System-Level Operational and Adequacy Impact Assessment of Photovoltaic and Distributed

34 Pages·2017·6.53 MB·English

energies
Article
System-Level Operational and Adequacy Impact
Assessment of Photovoltaic and Distributed Energy
Storage, with Consideration of Inertial Constraints,
Dynamic Reserve and Interconnection Flexibility
LingxiZhang1,YutianZhou1,DamianFlynn2,JosephMutale1andPierluigiMancarella1,3,*
1 SchoolofElectricalandElectronicEngineering,UniversityofManchester,ManchesterM139PL,UK;
[email protected](L.Z.);[email protected](Y.Z.);
[email protected](J.M.)
2 SchoolofElectricalandElectronicEngineering,UniversityCollegeDublin,DublinD04V1W8,Ireland;
damian.fl[email protected]
3 MelbourneSchoolofEngineering,UniversityofMelbourne,Melbourne,VIC3010,Australia
* Correspondence:[email protected]@manchester.ac.uk;
Tel.:[phone]
AcademicEditor:GianfrancoChicco
Received:1June2017;Accepted:4July2017;Published:13July2017
Abstract: The growing penetration of solar photovoltaic (PV) systems requires a fundamental
understanding of its impact at a system-level. Furthermore, distributed energy storage (DES)
technologies,suchasbatteries,areattractinggreatinterestowingtotheirabilitytoprovidesupport
tosystemswithlarge-scalerenewablegeneration,suchasPV.Inthislight,thesystem-levelimpacts
of PV and DES are assessed from both operational and adequacy perspectives. Different control
strategiesforDESareproposed,namely:(1)centralised,tosupportsystemoperationinthepresenceof
increasingrequirementsonsystemrampingandfrequencycontrol;and(2)decentralised,tomaximise
theharnessingofsolarenergyfromindividualhouseholdswhilestoringelectricitygeneratedbyPV
panelstoprovidesystemcapacityonrequest. Theoperationalimpactsareassessedbydeployinga
multi-serviceunitcommitmentmodelwithconsiderationofinertialconstraints,dynamicreserve
allocation,andinterconnectionflexibility,whiletheimpactsonadequacyofsupplyareanalysedby
assessingthecapacitycreditofPVandDESthroughdifferentmetrics.Themodelsdevelopedarethen
applied to different future scenarios for the Great Britain power system, whereby an electricity
demand increase due to electrification is also considered. The numerical results highlight the
importance of interconnectors to provide flexibility. On the other hand, provision of reserves,
asopposedtoenergyarbitrage,fromDESthatareintegratedintosystemoperationisseenasthe
mosteffectivecontributiontoimprovesystemperformance,whichinturnalsodecreasestheroleof
interconnectors. DEScanalsocontributetoprovidingsystemcapacity,buttoanextentthatislimited
bytheirindividualandaggregatedenergyavailabilityunderdifferentcontrolstrategies.
Keywords: photovoltaic;distributedenergystorage;inertia;systemadequacy;renewableenergy
sources;interconnector
1. Introduction
TheParisAgreementaimstolimitgreenhousegasemissionssubstantiallyinordertoachieve
the target of preventing global warming from being greater than 2 ◦C [1]. A substantial part of
carbonemissioniscausedbytheoperationoffossilfuelpowerplants. Therefore,societyisseeking
alternativeapproachestoprovidecleanandlowcarbonenergy. Renewablegenerationtechnologies
Energies2017,10,989;doi:10.3390/en10070989 www.mdpi.com/journal/energies
Energies2017,10,989 2of34
are recognised as one of the solutions towards a low carbon power system, while wind and solar
photovoltaic (PV) generation are seen as key technologies within the potential renewable energy
portfolioworldwide. TakingGreatBritain(GB)asanexample,duetovariousincentives,theinstalled
windandPVcapacitieshaveexceeded15and10GW,respectively,bythemiddleof2016[2],andthey
areexpectedtoreachcloseto48and34GW,respectively,by2035[3]. Thelevelisedcostsofelectricity
fromwindandsolargenerationhavedroppedbymorethan30%and80%respectivelyinthelasteight
years,whichmakesthemmoreattractivetechnologiestoachievetheambitiousemissionreduction
targets[4]. However,bothtechnologieshavecertaindrawbacks,suchasthepartialuncertaintyand
variabilityofpoweroutput,whichrequiresmoreflexibilityfromthesystemtocopewiththeirvariable
generation. Forexample,PVgenerationhassomespecificcharacteristics,suchasdiurnalavailability,
i.e.,nogenerationatnightandrapidoutputchangesatdawnandduskperiods,thatneedtobeproperly
dealtwith. AthighPVpenetrationlevels,thesecharacteristicsofPVgenerationmaythreatensecure
powersystemoperationandconsequentlyleadtorenewablegenerationcurtailment. Inthiscontext,
itiskeytobothsystemoperatorsandenergypolicymakerstodevelopafundamentalunderstanding
ofallthechallengesandpotentialbenefitsassociatedwithhighpenetrationofrenewablesinthefuture,
withregardstobothsystemoperationandsecurityofsupply. Furthermore,distributedenergystorage
(DES)technologies,suchasbatteries,arealsoattractinggreatinterestbecauseoftheirdecliningcost,
anincreasingrequirementforoperationalflexibilityandthepotentialtocomplementPVproduction.
Hence, it is also crucially important to understand and quantify to what extent DES is capable of
supportingpowersystemdevelopmentandoperationalongsidePV.
Whileextensiveresearchhasbeencarriedoutregardingtheimpactsofwindgenerationinthe
GB,muchlessattentionhasbeenpaidtoPVand,ingeneral,toitsimplicationsatthesystemlevel.
Infact,themajorityofresearchonPVhasfocussedonoptimaloperationofPVsystemseitherata
householdlevelforthepurposeofmaximisingconsumerbenefits[5,6],oratamedium/lowvoltage
levelinordertoimprovetheperformanceofdistributionnetworks(e.g.,reducinglinelosses[7]and
fluctuatingfeed-inpowerfromPVsystems[8]). However,therehavebeenonlyafewstudies[9–12]
thathaveinvestigatedanddiscussedthesystem-levelimplicationsofintegratingalargevolumeof
PVgeneration,intermsoftheoperationofanactualpowersystemandthecontributiontosecurity
ofsupply.
Morespecifically,large-scalePVinstallationscangiverisetotheso-called“duckcurve”inthe
systemnetdemand,whichwouldincreasethesystemrampingrequirementstocompensateforthe
diurnalvariabilityofPVgeneration[13]. InthecaseoftheGBsystem,thelargestreductionofnet
demandcausedbyPVgenerationhasreached7.5GWin2016,whichisequivalentto≈70%ofthe
totalinstalledPVcapacity[14]. Thisimpliesthatthe40GWPVgenerationcapacityprojectedfor2035
mightimposeanetdemandreductioncloseto28GW,withoutoperationalmeasuresinplace,which
consequentlycouldcausecriticalissuesforsystemoperation. Thisisbecauseasignificantreductionin
netdemandusuallyoccursaroundmidday(insummer)whentheunderlyingdemandhasalready
beenatarelativelylowlevel. Meanwhile,notonlyrelativelyinflexiblenuclearpowerplantswouldbe
challengedtostayonlineasbaseloadgenerators,butalsopart-loadedcombinedcyclegasturbines
(CCGT)wouldneedtobecapableofprovidingdifferentreserveservices. Consequently,theminimum
stable output of these conventional generators might substantially limit the system’s capability to
accommodatethepowergeneratedbyPVand/orwindfarms,althoughsomenuclearplantscould
beconstrainedofftoincreaserenewableenergyintegration. Itis,therefore,ofparticularinterestto
investigatehowdifferentoptions,suchasutilisingenergystorageandinterconnectors,orscheduling
methodscouldsupportsystemoperationandintegratemorerenewablegeneration. Moreover,dueto
theoperationaldisplacementofconventionalsynchronousgeneration,theoverallinertiaofthesystem
is declining significantly, which would increase the system frequency response requirement [15].
Ontheotherhand,thesurgeofsuchrequirementscouldinturncallfornewoperationalconstraintsfor
existinggeneratorstostayonlinetomaintaintheinertialevel,whichcouldinturnincreasecurtailment
ofrenewablegenerationinasystemlackingflexibility. Therefore,somepublicationshaveinvestigated
Energies2017,10,989 3of34
theflexibilitycontributionofinterconnectorsbetweenadjacentgrids[16–18]. Inaddition,different
reserve allocation methods have been discussed in order to improve the integration of renewable
energysources[19,20].Furthermore,severalmethodshavebeenproposedtoincreasesystemflexibility
andprovideancillaryservicesfromenergystorage[21–24].
In parallel to the above operational issues, it is also crucial to understand from a planning
perspectivehowPVgenerationcanprovidelong-termsecurityandcontributetoasystem’sadequacy
ofsupply. Tothisend,“capacitycredit”isaclassicmeasurementofthecontributionofatechnology
tosystemadequacy. Therehavebeenseveralstudiesfocusingonevaluatingthecapacitycreditof
PV[25–28]. However,thesestudiesgenerallydidnotenvisagespecificsituations,suchasfortheGB
system,wheretheannualpeakdemandwouldoccuronawintereveningwheninfactPVgeneration
isnotavailableatall. Hence,DESsystemscouldbecomeofgreatinteresttopotentiallyenablePV
tocontributetothesupplyatpeakdemandtimes,andthereforetosystemadequacy. Ontheother
hand,DESsystemscouldalsobecontrolledtoprovidevariousservices(e.g.,reservesandfrequency
response)tosupportsystemoperation,andatthesametime,potentially,systemcapacity. Inthislight,
itisofgreatinteresttoevaluatethecapacitycreditofcoordinatedoperationofDESandPVsystems,
aswellasthecapacitycreditofDESsystemswhenprovidingoperationalsupport.
On the above basis, the primary aims of this paper, which are also its main novelty and
contributions, are to: (i) analyse the system-level implications of high penetration levels of RES
inbothoperationalandplanningterms,whileconsideringprimaryfrequencyresponserequirements
andcontributionstakingintoaccountinertialconstraints;(ii)developadynamicreserveallocation
methodtoimprovesystemflexibility;(iii)investigatetheflexibilitycontributionfrominterconnectors
insupportofsystemoperation;(iv)assessthepotentialforDEStosupportPV-richsystemoperation
andenablePVgenerationtocontributetosystemadequacy;and(v)investigatethepotentialbenefits
from system-oriented DES operation in terms of energy and ancillary services provision beyond
PVcoordination. Totheseends,modelsofdifferentDEScontrolstrategiesinbothcentralisedand
decentralisedcontexts,dynamicreserveallocation,andinterconnectorflexibilityhavebeendeveloped
andintegratedintoamulti-serviceunitcommitmentmodeltoperformtime-seriesanalysisofsystem
operation. The system-level operational implications of PV and DES are investigated in terms of
windcurtailmentandenergyimportedfromorexportedtotheinterconnectedsystems. Furthermore,
aframeworkforassessingthecapacitycreditofDESandPVsystemsunderdifferentcontrolstrategies
isdevelopedtoinvestigatethesystem-levelimpactsonadequacyofsupply,whichincludesdefinitions
offourdifferentcapacitycreditmetricsandthecorrespondingassessmentalgorithms. Apossible
increaseinsystemdemand,duetofutureelectrificationinheatingandtransportationsectors,isalso
consideredbyusingrelevantmodelsofelectricheatpumps(EHP)andelectricvehicles(EV)in[27]
and[29],respectively.
Theremainderofthepaperisstructuredasfollows: Section2introducesmodelsthathavebeen
developedforDEScontrol,dynamicreserveallocationandinterconnectorflexibility,aswellasthe
adoptedmodelsforthemulti-serviceunitcommitmentandfutureelectricitydemand;additionally,
thecorrespondingmethodologiesutilisedforcapacitycreditassessmentarealsodescribedinSection2;
Section3presentscasestudiesfocusingonthefutureGBsystemandtheresultsaredemonstratedand
discussedinSection4. Finally,conclusionsaresummarisedinSection5. Supplementaryinformation
isalsoprovidedasanAppendixAattheendofthepaper.
2. ModelsandMethodology
2.1. FutureDemamdModelling
AbreakdownoftheexpectedresidentialelectricityconsumptioninGBuntil2035isdepictedin
Figure1[3]. Thereductioninapplianceandlightingloadsiscausedbyimprovementsintechnology
energy efficiency, while the overall increase in electricity demand is primarily due to a growth in
electricvehiclesandelectricheatpumps.
Energies2017,10,989 4of34
Energies 2017, 10, 989 4 of 35

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DF =t DCt−dAtp+dtEHP+tdEV (1)
t t t t t
2.2. SystemOperationalModel
2.2. System Operational Model
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wrehqiucihre amcceonutsnta nfodr cnoenwst irnaeinrttisa.l response requirements and constraints.
2.3. AssessmentandModellingofPrimaryFrequencyResponseRequirementswithInertialConsiderations
2.3. Assessment and Modelling of Primary Frequency Response Requirements with Inertial Considerations
The frequency variation of a system is associated with the system inertia and the mismatch
The frequency variation of a system is associated with the system inertia and the mismatch
betweengenerationanddemand,suchasduetoasuddendemandsurgeorgenerationloss.Inthiscase,
between generation and demand, such as due to a sudden demand surge or generation loss. In this
primaryfrequencyresponse(PFR)isactivatedinordertoconfinethevariationofsystemfrequencyand
case, primary frequency response (PFR) is activated in order to confine the variation of system
frequency and recover it to a normal range within a pre-set timeframe. Many publications, even
recent ones, on UC research do not consider a PFR constraint [24,32–34] or only consider a total PFR
Energies2017,10,989 5of34
recoverittoanormalrangewithinapre-settimeframe. Manypublications,evenrecentones,onUC
researchdonotconsideraPFRconstraint[24,32–34]oronlyconsideratotalPFRrequirementinstead
oflinkingthePFRprovisionraterequirementwithsysteminertiainUCoptimisation[31]. Considering
thehighpenetrationlevelofnon-synchronousRESwhichcanresultinalow-inertiasystem[35]and
the increment of the largest generation loss due to the construction of nuclear plant in the future,
bothPFRprovisionrateandfullrequirementareexpectedtohaveasubstantialincrease(however,
therequirementsforPFRcouldpotentiallybereducedifnuclearplantsareincentivisedtooperatein
part-loadedmode). Therefore,itisnecessarytoexplicitlyimplement,intheUCmodel,bothinertial
constraintsandPFRprovisionrateconstraintsinordertoaccuratelycapturetheoperationoffuture
low-carbonpowersystems.SincethePFRisassumedtobesolelyprovidedbyconventionalgenerators,
focusing on a generation loss at each simulation time step (t), the change in frequency (∆fsys) in
t+τ
sub-time-step(τ)followingagenerationloss(Ploss)atthebeginningofatimestepiscalculatedin(2),
t
sys
withcorrespondingsystemstoredrotationalenergy(E ),loaddampingrate(Dpr),systemdemand
t
level(D ),conventionalgeneratoroutput(pcon). Thesystemstoredenergyiscalculatedin(3)based
t n,t
ontheratings(pconMax, pphsMax)ofsynchronousconventionalgeneratorsandpumpedhydrostorage
n s
(PHS),theaverageratioofactivepowertoapparentpowerequipmentrating(βpf),thecorresponding
inertialconstantsforeachunit(Hcon,Hphs),andthenumberofonlineunits(Ucon,Uphs):
n s n,t s,t
2· Etsys · ∂∆fts+yτs +Dpr·D ·∆fsys = ∑(cid:104)pcon −pcon (cid:105)−Ploss (2)
fsys ∂τ t t+τ n,t+τ n,t+0 t
t+0 n∈N
(cid:34) (cid:35)
Esys = ∑(cid:0)PconMax ·Hcon·Ucon(cid:1)+ ∑(cid:16)PphsMax ·Hphs·Uphs(cid:17)−PlossMax ·Hloss · 1 (3)
t n n n,t s s s,t βpf
n∈N s∈S
Currently,threemetricsareusuallyconsideredtoassessthefrequencyresponseperformance
of a system, namely the (initial) rate of change of frequency (RoCoF), frequency nadir,
and quasi-steady-state (QSS) frequency [15]; the corresponding constraints in a unit commitment
modelarediscussedin[15]andillustratedbelowforclarity. TheRoCoFisoftenusedbygenerators
(including embedded generation) to trigger grid disconnection for self-protection in the case of
(islanding)contingencies. Therefore,itisnecessarytoconfinethesystemstoredenergyvalueabovea
certainlevel,sothatthefrequencyvariationintheinitialstagefollowing(maximumonline)generation
lossisslowerthantheRoCoFsetting. Itmustbeemphasisedthatthemaximumonlinegeneration
lossisconsideredasaconstantparameter,whichequalsthecapacityofthelargestinflexiblenuclear
plant. Althoughthelargestinfeedlossofthesystemmightactuallychange,forexampleduetofault,
scheduledmaintenanceoreveninflexibleplantshuttingdownduetolackofflexibility,inthispaper
nuclearplantsareconsideredas“must-run”unitsatfulloutput,followingthecurrentapproachby
NationalGrid. Anothermajorcontingencymightbecausedbylossofaninterconnector;however,
thisdoesnotcorrespondtothepotentiallylargestinfeedloss,astheinterconnectionGB-Francehastwo
independent1000MWcircuitsanditisunlikelytoexperienceasimultaneouslybreakdownofboth
transmissionlines. Further,thelossofahighvoltage,directcurrent(HVDC)interconnectorwouldnot
bringaboutlossofinertia,soagainthiscontingencywouldlikelyhavelessimpactthanthelossof
thelargestonlinegenerator. TherelevantconstraintbasedonRoCoFsetting(ROCOFMax)isshown
inEquation(4)withthemaximumgenerationloss(PlossMax),systemnominalfrequency(fsys)andits
t+0
correspondingunitinertialvalue(Hloss). Theprimaryfrequencyresponseprovisionraterequirement
(frr )duetothenadirconstraintispresentedin(5). Thepurposeofthisconstraintistoensurethat
t
thesystemfrequencytrajectoryliesabovethenadirsetbythesystemoperator. Thederivationdetail
ofEquation(5)isexplainedin[15]. Inthispaper,itisassumedthatthePFRissolelycontributedby
thegovernordroopresponseandnoresponsecontributionfromstaticresources(e.g.,HVDClink)
hasbeenconsidered. Td isthedeliverytimeofthePFRfromconventionalgenerators,while∆f is
db
thedeadbandbeforetriggeringofPFR.ThelastconstraintrelatingtoPFRisthequasi-steady-state
Energies 2017, 10, 989 6 of 35
Energies2017,10,989 6of34
securely take over frequency recovery. In constraint (6), the total PFR provision capacity is
ccaolncduiltaitoend. bAys thshe opwronviinsio(6n) ,raittee nmsuulrteipsltyhinatg tthhee scyosrtreemsphonasdipnrgo cduerleivdersyu ftfiimciee,n wt PitFhR thteo aresscuomveprtitohne
fthreaqt uthene ccyonbvaecnktitoona gneancecreaptotarsb lhealveev ael c(o∆nfsQtaSnStM raxa)mapft erartteh ien ftuhlel dtreapnlsoieynmt epnetrioofdP oFfR P,FaRn ddespolothyamtetnhte:
secondaryresponsecansecurelytakeoverfrequencyPrelocssoMvaxe⋅ryf.syIsnconstraint(6),thetotalPFRprovision
capacityiscalculatedbytheprovisioRnOrCatOeFmMuaxlt≥iplyingthet+c0o rrespondingdeliverytime, witht(h4e)
2⋅Esys
assumptionthattheconventiongeneratorshaveaconstanttramprateinthetransientperiodofPFR
deployment:
Δf Nadir ≥ DPplorss⋅MADXt +(Dp2rf⋅rrDtt⋅)E2ts⋅ysft+s0ys lRnOCftO+s0ysF⋅MDapxr≥⋅DPt⋅l(os2PsM·loaEssxMtsA·y2Xsfft−s+ryr0Dst⋅pErts⋅ysDt⋅Δfdb)+2frrt⋅Etsys  ((45))
(cid:18) (cid:19)
∆fNadir ≥ PlossMAX + 2frrt·Etsys ln 2frrt·Etsys (5)
Dpr·Dt (fDrrptr·⋅DTtd)2≥·fts+Pys0lossMaxf−ts+ys0Δ·DfQprS·SDMtax·(⋅PDlospsMrA⋅XD−tD pr·Dt·∆fdb)+2frrt·Etsys (6)
Since the PFR provision rfartret r·eTqdu≥irePmloessnMt aaxn−d∆ (ofnQlSiSnMea)x s·yDstperm· Dsttored energy are both variabl(e6s)
in EqSuinatcieonth (e5)P, FcRerptarionv tiesicohnnirqauteesr enqeueidre tmo ebnet aapnpdli(eodn liinn eo)rdsyesr tteom costnovreerdt ethniesr gnyona-rleinbeoatrh cvoanrsitarbalienst
iinntEo qau laintieoanr o(5n)e,,c werhtaicinh cteacnh snuibqsueeqsuneenetdlyt roedbeucaep tphleie cdominpourtdaetirotnoacl otinmvee.r tTthhei smneothno-ldin aepaprlcieodn sintr a[1in5]t
iunsteos aaldindeitairononale ,bwinhaircyh vcaanriasbulbesse qanuden ctolynrsetrdauincetst, hwehcoicmh pwuotautlidon laelatdim toe .aT shiegnmifeitchaondt caopmplpieudtaitnio[n15a]l
utismese aidndcriteiaosnea labnidn airty ivs acroianbsleeqsuaenndtlcyo nnsottr asiuntista,bwleh ifcohrw soceunldarlieoa dantoalaysseigsn. iTfihcaenretfcoorme, paunta atilotenranlattimivee
iintecrraetaivsee aapndpriotaischc oisn pserqoupeonsetldy hneorte,s uwihtaicbhle isfo drespciecnteadri iona Fniagluyrsee s2.. ITnh Eerqeufoatrieo,na n(5a),l ttehren PaFtiRv epirtoevraistiiovne
araptpe roreaqcuhirisempreonpt o(s(cid:1858)e(cid:1870)d(cid:1870)(cid:3047))h earned, wthhei cshysitsedme pstioctreedd irnotFaitgiounreal2 e.nIenrgEyq u((cid:1831)a(cid:3047)t(cid:3046)i(cid:3052)o(cid:3046)n) a(5re), tthhee oPnFlRy ptwroov visaiorinabrlaetse,
rweqhuicihre mareen tm(furtru)alalnyd dthepeesnydsteenmt sotnor eedacrho taottihonera.l eTnheerrgeyfo(rEes,y sa)na reinthiteiaol nslytattwic oPvFaRri apbrleosv,iwsihonic hraartee
t t
mreuqutuiraellmyednetp iesn udseendt oinn ethaceh UoCth etor. sTihmeurelafotere s,yasnteinmit ioaplesrtaattiiconP.F TRhperno,v tihsieo nvarlautee roefq ustioreremde nenteisrguys eids
ipnotsht-eaUssCestsoedsi manudla ateppsylisetdem too Epqeruaattioionn. T(5h)e inn, tohredvera ltuoe doeftsetromreidnee nthereg cyoirsrepsopsot-nadssinesgs ePdFRan pdraopvpisliioedn
troatEeq rueaqtuioirne(m5)enint.o Srudbersetoqudeentetlrym, itnheist hdeycnoarmreiscp roanted irnegqPuFirRempreonvt isisio unsreadt eargeaqinu iirnem theen tU. SCu mbsoedquele nantldy,
tshimisudlaytnioanmsi acrrea rtee-rreuqnu. iArefmtere na tfeiswu isteedrataigoanisn, binotthh ethUe CPFmR opdreolvaisniodns irmatue laantido nssysatreemr ein-reurnti.a Atefntder toa
fceownvietergraet itoon tsh,eb ootphtitmhealP lFeRvepl,r aosv iislliuonstrraatteeda nind Fsiygsuterems i3n aenrtdia 4t.e Tnhdet oitecroantvioenrgs eartoe ttheremoipntaimtedal wlehveenl,
athsei llduisffteraretendcein bFeitgwuereens 3suacncdes4s.iTveh eroituenradtsio fnosr atrheet esrymstienmat eodpwerhateinonthael cdoifsfte ries nscmeableletwr ethenans uac cperses-isveet
rvoauluned. sforthesystemoperationalcostissmallerthanapre-setvalue.

FFiigguurree 22.. PPFFRR ccaallccuullaattiioonn iitteerraattiioonn aapppprrooaacchh,, wwiitthh iinneerrttiiaall ccoonnssiiddeerraattiioonn..
Energies 2017, 10, 989 7 of 35
EEnneerrggieiess2 2001177,,1 100,,9 98899 77o off3 345

Figure 3. PFR provision rate requirement across a week in an iterative process.
Figure3.PFRprovisionraterequirementacrossaweekinaniterativeprocess.
Figure 3. PFR provision rate requirement across a week in an iterative process.

Figure4.Systemstoredrotationalenergyacrossaweekinaniterativeprocess.
Figure 4. System stored rotational energy across a week in an iterative process.
Figure 4. System stored rotational energy across a week in an iterative process.
22..44.. DDyynnaammiicc RReesseerrvvee
2.4. DIInny nttrraaamddiiictti iRoonensaaelrlp vpeoo wweerrs ysystsetmems,st, htehep epneentreatrtiaotnioonf oref nreewneawblaebelen eerngeyrgreys oruesroceusrcisesr eilsa trievlealtyivleolwy alonwd
tahneds ytIhsnte e tmsryasdistietsmicohn eiasdl uspclehodwedteourl iesndytes tgtoerm aitnset, eatglhlrera etpnee eanwlela trrbealnetieogwnen aoebfrl aert eigonenenw.eIranabtaliedo dnei.nt iIeonrng a,ydc erderitstaiooiunnr,vc oceeslur itmsa iernse lvoafotilsvupemilnyen sli onowgf
asapnniddn snttihaneng ds ayinnsgtde rmsets aeinsr dvsiecnshgea drreeusrleeerdqv uetiosr eaidnrette orgedrqaeutaeil raweldli trtheont hdeeewasalu bwdledi teghne tnlhoeers asstuoiodfndp.eo Inwn leaordspsd lioatnfi otpsno,a wcneedrrt taphielna unvntoscl euarnmtdaei snt htoyef
ausnpndicnevnratiarniigan btayinl iadtyn sdot favntahdreiinaubgni dlrieteysrel yorvifn etgsh eda reuemn rdaeneqdrulyiarinenddg rtdeoen mdeweaanal bdwl eaitnehnd et hrregeny sesuwoduadbreclnee s el.onTsehsr igosyf“ spstooauwtircec”re ssp.e lcTaohnnitsds a“arsnytdaa tnitchd”e
tsueernctcoiaenrrdytaarirneyst year avnnedsd rtveeqartruiiaiarrbeyim lirteyens toe(rfR vteih,tse) irusenqodufteierrnleymcianelgnc utd lea((cid:1844)mte(cid:3036)da,(cid:3047)n)b dai ssa enoddfto ernnen thceaewlmcauballxaeti meednu embrgacysoe sndov uoernnct eitosh.n eTa lhmgisea nx“seimtraauttiomcr”
ccsaoepncaovcneindtytair(oyPn laoasls ngMdeax n)te,erfraottiroaerrcy ac satrpeedascedirtevyme (s(cid:1842)a n(cid:3039)r(cid:3042)de(cid:3046)q(cid:3046),(cid:3262)uw(cid:3276)i(cid:3299)irn)e,dm foaernnedtc as(so(cid:1844)tleadr) doiuesm tpoaufntte,dna, nwcdainlsctdua nlaandtdeadr sd obdlaaersv eoidaut tioponnu to,t fhatenh dem sdataexmnimdaanurdmd,
(cid:3036),(cid:3047)
wdcoeinvndivaetaninotndio sonofa llta hgreef nodereremactaaosnrt dce,ar prwoaircnsidt(y δa D(n(cid:1842)/d(cid:3039)W(cid:3042) (cid:3046)s/(cid:3046)oS(cid:3262)l)(cid:3276)a,(cid:3299)ra) s,f ofsorheroeccwaasnst teeinrdr Eodrqesum (a(cid:2012)at(cid:3005)ino/d(cid:3024)n, /w((cid:3020)7)i),n [ad3s6 as,3nh7do] w.soTnlh aiern ofEouqrteupcauattsi,to anenr d(r7o s)r ts[a3on6fd,3Pa7rV]d.,
wTdhienevd ifaoatrnioedcnad osetfm etharrneo ddrsae rmoefa cPnoVdn,,s iwwdeiinnreddd aatnnoddb esdofeolmalrlao fnwodrin eacgraeas tcn oeonrrrmsoidrasel rd(e(cid:2012)ids(cid:3005)t /rt(cid:3024)iob/ (cid:3020)ub)te,i oafnos .lslAohwo“wi3n-nsg i iganm nEaoq”rumrauatlielo dinsi s(at7pr)ip b[l3uie6tdi,3o7tno]..
dATeh me“ 3af-nosdriegacmansadt” s eorrrluaolrresr eoissfe rPavVpep, clwaielicdnu dlt aoat nioddn e,dmweamhniadlne d“a 3na.dr5e- s csigoomnlasrai d”reierssecedor vntoes idbceea rlfecoudllloiantwiooinrndg, e awr tnhooilcreom v“ae3lr .d5th-isseitgrfimobruaet”ci aosinst.
ecAror no“sri3do-sefirwgemdin aidn” goerrundleeerr a titosio cnao,pvbpealrsi eetdhd eo tfnoo rthedceeamisntaf eonrrdrm oraa tnoidof n wssiohnlodawr g nerneisneer[ra3vt8ieo] :nc,a blcauseladt ioonn ,t hwe hinilfeo r“m3a.5ti-osing mshao”w nis
icno [n3s8id]: ered in order to cover the f(cid:113)orecast error of wind generation, based on the information shown
in [38]: Ri,Rt ==PlPoslsoMssMaaxx++ ((cid:0)33⋅P·PVV⋅tδ·SδiS)2(cid:1)2++(3(cid:0)⋅3D·D⋅δtD·δ)2iD+(cid:1)2(3+.5(cid:0)⋅3W.5·⋅δWWt)·2δiW(cid:1)2 ((77))
However,theinsRtia,tll=edPcloaspsMaaxc+ityo(3f(⋅vPaVrtia⋅bδilSe))2re+n(e3w⋅aDbtl⋅eδeiDne)2rg+y(r3e.s5o⋅uWrtc⋅eδsiWis)i2n creasingsubstantial(l7y),
i,t t i t i t i
whichHloewadevsetro, atshieg niinfisctaanlltedin ccraepasaeciitny thoef r(evqauriiraebdlea) mroeunnewtoafbrlee seernveergwyi threlsoonugrecresti mise sicnaclreesas(ii.neg.,
SsuTbOsRtHainnotwiGaeBllvy,ew, rw,h ihcthihcehh ailsnea4sdthasl dlteeodl i av cesaripygantciimiftiycea anontf d in2(vchraerfaiuaslebl ldiene) l itvrheeenr yerewrqeaqubuilrieer edme anemenrtog)u.ynF otr reosefo xruaermsceeprslv ee,i stwh eiitnshct arlenoadnsagirnedgr
dtsieumvbeisa tstacinoatlneiasol l(fyit.,eh .we, SwhTiicOnhRd l eginae dnGseB rt,ao wt iaoh niscifhgo nhrieafcisca 4as nthteo riurnorcsrr deisaesl9ie.v3 ei%nry ft hotirem 4reeh aqnauhdire e2ad dh oaiufmraosd ufounpltlt idonfeg lritevhseeerrydv areet aqwupiitrrhee smleonentngeted).r
iFtniomr[3 ee8 xs]ac.maTlephsle e(n,i .,teht.,he S esTtmaOnaRdx aiinmrd Gu dBme, vwviaahtliiucoehn ohofaf stt hh4ee h wSoTuinOrsdR d gereelniqveuerirarytei odtinmb fyeo rawencidna sd2t hegorerunorersr iafsut 9ilo.l3 nd%,ew lfiovhrei rc4yh h roiesuqcruasi lracehumelaaetdne tdi)f.
iaFndooEr pqetuxianamtgi optnhlee(,7 td)haecta sant aprnerdeaascerhdn3 tde2de%v iionaft i[to3hn8e ]o.w f Ttihnhede nwf,o intrhedce a gmsetneaedxriaomtuiuotmpn uf otv.raeClcuoaesn tso eifdr retohrrien isgS 9Tt.hO3a%Rt tfrhoereq 4ui nhirsoetuadlr lseb dayh wweaiindnd dif’
cgaaedpnoaepcrtiaittnyigoin st,4h 8we GhdiWacthai nipsNr ecasatelicnoutnelaadlt eGidnr ii[dn3’8 s]E2. q0Tu3ha5etGino,on nt he(7eG) mrceaaenxn imrsecuaemncha rvi3oa2l%u[3e ] ,oocffo tnthhseee q wSuTienOndtRl y forterhqeecuasiysretsedtde m boymu wtipgiunhtdt.
generation, which is calculated in Equation (7) can reach 32% of the wind forecasted output.
Energies 2017, 10, 989 8 of 35
ECnoerngisesid20e1r7in,1g0 ,t9h8a9t the installed wind’ capacity is 48 GW in National Grid’s 2035 Gone Green sce8noafr3i4o
[3], consequently the system might require some 15 GW (32% of 48 GW) of conventional generation
to provide STOR to handle wind uncertainty . This would lead to a shortage of flexibility in a system
requiresome15GW(32%of48GW)ofconventionalgenerationtoprovideSTORtohandlewind
with total conventional capacity (excluding nuclear) of only 39 GW (however, reserve could be
uncertainty. Thiswouldleadtoashortageofflexibilityinasystemwithtotalconventionalcapacity
provided by other components, such as pumped hydroelectric storage, demand response and
(excludingnuclear)ofonly39GW(however,reservecouldbeprovidedbyothercomponents,suchas
interconnector, etc.). In fact, even assuming a state of the art wind forecasting technique, the system
pumpedhydroelectricstorage,demandresponseandinterconnector,etc.). Infact,evenassuminga
may experience some periods with insufficient reserve provision capability, as, for example, shown
stateoftheartwindforecastingtechnique,thesystemmayexperiencesomeperiodswithinsufficient
by the one week simulation results of GB system in Figure 5, with the installed renewable capacities
reserveprovisioncapability,as,forexample,shownbytheoneweeksimulationresultsofGBsystem
given in National Grid 2035 Gone Green scenario. More specifically, in Figure 5, there are a few
inFigure5,withtheinstalledrenewablecapacitiesgiveninNationalGrid2035GoneGreenscenario.
hours when the renewable production is higher than the system demand. Meanwhile, the total
Morespecifically,inFigure5,thereareafewhourswhentherenewableproductionishigherthanthe
requirement for frequency response and upward reserves even exceeds the headroom (“headroom”
systemdemand. Meanwhile,thetotalrequirementforfrequencyresponseandupwardreserveseven
here refers to as the sum of spare capacity of online generators for ramping up and the capacity of
exceedstheheadroom(“headroom”herereferstoasthesumofsparecapacityofonlinegeneratorsfor
standing generators, such as offline open cycle gas turbine (OCGT) and CCGT, which can achieve a
rampingupandthecapacityofstandinggenerators,suchasofflineopencyclegasturbine(OCGT)and
quick start-up to provide upward reserve. However, ramp rates have not been considered, which
CCGT,whichcanachieveaquickstart-uptoprovideupwardreserve. However,ramprateshavenot
makes the considered headroom to be the actual maximum ramp-up potential of the supply system)
beenconsidered,whichmakestheconsideredheadroomtobetheactualmaximumramp-uppotential
of the generation portfolio. If no measure has been taken, the security constraints of the supply
ofthesupplysystem)ofthegenerationportfolio. Ifnomeasurehasbeentaken,thesecurityconstraints
system may be compromised due to a lack of flexibility. Therefore it is necessary to reassess or
of the supply system may be compromised due to a lack of flexibility. Therefore it is necessary to
increase (although nuclear plants are considered as must-run units in this paper, it is also possible to
reassessorincrease(althoughnuclearplantsareconsideredasmust-rununitsinthispaper,itisalso
shut down nuclear plants and switch on more flexible plants to increase the total “online” flexibility
possibletoshutdownnuclearplantsandswitchonmoreflexibleplantstoincreasethetotal“online”
of the system) the flexibility contribution from each component to satisfy the flexibility requirement
flexibility of the system) the flexibility contribution from each component to satisfy the flexibility
of the system.
requirementofthesystem.

Figure5.ExampleofinsufficientreservecapacityduringhighPVandwindgenerationandlowload
Figure 5. Example of insufficient reserve capacity during high PV and wind generation and low load
periodinNationalGrid2035GoneGreenscenario.
period in National Grid 2035 Gone Green scenario.
TThheerreeffoorree,, aa nneeww ddyynnaammiicc rreesseerrvvee mmooddeelllliinngg mmeetthhoodd iiss pprrooppoosseedd ttoo rreelleeaassee ppaarrtt ooff tthhee ssyysstteemm
flfleexxiibbiilliittyy aatt hhiigghh rreenneewwaabbllee eenneerrggyy ppeenneettrraattiioonn lleevveellss.. FFirisrts toof falal,l lt,hteh eprporpoopsoesde drerseesrevrev emmethetohdo dis
iosnolny lyapapplpieldie dtot othteh ewwinindd reresesrevrve eccoommppoonneennt tinin EEqquuaattioionn ((77)), ,bbeeccaauussee tthhee wwiinndd ffaarrmmss aarree mmoorree
ggeeooggrraapphhiiccaallllyy ccoonncceennttrraatteedd,, ccoommppaarreedd wwiitthh tthhee PPVV ppllaannttss,, aanndd mmoosstt ooff tthheemm aarree ccoonnnneecctteedd ttoo tthhee
ttrraannssmmiissssiioonn nneettwwoorrkk,, wwhhiicchh ccaann ggiivvee tthhee ssyysstteemm ooppeerraattoorr ddiirreecctt ccoonnttrrooll oovveerr tthhee wwiinndd ccuurrttaaiillmmeenntt
bbeeffoorreehhaannddb baasseeddo onn ssyysstteemm ooppeerraattiioonnaallc coonnddiittiioonnss.. TThhee ssyysstteemm ooppeerraattoorr mmaayy ddeecciiddee ttoo ccuurrttaaiill wwiinndd
ttoo rreedduucceet thheer reesseerrvveep prorovvisiisoionnf rformomc ocnovnevnetniotinoanlagl egneenreartaotrosras nadndm miniinmimiseisteh tehoep oepraetriaotnioanlaclo scto,sot,r oitr
mit amyacyu crutaritlaiwl winidnda sasa al alaststr reessoorrttt too aavvooiidd iinnffeeaassiibbllee sscchheedduulliinngg aass mmeenntitoionneedd aabboovve edudeu etot oa laaclakc okf
oflfeflxeibxiilbitiyli.t yT.hTe hoeuotpuutpt uotf owfinwdin fdarfmarsm ((cid:1875)s()w tth)atth caatnc abne bseecsuerceulyre ilnyteingtreagterdat eisd ciaslccuallactuelda tbedasbedas oend tohne
(cid:3047)
twheinwdi fnodrefcoarsetc pasottepnottieanl otiualtpouutt p((cid:1849)ut)( aWntd) atinmdet-iamheea-adh ceuardtaciulmrteaniltm ((cid:2033)en)t i(nω Et)qiunaEtiqouna (t8i)o. nIn(s8t)e.aIdn sotfe audsinogf
(cid:3047) (cid:3047)
uthsien gwtihnedw foinredcfaosrte coausttpouut tptou tcatolccuallactuel athteet hseecsoencdonardya raynadn dtetretriatirayr yrereseservrvees srreeqquuiirreemmeenntt,, tthhee wwiinndd
oouuttppuutt tthhaatt ccaann bbee iinntteeggrraatteedd iiss aapppplliieedd iinn EEqquuaattiioonn ((99)) ttoo ddeetteerrmmiinnee tthhee ssyysstteemm rreesseerrvvee rreeqquuiirreemmeenntt,,
Energies2017,10,989 9of34
whichwouldallowthesystemoperatortofindabalancebetweenreserveprovisionandrenewable
integrationtominimisethesystemoperationalcost:
w =W −ω (8)
t t t
(cid:113)
Ri,t = PlossMax + (cid:0)3·PVt·δiS(cid:1)2+(cid:0)3·Dt·δiD(cid:1)2+(cid:0)3.5·wt·δiW(cid:1)2 (9)
2.5. Interconnectors
Interconnectorsareakeypotentialflexibilityproviderbyimporting/exportingelectricityfrom/to
adjacentgridswhenneeded. Moreover,interconnectioncapacityisrapidlyincreasing(forexample,
GB is projected to install another 19 GW of interconnectors in addition to current 4 GW capacity
by2035[3]),whichmakesitsmodelling(andthatofneighbouringsystems)essentialinUC,andits
specificmodellingisanothernewcontributionofthispaper. Theinterconnectorsarebasedonvoltage
sourceorcurrentsourceconvertertechnologies. Withoutenteringspecifictechnicaldetailsofeach
specificinterconnectorandwithoutlossofgenerality,wemodelthedifferentinterconnectorsasone
equivalentinterconnectionelementasacombinationofgenerationanddemand. Thisisbecausewe
areprimarilyinterestedintheenergyflexibilitythatimportsandexportscancontributetothesystem.
Thenetoutputoftheinterconnectortothesystem(pint)iscalculatedwithindividualinterconnectors
t
import(pintim)andexport(pintex)flows,asin(10). Theimportandexportflowsareconstrainedbythe
l,t l,t
interconnectorcapacity(pintMAX),import/exportcapacitylimits(CLintim,CLintex )andbyitscurrent
mode(bnint)(binaryvariable,1representsimportmodeand0representsexportmode),asshownin
l,t
Equations(11)and(12)respectively. Theimportandexportflowisalsolimitedbytherampingrateof
theinterconnectorsrepresentedbyEquations(13)and(14):
(cid:16) (cid:17)
pint = ∑ pintim −pintex (10)
t l,t l,t
l∈L
pintim ≤ PintMax ·CLintim ·bnint (11)
l,t l,t
(cid:16) (cid:17)
pintex ≤ PintMAX ·CLintex · 1−bnint (12)
l,t l,t
(cid:12) (cid:12)
(cid:12)pintim −pintim(cid:12) ≤ RAMPint (13)
(cid:12) l,t l,t−1(cid:12) l
(cid:12) (cid:12)
(cid:12)pintex −pintex (cid:12) ≤ RAMPint (14)
(cid:12) l,t l,t−1(cid:12) l
2.6. DistributedEnergyStorage
HigherpenetrationlevelsofRESinthefuturewillcallformoresystemflexibility. Besidesthe
existinglargescalepumped-hydrostorage,DEScanalsobedeployedtoprovideflexibility,andmaybe
coupledwithPVpanels. ThefundamentalfunctionalityofDEScanbecharacterisedbythefollowing
parametersincludingthestateofcharge,charging/dischargingpowerrates,charging/discharging
efficiencies,maximumcharging/dischargingpowerratings,energycapacity,andminimumenergy
level. ExistingtypicalcontrolalgorithmsimplementedinDESaimtomaximisetheself-consumption
of PV generation within individual dwellings. However, with future extensive installation of
communicationinfrastructures,systemoperatorscouldbeabletocoordinatetheoperationofbatteries
toabsorbrenewablegenerationproductionandprovideancillaryservices,enablingthemtocontribute
to system operation. The following subsections thus introduce the basic models that describe the
operationofDES,thecurrentindependentcontrolalgorithmfocusingonlocalenergyconsumption,
andanintegratedcontroltomaximisethebenefitsofbatteryutilisationatthesystemlevel.
Energies2017,10,989 10of34
2.6.1. BasicModelofDES
Modelling of DES to provide energy arbitrage to support system operation is included here,
whichisdevelopedbasedonthestoragemodelin[39]. TheenergyofDES(eDES)iscalculatedin(15)
m,t
withitsinstantaneouschargingrate(pDESc),dischargingpower(pDESdc),charginganddischarging
m,t m,t
efficiency(ηDESc,ηDESdc)andthesimulationtimesteplength(∆ts).Equation(16)determinestheenergy
levelofDES(eDES),whichisconfinedwithinitsenergycapacity(EDESMax and EDESMin). Thecharging
m,t
anddischargingpowerofDESisalsolimitedbyitspowerrating(PDESMax)andcurrentstatevariable
(bnDES), whichisabinary, anduses1and0torepresentthechargingordischargingstateofDES,
m,t
asshowninEquations(17)and(18):
(cid:32) pDESdc(cid:33)
eDES−eDES = pDESc ·ηDESc − m,t ·∆ts (15)
m,t m,t−1 m,t ηDESdc
EDESMin ≤ eDES ≤ EDESMax (16)
m m,t m
pDESc ≤ PDESMax ·bnDES (17)
m,t m,t
(cid:16) (cid:17)
pDESdc ≤ PDESMax · 1−bnDES (18)
m,t m,t
2.6.2. IndependentControlStrategy
Intheresidentialsectoratahouseholdlevel,consumerswithPVpanelsontheirrooftopscan
bemotivatedtoalsoinstallDESfortheprimarypurposeofmaximisingtheself-consumptionofthe
energygeneratedbyPVpanels,forinstancetomaximisesavingsonelectricitybills;andifthereis
sparecapacityleftaftermaximisingtheself-consumption,theDEScanalsobeusedtominimiselocal
network injections to avoid voltage issues in distribution networks. Furthermore, in regions such
asGB,wheresolarPVcannotcontributetothesupplyofsystempeakdemands(usuallyinwinter
evenings),distributedDEScouldpotentiallybecoordinatedwithandsignalledbythesystemoperator
tostorethesolarenergygeneratedinthedaytimesoastosupplysystempeakdemandsintheevening
periods,leadingtoapeakclippingeffectandacontributiontogenerationcapacity. Thiscoordinated
controlaimstorepresenthowPVandDEScouldbecontrolledtodisplaceconventionalgeneration
capacity.ItisworthnotingthatthepeakclippingoperationofcombinedDESandPVpanelsistypically
onlyneededbythesystemoperatorforacertainnumberofdaysthroughoutayear,inthecaseofGB
itwillbeseveraldaysduringwinter. Insummary,consumerswithPVpanelscouldoperatetheirDES
toachievethefollowingobjectives:
• Maximisingtheirself-consumptionofsolarPVenergyatahouseholdlevel;
• Minimisingthemaximumfeed-inpowerofsolarPVatahouseholdlevel;
• ContributingtogenerationcapacitybyshiftingthegenerationfromsolarPVtosupplythesystem
demandatpeaktimes.
AstheaforementionedcontrolstrategyofDESdoesnotrecognisetheoperationofothergeneration
technologies,thiscontrolstrategyisreferredtohereas“Independentcontrol”. Figure6demonstrates
thecontrolstrategyandhowitisintegratedintotheUCmodelandcapacitycreditassessment.