6)
ThisfinalequationtakesonceagainintoaccounttheEOLofthebatteriesasapercentageofits
C0,alsobeingestimatedatthe70%forthiscell,accordingtomanufacturer’sinformation.
2.4.DegradationModelsforStateoftheArtCells
Asindicated,previousdegradationmodelswerepublishedseveralyearsagoandthey
correspondtoLFPandNMCcylindricalcellscommercializedinthefirsthalfofthisdecade.Liion
cellshaverapidlyevolvedlatelyandcurrentcommercialmodelspresentextendedcapabilitiesthat
providemuchimprovedperformances,mainlyintermsoflifespanandwarranty.Thisisduetothe
improvementinboththecurrentinternaldesignofthecells(mostofthemevolvingtowardspouch
cellsfortheseapplications)andintheirarrangementwithinthebatterypacks.Inthisway,new
batterypackspresentbetterthermalmanagementandreducedinternalresistances,whichimply
lowerinternaloperationtemperaturesandreduceddegradationduetocurrentexchanges.
Amongthedifferentcommercialmodelsthatareavailableinthemarket,thisworkfocuseson
thesolutionsbelongingtotwoofthemainglobalenergystorageplayersnowadays:theBYDBBOX
ProasLFPsystemandtheLGChemRESUasNMCsystem.Forthecaseofthefirstone,BYDcomes
withoneofthebestwarrantiesonthemarket,withanestimated60%retainedcapacityafter10years
anduptoaround5100fullcycles,ifoperatedinarangeoftemperaturesbetween−10°Cand50°C.
Thiscorrespondstoanoverall23.9MWhenergythroughputcapabilityfortheBBOXPro7.5[50].
LGChem,ontheotherhand,implementsNMCpouchcellswithanestimatedminimum60%
retainedcapacityafter10yearsifbeingoperatedwithin−10°Cand45°Candforanoverall20MWh
energythroughputcapabilityforitsRESU6.5batterypack[51],whichimplies4000fullcycles.
Therefore,apartfromthepreviouslyintroducedreferencedegradationmodels,thiswork
considersothertwomodelsthatadaptthetrendingcurvesdefinedthroughEquations(1)–(6)tothe
warrantiesthataredefinedbyBYDandLGfortheircurrentcommercialproducts,BBOXand
RESU,respectively.Inthisway,theweightedeffectofthedifferentstressfactorsovertheglobal
ageingofthecellsdemonstratedbypreviousstudiesiskept,butitisupdatedtothecurrent
performancesofthecellsbeinginstalledincommercialhomestoragesystemsnowadays.Theseare
labelledasStateoftheart(SoA)modelsandtheyhavebeenvalidatedwhileusingonthefielddata
anddataprovidedbysponsorsofthestudyandprotectedbyaNonDisclosureAgreement(NDA).
ThecorrespondingvaluesforthecoefficientsofthedifferentmodelsareintroducedinTable1.
Table1.CalendarandCyclingAgingModels’CoefficientsforthedifferentBatteryTypesanalyzed.
BatteryModel𝜶𝒄𝒂𝒍
_
𝑳𝑭𝑷𝜶𝒄𝒚𝒄
_
𝑳𝑭𝑷𝜷𝒄𝒂𝒍𝜷𝒄𝒚𝒄𝜶𝒄𝒂𝒍
_
𝑵𝑴𝑪𝜶𝒄𝒚𝒄
_
𝑵𝑴𝑪
Ref.LFP
(SaftVL41M)3.087×1076.87×1050.05176 0.02715  ‐ ‐
SoALFP
(BYDBBOX)1.985×107 4.42×1050.0510 0.02676  ‐ ‐
Ref.NMC
(SanyoUR18650E)‐ ‐ ‐ ‐ 7.54×1064.081×103
SoANMC
(LGChemRESU6.5)‐ ‐ ‐ ‐ 3.02×1061.632×103
Theresultingglobaldegradationevolutions,asrepresentedascapacityfadepercentage,
togetherwiththepartialdegradationproceduresthatareassociatedtobothcalendarandcycling,
areshowninFigure4forthetwocellswithstateoftheartwarranties(thoseoftheRESU6.5and
thoseoftheBBOX7.5batterypacks).Notehowbothachievetheirwarrantypoints(retainatleast
60%ofinitialcapacity)aftera10yearoperationperiodsubjectto45°C.However,despitealso
agreeingwiththewarranty,theNMCpresentsanoverallenergythroughputof19.9MWhinthat
Energies2020,13,5687of18
period(whatwouldrepresent1.2fullcyclesperday),whiletheLFPcellsfromtheBYDbatterypack
goupuntil23.9MWh(whichwouldrepresent1.4fullcyclesperday).
Figure4.Degradationevolutionthroughout10yearsunderwarrantyconditionsforthetwo
commercialLiionbatterypacksanalyzedinthiswork.
2.5.OperationofPVSystemswithBatteries
Aspreviouslyintroduced,althoughhomesolarstoragesystemswillbepotentiallyusedfora
widevarietyofgridservicesthatwillhelpinenhancingtheprofitabilityoftheirinstallation,these
aremainlyinstallednowadaysforenergyarbitrageandpeakshaving(alsobackupincertain
locations).However,andregardlessoftheoperationgoalofthesystem,thecontrolalgorithmin
chargeofsolarstoragesystem’soperationmust,ateverygivenmoment,analyzethedifference
betweentwouncontrollablevariables(𝑃andtheconsumptionoftheloads, 𝑃)anddecidewhat
todoifthereisanexcessorashortageinpowerasafunctionofthemainoperationalgoal.Inthe
firstcase,itcaneitherchargethebattery(𝑃 0)orsellenergytothegrid(𝑃 0).Inthesecond,
itcansupplementthepowerthatisproducedbythePVpanelswithenergystored(ifavailable)or
bypurchasingfromthegrid.Inanelectricitymarketwithatimeofuseratesstructure(onpeakand
offpeakhours)thecontrolalgorithmmusttakethisdecisionbyconsideringnotonlythecurrent
momentintime,butalsotheexpectedevolutionof𝑃and𝑃.Otherwise,theimplemented
strategycouldavoidpurchasingenergyduringoffpeakhours,onlytohavetobuyitinthefuture,
duringonpeakperiods.SuchaproblemcanbeeasilyformulatedintheframeworkofModel
PredictiveControl(MPC)[52].Thisisacontrollerdesigntechniquethatisbasedonanoptimization
strategy,inwhichthefutureoutputsforagivenhorizonN,calledthepredictionhorizon,are
predictedateachinstantwhileusingappropriatemodels.Thesepredictedoutputsdependonfuture
decisionvariables,whicharecalculatedbyoptimizingadeterminedcriterionwhilefulfillingasetof
constraints.Althoughacompletesequenceoffuturedecisionvariablesiscomputed,onlythefirst
oneiseffectivelysenttothesystem,because,atthenextsamplinginstant,newinformationwillbe
available.Thisisknownasrecedinghorizon.
Fortheproblemathand,whichfocusedontheenergyarbitrage,theeconomicbalanceofthe
energyexchangedwiththegridmainlydeterminestheoptimizationcriterion.Regardingthe
constraints,thepowerbalance,includingpowersfromthePVsystem,thebattery,thegrid,andthe
loads,mustbemet;also,thestateofcharge(SOC)ofthebatterymustbekeptwithinitslimits;and,
finally,thepowerexchangedbothwiththegridandwiththebatterymustalsostaywithincertain
limits,eitherbecauseofpowerconverterslimitationsorpeakshavingstrategies.Notethat,even
though𝑃doesnotappearintheoptimizationcost,itisstilladecisionvariableanditaffectsthe
resultsbecauseoftheconstraints.
Energies2020,13,5688of18
Takingalloftheseconsiderationsintoaccount,andfollowinganapproachsimilartothatin
[53],theoptimizationproblemtobesolvedintheMPCframeworkcanbeformulatedas:
min 𝐽𝑇𝑐
𝑡𝑘𝑃
𝑡𝑘

(7)
subjectfor𝑘0…𝑁 to:
𝑃
𝑡𝑘𝑃
𝑡𝑘𝑃
𝑡𝑘𝑃
𝑡𝑘
𝐸𝑡𝑘1𝐸
𝑡𝑘𝑇𝑃
𝑡𝑘
𝐸, 𝐸
𝑡𝑘𝐸
,
𝑃, 𝑃
𝑡𝑘𝑃
,
𝑃, 𝑃
𝑡𝑘𝑃
,
where:
Tisthesamplingperiod.
𝑃
𝑡𝑘and𝑃
𝑡𝑘arethepredictionsfor𝑃𝑡𝑘and𝑃𝑡𝑘,respectively.
𝑃𝑡𝑘isthepowerexchangedwiththegridatinstant𝑡𝑘,with𝑃𝑡𝑘0when
energyispurchased.
𝑃𝑡𝑘isthepowerexchangedbythebatteryatinstant𝑡𝑘,with𝑃𝑡𝑘0when
discharging.
𝐸𝑡𝑘istheenergyavailableinthebatteryatinstant𝑡𝑘.
𝑃,and𝑃,arethelowerandupperboundsforthepowerexchangedwiththeESS.
Theseconstraintsareduetothelimitationsonthepowerconvertersand,therefore:𝑃,
𝑃,.
𝑃,and𝑃,arethelowerandupperboundsforthepowerexchangedwiththegrid
(𝑃, 𝑃
,).Thesecanalsorepresentlimitationsonaconverterorcanbeusedin
ordertoimplementpeakshaving.
𝐸,and𝐸,arethelimitsinbetweenwhichthebatterySOCmustbekept.
𝑐 
𝑐ℎ 𝑓𝑜𝑟 𝑃 0
𝑐 𝑓𝑜𝑟 𝑃 0aretheelectricityprices.𝑐changesitsvalueswiththehour
ofthedaydependingontherateperiod(onpeakoroffpeak),while𝑐isconsidered
constantand𝑐𝑐
foranygiven.
Inthiswork,thedescribedoptimizationisperformedhourly,updatingtheproblemwiththe
newmeasurementsof𝐸𝑡ateachstep,andalso 𝑃
𝑡𝑘whennewinformationisavailable.
Althoughmostoftheequationsintheaboveproblemsarelinear,suchaprobleminitscurrent
formulationisstilldifficulttosolvebecauseofthepiecewisenatureof𝑐.Thiskindoffunctions
canbedealtwithbyintroducingbinaryvariables,whichleadtoamixedintegerlinearprogram
(MILP),whichiscomputationallyprohibitivefortheproblemsize.Therefore,adifferent
formulationisproposed.Theideaistoreplace𝑃bytwonewvariables,𝑃and𝑃,forthe
caseswhenitispositiveornegative,whichyieldsthefollowingproblem:
min
𝑇𝑐
𝑡𝑘𝑃𝑡𝑘𝑐𝑡𝑘𝑃𝑡𝑘

(8)
subjectfor𝑘0…𝑁 to:
𝑃
𝑡𝑘𝑃
𝑡𝑘𝑃
𝑡𝑘𝑃
𝑡𝑘𝑃
𝑡𝑘
𝐸𝑡𝑘1𝐸
𝑡𝑘𝑇𝑃
𝑡𝑘
Energies2020,13,5689of18
𝐸, 𝐸
𝑡𝑘𝐸
,
0𝑃
𝑡𝑘𝑃
,
0𝑃
𝑡𝑘𝑃
,
𝑃, 𝑃
𝑡𝑘𝑃
,
𝑃𝑡𝑘𝑃
𝑡𝑘0,
wherethelastquadraticconstraintistheonlyonenotlinear,beingintroducedtoavoidthe
suboptimalsolutioninwhichenergyissimultaneouslyboughtandsoldfromthegrid.
Then,letusconsideranewoptimizationproblembydroppingthislastconstraintthatinvolves
𝑃and𝑃.Becauseofthestructureofthisnewproblem,itsoptimalsolutionissuchthateither
𝑃
 0or𝑃
 0.Indeed,if𝑃
 0and𝑃
 0, as c c 0,therewouldexista
newfeasiblesolution𝑃′
 𝑃

 𝑃

andP
 0 withalowervalueofthecostfunction,
rendering𝑃
and𝑃
asbeingsuboptimal.Furthermore,thenewproblem,withboththecost
functionandconstraintsdefinedaslinearfunctions,isalinearprogram(LP),whichisaconvex
optimizationproblem.Convexityimpliesthattheoptimizationalgorithmwillfind𝑃′
 and
𝑃′
 insteadofthesuboptimalsolutions.Therefore,thisnewlinearprogram(LP)canreplacethe
originaloptimizationproblem,whichachievesthesameoptimalsolutionsandiseasilysolvedwith
standardoptimizationtools.
Finally,itisimportanttoremindthat,fortheapplicationoftheMPCstrategy,prediction
models𝑃
and𝑃
areneeded.
Regarding𝑃
,itispredictedinthisworkfromthePVsystemratedpowerandefficiencyin
combinationwithirradianceforecastedvaluesdownloadedfromthemodelsavailableonlineatthe
EuropeanCentreforMediumRangeWeatherForecasts(ECMWF)[54].ECMWFproducesan
ensembleofpredictionsthatindicatethelikelihoodofarangeoffutureweatherscenarios.Forecasts
aremadewhileusingNWPmethods,whichhavegoodperformancesfordayaheadforecastsand
beyond.Theforecastspredictthenext10dayswithonehourtimesteps,andupdatedforecastsare
availableevery12hours,at12a.m.and12p.m.Thespatialresolutionoftheforecastsis0.1°forboth
latitudeandlongitude.
Ontheotherhand,giventheSouthernEuropeanlocationofthehouseholdsunderanalysis,
𝑃
isobtainedasoneofthereferenceloadprofilesdefinedbytheSpanishMinistryofIndustryfor
theresidentialsector[55].EnergyretailersintheIberianMarketusetheseprofilestobillthose
consumersnotupdatedyetwithconsumptiontelemetry,andarethereforesupposedtorepresent
theaveragetrends.Amongthevariousprofilesthataredefinedin[55],thisworkusesthat
designatedforuserswithtimeofuseelectricityrates,whicharethosethatarepronetobeeligibleby
consumerswithhomesolarstoragesystems.ThebluecontinuouslineinFigure4representsthe
annuallyaverageddailydistributionofthatloadprofile.
3.ResultsandDiscussion
TheanalysisofthelifetimeexpectancythatisofferedbythedifferenttypesofLiionbatteries
hasbeenperformedbymeansofsimulationswhileusingMATLAB®.Accordingtotheintroduced
controlalgorithm,theoperationofthehomestoragesystemproducessuccessivechangesinthe
batterySOCthatbasicallydependonthepowerbalancetobegrantedhourafterhour.Therefore,the
continuousPVproductionandthehouseholdloadvaluesstronglycharacterizetheSOCevolution.
Inthissense,withtheaimtotrytogeneralizetheresults,theoperationofthehomestorage
systemsatthreedifferentlocationsinSouthernEuropeduringuptothreeyearswasexplored(2016,
2017,2018).Thus,uptonineannualirradiancepatterns,presentingallofthemaround1500peak
sunhours(PSH)peryearonthehorizontalplane,wereavailableandevaluated.Thethreeplaces
usedforanalysiswere:alocationintheeasternpartofSpain(ontheMediterraneancoastatsea
level,labelledasA),alocationinthecentralplateau(800mabovesealevel,labelledasB),anda
Energies2020,13,56810of18
locationinthenorthernpartofthecountry(420mabovesealevel,labelledasC),respectively.With
thesamegoal,threetypesofresidentialloadpatterns,thosewhoseannuallyaveragedhourly
distributionsareintroducedinFigure5,wereanalyzed.Notehowoneofthemispractically
coincidentwiththereferenceloaddistributionmodelthatisprovidedin[55],thatofhousehold3,
whiletheothertwoloadpatternsrepresentuserswithsignificantconsumptionduringthe
mornings,household1,orduringtheevenings,household2.Alsonotethat,althoughbeing
differentlydistributedthroughouttheday,theactualstochasticconsumptionofeachofthe
householdsdayafterdayaddsuptoanoverallannualconsumptionofaround5000kWh/year.
Moreover,anactualtimeoffusetariffforresidentialconsumerspresentingdailyoffpeak
(from10pmtillnoon)andonpeak(fromnoontill10pm)hours,regardlessofthedifferentseasons
oftheyearwasimplemented.ThiscomprehendsthecostsorpricesthataresummarizedinTable2
forthepurchaseofelectricityfromthegridorfortheinjectionofpowerintoit.Notehowthe
acquisitioncostisalwayshigherthanthegenerationone.
Table2.Costs,inc€/kWh,oftheelectricityfortheresidentialelectricitytariffconsidered.
PeriodOnpeakOffpeak
Purchaseprice(c€/kWh)2211
Saleprice(c€/kWh)55
Figure5.Loaddistributionprofileforthethreehouseholdsanalyzed,andreferenceloadcurveused
asmodel.
Afterwards,simulationshavebeenrunforeachofthecombinationsexplainedabove.Inall,if
thethreelocations,thedifferentyearsavailable,andthevariousloadprofilesareanalyzedwitheach
ofthealternativehomestoragetechnologicalsolutions,i.e.,considering2kWor4kWratedPV
installationsateachhousehold,andcombiningeachofthesePVsystemswiththevariousbattery
typesanalyzed(LFP,NMC…),which,inturn,areintroducedwiththreedifferentenergycapacities
(3.3kWh,6.5kWh,and10kWh)andaroundtripefficiencyof95%,thesesumup648combinations.
NotethatthevaluesofratedpowerforthePVplantssimulatedandthethreedifferentenergy
capacityratingsaccountedforthebatteriestryingtoreflectthemostpopularPVcasesforresidential
installationsinEuropeandtheusualbatterystoragecommercialmodelsbeinginstallednowadays.
3.1.AnnualEvolutionoftheGlobalDegradation
Foreachofthecases,anannualhourlysimulationofthehomesolarstoragesystemoperation
hasbeenperformed,providingtheSOCevolutionofthecorrespondingbatterypackasmainresult.
AsexplainedinSection2.1,thedifferentSOCevolutionsthatweregeneratedforthevariousbattery
Energies2020,13,56811of18
capacitiesconsideredatagivenhouseholdinoneofthelocationsunderstudywere,inturn,
introducedintotheRFCalgorithm.Thisalgorithmreturnedthehistogramofpartial
chargedischargecyclesthatwereannuallyregisteredbythedifferentbatteriesandtheaverageSOC
levelforeachcycle.Figure6representssuchhistogramsgenerated,inthatcase,forhousehold1in
locationAwhena4kWratedPVisassumedandforeachofthethreebatterycapacitiesconsidered
(3.3kWh,6.5kWh,and10kWh).Itisimportanttonoticeinthosedepictedcyclingpatternshowthe
maximumdepthofthechargedischargecyclesis95%,limitedinthiswaybythecontrolsystemin
agreementwithmanufacturer’sindicationtoavoidexcessivedegradationofthebatterythatis
associatedwithverydeepcycles.Apartfromthismaincycle,nosignificantpartialcyclesintermsof
DoDareexperiencedbythehomestoragesystems.Mostofthepartialcyclesregisteredcorrespond
to25%andbelowDoDmaneuvers.Addingthemall,thesedonotevenachieveinnumberthe95%
DoDcycles.Therefore,homestorageapplicationscanbeconcludedtobeverymonotonousand
sortableintermsofDoDpatterns.Additionally,notehow,asthebatterycapacitygetslarger,the
numberoffullcycles(thoseof95%DoD)getssmalleranditisredistributedalongalltherangeof
partialDoDs.Thisdirectlyimpactsthecycledegradationofthedifferentbatteries.Fromthese
histograms,theamountofQ(chargethroughput)thatisexperiencedbythebatterycanbealso
estimated.Inthesameway,the
VandVvaluesrequiredforthecalculationsinequations(4)and(5)
canbederivedfromtheresultingaverageSOCprovidedbytheRFCalgorithmandfromtheSOC
evolutionitself,respectively.Thisisdonebymeansofanexperimentalequationobtainedforthe
batterypacksmeasuredinourlabthatcorrelatesthevoltageofthebatterypackwiththe
correspondingSOC.Therefore,accordingtoEquations(2)and(5),suchamethodologyisusefulin
thedegradationanalysisassociatedwiththecycling.
Figure6.Histogramforthenumberofcyclesforeachdepthofdischarge(DoD)forthreedifferent
batterycapacities.
Conversely,notbeingtheonlystressfactor,temperatureisconsideredtobethemainonethatis
associatedtocalendarageingthough.Forthecasesthatweresimulatedinthiswork,thebatteries
havebeensupposedtobestressedtocelloperationtemperaturesalwayswithinthewarrantylimits
andrangingfrom35°Cto45°Calongtheyear.Thesearedefinedforthecellsasthetemperature
thatwouldbeachievedwithinthebatterypackduringregularoperationwheninstalledindoorsat
locationswithairtemperaturesrangingfrom20°Cto32°C.Therefore,thecalendarageingofthe
batterypacksalongtheyearcanbeequallyestimatedwhileusingEquations(1)and(4).
Calendarandcycleageingundertheseoperationconditionsarebothrepresentedforthefirst
yearofoperationinFigure7forthecommercialbatterypacksfromBYDandLGChem,respectively.
Energies2020,13,56812of18
(a)
(b)
Figure7.Cycling,calendar,andtotalcapacityreductioninoneyearfora3.3kWhLiFePO4(LFP)(a)
andLiNiMnCoO2(NMC)(b)batteryoperatedatlocationAwithinhousehold1.
InagreementwiththewarrantyevolutioncurvesthatarerepresentedinFigure4,notehowthe
maindifferenceamongthebatterydegradationmodelsisdefinedbytheirresponseintermsof
calendarageing.Itcanbeclearlyobservedhow,forthesameoperationconditionsand,accordingly,
thecorrespondingsimilarcycleageing,theglobaldegradationoftheLFPbatteryismuchmore
importantthanthatofitsNMCcounterpartduringthefirstyearofoperationduetotheaccelerated
calendarageing.However,thisbehaviorbecomesmorebalancedastimegoesby,becauseofthe
relationwithtimeofbothcalendarmodels(t0.75forNMCVs.t0.5forLFP).Thiscanbeclearlydeduced
fromFigure3anditisalsoreflectedinthelifetimeestimationvaluesthatareprovidedforthe
differentchemistriesinthedifferentcasesanalyzedandsummarizedinthefollowingsubsection.
3.2.ComparativeDiscussionamongTechnologies.
Outofthe648combinationsanalyzed,justsomeofthemareintroducedfordiscussion.The
selectedcasescoverthemaindifferentoperatingscenariosandallowforextractingthemain
conclusionsfromthisstudy.Tostartwith,Table3introducesthelifetimeexpectancyresultsthat
wereobtainedinagivenhousehold(specificloadcurve)andagivenlocation(irradianceprofile)for
thefourbatterymodels:thoseintroducedinSection2.1and2.2asreferenceforLFPandNMCcells,
respectively;and,thoseintroducedinSection2.3asstateoftheart(SoA)models.Itisimportantto
noticethatthelifetimeexpectancyhasbeencalculatedassumingtheEOLisachievedwhenthe
batteryretains70%(asdefinedforthereferencecellsintheircatalogues)or60%(asdefinedby
manufacturersfortheSoAbatterypacks).Itcanbeobservedataglancehowallowingthecellsto
operateuntila40%capacityfadeoffersacertainlyincreasedlifetimeexpectancy.Therefore,
althoughthewarrantiesfrommanufacturersdefinedifferentEOLhorizonsforthevariouscells,for
thesakeofcomparison,bothhorizonshavebeenanalyzedforallofthem.
Energies2020,13,56813of18
Table3.Lifetimeexpectancyresultsforthedifferentbatteriesathousehold1inlocationA.
Modelof
Battery
PV
Power
(kW)
Battery
Capacity
(kWh)
Calendar
Ageing
EOL70%
Cycling
Ageing
EOL70%
Lifetime
Expect.
(years)
Calendar
Ageing
EOL60%
Cycling
Ageing
EOL60%
Lifetime
Expect.
(years)
LFPRef23.322.077.943.5629.4310.576.30
LFPRef26.522.827.193.7630.419.596.63
LFPRef21024.405.614.3832.577.447.59
LFPRef43.322.097.923.5729.4710.536.32
LFPRef46.522.397.623.6529.8910.126.45
LFPRef41023.406.604.0131.228.787.02
LFPSoA23.319.1210.8810.1625.5314.4717,80
LFPSoA26,520.0010.0111.0626.6913.3219.48
LFPSoA21022.027.9813.3829.3810.6223.53
LFPSoA43.319.1510.8510.2025.5614.4517.85
LFPSoA46.519.5210.4810.5326.0413.9618.55
LFPSoA41020.739.2711.8127.6712.3320.88
NMCRef23.315.0115.002.0521.6518.373.34
NMCRef26.517.5512.452.8724.8615.154.57
NMCRef21020.269.744.1928.4011.616.47
NMCRef43.315.6014.402.0722.3717.643.33
NMCRef46.517.4712.542.5724.6315.384.18
NMCRef41019.7610.253.0827.7312.284.65
NMCSoA23.317.7812.228.4925.2014.8013.48
NMCSoA26.519.9810.0211.5827.9312.0718.18
NMCSoA21022.437.5716.0230.989.0224.58
NMCSoA43.318.2711.738.4125.8014.2013.31
NMCSoA46.519.8010.2010.3727.7112.2916.19
NMCSoA41021.858.1511.5730.239.7717.75
ItcanbeconcludedfromresultsinTable3thattheSoAbatterymodelssignificantlyoutperform
theirreferencecounterparts.ThelifetimesfortheSoALFPbatteryareexpectedtobearoundthree
timesthoseofthereferencemodel,whileafourfoldrelationisregisteredbetweentheNMCmodels.
Theimprovedpropertiesofthenewbatteriesintermsofexpectedlifetimeactuallyenablethemasa
formalsolutionforresidentialstorage,whichwasunderdiscussionuntilrecentlyduetothetight
marginbetweentheirexpectedlifetimesandtheirpaybackperiods(around10years,withhighly
dependenceonthemarket).AccordingtotheresultsinTable3,newbatterydevelopmentswould
grantlifetimeexpectanciesbeyond10yearsformostofthecasessimulated,evenifonlya30%
capacityfadeisallowedtothebatterypriortosubstitution.
Whencomparingthechemistries,itcanbeobservedhowthecycleageingimpactsmoreNMC
cellsthanLFPones;thismakestheLFPbatteriesoutfitNMCmodelswhensmallbatterypacksare
implementedinthehomestoragesolution.Thisisbecausebatterieswillexperiencedeep
chargedischargecycleseverydayduetotheirlimitedcapacity.However,lifetimeexpectancies
convergeasbatterycapacitygetslarger.
Beyondthat,notehowincreasingthePVratedpowerfrom2kWto4kWdonotsignificantly
varytheexpectedlifetimewhensmallsizebatteriesareimplemented(thoseof3.3kWh).Itcan
introducea15%variationinthelifetimeifthebatterypresents10kWhthough.Thisisbecause3.3
kWhbatteriesgetregularlysaturated(profitalltheirDoD)everydayduringthenormaloperation
withanyPVinstallationbeyond2kW.Therefore,thesecannotdegradefasterduetocycling.Onthe
contrary,10kWhbatteriesdonotexperiencefulldischargedailycycleswiththe2kWsolarplant
(reducingtheircycleageing),whiletheyaremoreextensivelyprofited,intermsofcycling,withthe4
kWplant.Finally,notethat,asexpected,thelargerthebatterysizeisthelongerthelifetime
expectancyresults.ThisisduetothesamereasonjustexposedandalsoexplainedwithFigure6,as
thebatterypresentsmorecapacity,cyclesareshorter,anditsufferslessfromcycleageing.
InordertoanalyzetheimpactofthelocalPVproduction(irradiancecharacteristicsatthe
location),simulationsbothfordifferentyearsatthesamelocation(Table4)andforthethree
differentlocations(Table5)havebeencarriedoutThefirsttableintroducesthelifetimeexpectancy
thatwasobtainedfortheLFPbatterypackinstalled,inthatcase,athousehold3.Thisisanalyzed
Energies2020,13,56814of18
withannualirradiancedatafromthreesuccessiveyearsthatwereregisteredinthelocationlabelled
asA.NoteinTable4howusingagivenyearofannualirradiancedatadonotsignificantlyimpact
theprognosisintermsofexpectedlifetime.Thedeviationsareminimal.Ontheotherhand,itcanbe
observedinTable5howthedifferentirradiancepatternsregisteredatthevariouslocations,
althoughallofthemwithsimilarPSH,certainlyinfluencethelifetimeexpectancyofthebatteries.In
thiscase,variabilitycanrangefrom5%to20%,dependingonthelocationand,also,stronglyonthe
sizeofthebatteryunderanalysis.However,inanyofthecases,thebatterypackskeeppresenting
lifetimesbeyondthe10yearwarrantytimes.
Table4.LifetimeexpectancyresultsfortheLFPstateoftheartbatterypackinstalledathousehold3
analyzedwithirradiancedatafromthreesuccessiveyearsinlocationA.
Modelof
Battery
PVPower
(kW)
Battery
Capacity
(kWh)
LifetimeExp.
Irradiance’16
(Years)
LifetimeExp.
Irradiance’17
(Years)
LifetimeExp.
Irradiance’18
(Years)
LFPSoA23.318.9618.9918.64
LFPSoA26.521.9121.8021.49
LFPSoA21025.9025.8225.52
LFPSoA43.318.1518.2118.07
LFPSoA46.519.2619.1419.01
LFPSoA41022.4822.5722.42
Table5.LifetimeexpectancyresultsfortheNMCstateoftheartbatterypackinstalledathousehold
2andanalyzedatthethreedifferentlocations.
Modelof
Battery
PV
Power
(kW)
Battery
Capacity
(kWh)
LifetimeExp.
LocationA
(years)
LifetimeExp.
LocationB
(Years)
LifetimeExp.
LocationC
(Years)
NMCSoA23.313.5013.1212.93
NMCSoA26.518.5816.5915.71
NMCSoA21025.4321.4519.81
NMCSoA43.313.1512.4712.33
NMCSoA46.516.0914.9814.35
NMCSoA41018.2316.6715.68
Finally,thelifetimeanalysisoftheseLiionbatteriesistheinfluenceoftheloaddistributionor
itsvariabilityistheotherfactortotakeintoconsideration.Theresultsinthissenseareintroducedin
Table6.Thistablesummarizeslifetimeexpectanciesthatwereobtainedforboththestateoftheart
LFPandNMCbatterypackswheninstalled,forthiscase,atlocationBandforeachofthethree
householdsanalyzedwiththeircorrespondingdifferentlyhourlydistributedloads,accordingto
Figure4.NotealsoagainthattheloadprofilesthatarerepresentedinFigure4arerealand,
therefore,alsopresentdifferentvariabilitiesamongthedaysthroughouttheyear.ObserveinTable5
howthedifferentloadprofiles(batteryoperationwithinthedifferenthouseholds)implylifetime
deviationsthatarebelow10%amongthecases,andforeachofthebatteries.Therefore,theeffectof
theloadcanbeconcludedtobelowerthanthatoftheradiationonthelifetimeexpectancyanalysis.
Table6.LifetimeexpectancyresultsfortheLFPandNMCstateoftheartbatterypacksinstalledat
locationBinanyofthehouseholdsanalyzed.
Modelof
Battery
PV
Power
(kW)
Battery
Capacity
(kWh)
LifetimeExp.
Household1
(years)
LifetimeExp.
Household2
(years)
LifetimeExp.
Household3
(years)
LFPSoA23.317.6417.6817.95
LFPSoA26.518.6718.7920.13
LFPSoA21021.9922.4523.96
LFPSoA43.317.6217.6117.66
LFPSoA46.518.2818.2918.65
LFPSoA41020.7221.1622.27
NMCSoA23.313.1113.1213.66
Energies2020,13,56815of18
NMCSoA26.516.4416.5918.60
NMCSoA21020.9221.4524.28
NMCSoA43.312.5512.4712.77
NMCSoA46.514.9814.9815.62
NMCSoA41016.5516.6717.38
4.Conclusions
ThispaperintroducesthelifetimeexpectancyforfourdifferenttypesofLiionbatteries
implementedashomesolarstoragesystems.Thechemistriesanalyzedarethosethatarebeing
proposednowadaysforthiskindofapplicationbymostofthemanufacturers,i.e.,LFPandNMC
typebatteries.Foreachofthem,twotypesofcellshavebeenconsidered:cellsthatwere
commercializedinthefirsthalfofthisdecadeandstateoftheartcellsbeingusedincommercial
currentsolutions.Thefirstpresentsdegradationmodelsintheliteraturethatareusedasreference
foreachofthechemistries,whilethelatterpresentsextendedandimprovedoperationwarranties
thataretakenintoaccounttoupdateandcalibratenewdegradationmodels.Eachofthefourbattery
typeshasbeenanalyzedinvariousscenariosofloadpattern(threecasesofdistributionofthe
consumptionalongtheday),atthreedifferentlocationswiththeircorrespondingvariationsinthe
PVproductionprofile.ThisiscombinedwithtwosizesofPVinstallation(2kWand4kW)andwith
uptothreelevelsofenergystoragecapacity(3.3kWh,6.5kWh,and10kWh).Simulatingtheannual
operationofthePVresidentialsystemswithbatteriesateachofthescenariosintroducedandtaking
intoaccountbatteryoperationtemperaturesrangingfrom35°Cto45°C,dependingonthetimeof
theyear,isundertakentoperformthestudy.Theintroductioninthesemiempiricaldegradation
modelsofthebatteryoperationparameters(SOCevolutions,exchangedcurrent,voltagestandby
levels,andothers)obtainedatthesimulations,deliverslifetimeexpectanciesforthedifferent
batteriesunderthevariousscenarios.Ingeneral,itcanbeobservedhowthecycleageingimpacts
moreNMCcellsthanLFPones,whichmakesLFPbatteriesoutfitNMCmodelswhensmallbattery
packsareimplementedinthehomestoragesolution.However,asbatterycapacitygetslarger,
lifetimeexpectanciesconverge.Additionally,notethatthedegradationexperiencedforthedifferent
loadprofilesdoesnotvarysignificantly,whichimpliesthatthewarrantycanbegranted,regardless
ofthetypeofconsumer.Additionally,similarly,thelifetimeexpectancythatisobtainedatthe
differentlocationsisalsoquiteregular,whichalsoimpliesthatthewarrantycanbegrantedatany
location.Infact,noneofthecasesanalyzedprovidedlifetimesbelow10yearsbeingthebatterypack
temperatureofsimulationsalwaysbelowthatofthewarrantyforstateoftheartmodels.Neither
chargethroughputwentbeyondthatofferedinthemanufacturers’datasheets.Therefore,itcanbe
finallyconcludedthatcurrentcommercialbatterymodelspresentlifetimeexpectanciesunderreal
operationconditionsbeyondthebreakevenpointthatisestimated,dependingonthecountryand
itscorrespondingelectricitytariffs’structures,between8and12years.
AuthorContributions:Conceptualization,HectorBeltran;methodology,HectorBeltran,PabloAyusoand
EmilioPerez;software,PabloAyusoandEmilioPerez;validation,PabloAyusoandHectorBeltran;formal
analysis,HectorBeltranandPabloAyuso;investigation,HectorBeltran,PabloAyusoandEmilioPerez;
resources,PabloAyusoandEmilioPerez;datacuration,PabloAyuso;writing—originaldraftpreparation,
HectorBeltranandPabloAyuso;writing—reviewandediting,HectorBeltranandEmilioPerez;visualization,
HectorBeltran,PabloAyusoandEmilioPerez;supervision,HectorBeltranandEmilioPerez;project
administration,HectorBeltran;fundingacquisition,HectorBeltran”.Allauthorshavereadandagreedtothe
publishedversionofthemanuscript.
Funding:ThisresearchwasfundedbyUniversitatJaumeI(Spain),projectUJIB201726,andbythe
GeneralitatValenciana,projectGV2019087.
Acknowledgements:
ConflictsofInterest:Theauthorsdeclarenoconflictofinterest.
Energies2020,13,56816of18
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