Please cite this article in press as: A.A. Kida, L.A. Gallego, A high-performance hybrid algorithm to solve the optimal coordi- ContentslistsavailableatScienceDirect
Electric Power Systems Research
jou rn al h om e p a g e :w w w . e l s e v i e r . c o m / l o c a t e / e p s r
A high-performance hybrid algorithm to solve the optimal
coordination of overcurrent relays in radial distribution networks considering several curve shapes
Alexandre A. Kida
∗, Luis A. Gallego
DepartmentofElectricalEngineering,LondrinaStateUniversity,Londrina,PR,Brazil
a r t i c l e i n f o
Articlehistory:
Received22October2015
Receivedinrevisedform25May2016 Accepted30May2016
Availableonlinexxx
Keywords:
Evolutionaryalgorithm Overcurrentrelayscoordination Distributionnetworks Optimization
a b s t r a c t
Thecoordinationofovercurrentrelays(OCRs)isessentialforimprovingreliabilityandsecurityindicators inelectricalnetworks.Thispaperproposesahigh-performancehybridalgorithm(HPHA)tosolvethe optimalcoordinationofOCRsinradialdistributionnetworks(RDNs).Theoptimalcoordinationproblem isformulatedasamixed-integernonlinearproblem(MINLP).Weconsideringasdecisionvariables:(1) thepickupcurrent(Ip);(2)timedialsetting(TDS);(3)relaytype;(4)curvetype.TheHPHAiscomposed ofaspecializedgeneticalgorithm(SGA)andanefficientheuristicalgorithm(EHA).Thus,theHPHAfinds theoptimumcombinationofIp,TDS,relaytypesandcurvetypesthatminimizetherelaysoperational times,ensuringtheselectivityforseveralfaultlevels.Theproposedalgorithmconsidersdiscretevalues ofIpandTDS.Thesimulationresultsshowedthattheproposedtechniqueisefficient,fast,reliableand improvesthecoordinationbydecreasingtheoperationaltimesofOCRs.
©2016ElsevierB.V.Allrightsreserved.
1. Introduction
Theelectricalsystemisnotimmunetofailure,anditsprotec- tionhasakeyroleinthepreservationofequipment(generators, switchgears,conductors,capacitors,transformersetc.).Inaddition, it isnecessary toensuremaximumcontinuity of powersupply toconsumers.Interruptionscausedamagebothforusersandfor electricutilities.Forthese,interruptionscanmeanrevenuelosses, damagetothepowerutilityimageandfines[1].Inordertoreduce thenumberofusersaffectedbytheinterruptions,theprotection devicesmust becoordinated.Thisallowsa specificsequenceof operationswhenafaultoccurs.Themaingoalsofthecoordination aresensitivity,selectivity,reliabilityandspeed[2].
Duringafaultcondition,oneofthemainconsequencesforthe electricalsystemistheelevationofcurrentlevels.Thus,itisnatu- raltousetheselevelsasparameterstodetermineifthesystemis faulty.Themostcommondevicesinthiscategoryaretheovercur- rentrelays(OCR),fusesandcircuitbreakers.TheOCRaretypically usedasbackupprotection,butinsomecases,theymaybetheonly typeofprotectionavailable[3].Asmostofthedistributionsystems areradial,theprotectionusingnon-directionalOCRissuitableand iswidelyusedbecauseitissimple,effectiveandcheap.Thispaper
∗Correspondingauthor.Tel.:+5571991001595.
E-mailaddress:[email protected](A.A.Kida).
focusesontheinversedefiniteminimumtimeovercurrentrelay (IDMTOCR).Theserelayshavetwoparameters:pickupcurrent(Ip) andtimedialsettings(TDS).However,somerelayscanhavetheir curvetypesmodified(inverse, veryinverseetc.).Wherein,each relaytype(IEEE[4],IEC[5],IAC[6],U.S.[7]etc.)hasadifferentset ofstandardizedcurves.
Thecoordinationproblemcanbeformulatedasamixed-integer nonlinear optimizationproblem. Themain objectiveconsistsin minimizingthetotaloperationaltimesoftheprimaryrelays.These timesrelyonthevaluesofIp,TDS,curvetypesandrelaytypes.Ipis treatedasdiscretebutthevariableTDSisoftenconsideredcontinu- ous.However,someOCRdoesnothavestepsofTDSsmallenoughto betreatedascontinuous,androundingthemtothenearestpossible valuescanleadtomiscoordination[8].
TosolvetheOCRcoordinationproblem,classicaloptimization techniquesareused,suchaslinearprogramming(LP)[2,3,9]and nonlinearprogramming(NLP)[10–12].Aswellas,metaheuristics algorithms(MHAs)havebeenused.TheMHAscanfindhigh-quality solutionsand,insomecases,theglobaloptimalsolutionwithless computationaleffort[13].In[14–16,8,17]geneticalgorithms(GAs) wereusedtosolvetheOCRcoordinationproblem.In[8],theauthor solvedtheproblemwithGAandconsideredIpandTDSasdiscrete variables.In[18,19]theproblemwassolvedusingparticleswarm algorithm.In[20,21]theartificialhoneybeealgorithmswereused tosolvethecoordinationproblem.In[22,23],ahybridalgorithm thatcombinesLPandevolutionaryalgorithmswasusedtosolvethe http://dx.doi.org/10.1016/j.epsr.2016.05.029
0378-7796/©2016ElsevierB.V.Allrightsreserved.
problem.Amethodologythatoptimizeseachparameterindepen- dently,consideringdiscreteIpandTDS,wasproposedin[24].The problemwasalsosolvedusingbinaryintegerprogramming,this wayTDSandIpwereconsidereddiscrete[25].In[26]therewas anadditionofthecurvetypesasdecisionvariables.Theauthors consideredstandardizedandnon-standardizedcurvestypes.
The electrical networks encouragedthe industrial, commer- cialandtechnologydevelopment,butmostofthemareoldand nottechnologicallydeveloped.Nowadays,governmentshavebeen encouraging theelectrical utilityto make investmentsin their networkstomakethemmorereliable,safeandtechnological.This way,utilitiesaredevelopingthesmartgrids.Theseareelectrical gridsthatuseadvancedtechnologiestomonitorandactbasedon theinformationaboutthebehaviorofend-usersandgeneration sources.So,thesmartgridcoordinatestheneedsandcapabilities ofallgenerators,gridoperators,consumersandelectricitymarket stakeholders.Withtheobjectiveofoperatingallpartsofthesys- temasefficientlyaspossible,minimizingcostsandenvironmental impactswhilemaximizingsystemreliability,securityandstabil- ity[27].Inthesmartgrids,theenergycontrolcentersneedfastand reliabletechniquesorcomputationalalgorithms,tobeusedinreal- timeapplications.Hence,thereisagreatinterestofelectricutilities tousetechniquesorcomputationalalgorithmstosolveproblems intheirpowergrids.Oneoftheseproblemsistheoptimalcoordi- nationofprotectiondevicesinreal-time.Inthispaperwepropose anefficient,fastandreliablemethodologyforthecoordinationof OCRinradialdistributionnetworks(RDNs).Suchproceduresare essentialfortheoptimaloperationofthenetworks.
TheIp,TDSareusuallyconsideredasdecisionvariables.This paperconsiders theaddition of curve and relay typesas deci- sionvariables. A high-performance hybrid algorithm (HPHA) is proposedtosolvethecoordinationproblem.ThiscombinesaGA withanefficientheuristicalgorithm(EHA).TheGAisresponsible forsolvingthenonlinearoptimizationproblem,whichconsistsin determiningtheIp,relaytypesandcurvetypes.Thiswayispossi- bletofindtheoptimumTDSpossessingthesevariables.IfTDSare treatedascontinuousvariables,theproblemoffindingitsoptimal valuesislinear.Thus,LPtechniquessuchassimplex,dualsimplex, two-phasesimplexandinteriorpointsareusuallyusedtosolveit.
Inthispaper,theEHAwillbeusedinsteadofLPtechniques.Since theTDSarenotencodedinthechromosomeoftheGA,itssearch spaceisgreatlyreduced.TheHPHAalsoensuretheselectivityfor multiplefaultlevels.
Thispaperisorganizedasfollows:Section2,presentsthechar- acteristicsoftheOCRusedinthispaper.Section4,thepresents OCRcoordinationproblemasanoptimizationproblem.Section5.5 presentstheEHAforfindingtheoptimalTDS,inRDN.Section5, presentstheHPHA.Section6,presentsthetestsystemsusedinthis paper.Section7providesacriticalanalysisoftheobtainedresults.
Finally,Section8concludestheworkpresentedinthispaper.
2. Overcurrentrelaycharacteristics
The OCR operates when the input current exceeds a pre- determinedvalue(Ip),sendinga signaltothecircuitbreakerto interruptthecircuit.Thenon-directionalIDMTOCRhasanopera- tiontimethatisinverselyproportionaltotheintensityoftheinput current.Moreover,itdoesnottakeintoaccountthedirectionof thecurrentflow.OneofitsmainapplicationsisintheRDNs,where thedirectionsofthecurrentflowsarealwaysknown[28].These relayshavetheiroperationaltimes(1)determinedbyinternational standards,suchasIEEE(InstituteofElectricalandElectronicsEngi- neers)[4],IEC(InternationalElectrotechnicalCommission)[5],IAC (InverseAlternateCurrent)[6],U.S.(UnitedStates)[7]etc.Theoper- ationaltime ofa relayi(Ri)for eachk faultinside theprimary
Table1
ConstantsofcurvetypesfortheIEEErelay[4].
Curvetype A B P
E.I 28.20 0.122 2.00
V.I 19.61 0.491 2.00
M.I 0.05 0.114 0.02
Table2
ConstantsofcurvetypesfortheIECrelay[5].
Curvetype A N
I 0.14 0.02
V.I 13.50 1.00
E.I 80.00 2.00
L.I 120.00 1.00
Table3
ConstantsofcurvetypesfortheIACrelay[6].
Curvetype A B C D E
E.I 0.004 0.638 0.620 1.787 0.246
V.I 0.090 0.796 0.100 −1.289 7.959
I 0.208 0.863 0.800 −0.418 0.195
S.I 0.043 0.061 0.620 −0.001 0.022
protectionzoneofRj(Icckj)isshownin(1),anditdependsontheTDS ofRi(TDSi)andKi,jk.ThetermKi,jk varieswiththestandardofRi,and itrelatedtothevaluesofIpofRi(Ipi),Icckj andthecurveconstants relatedtothecurvetypesofRi.FortheIEEE,IEC,IACandU.S.stan- dards,Ki,jk iscomputedusing(2)–(5),respectively.Tables1–4show theconstantsrelatedtothecurvetypesfortheIEEE,IEC,IACand U.S.standards,respectively.WhereE.I,V.I,M.I,I,L.IandS.Irefer toextremely,very,moderately,standard,longandshortinverse curvetypes,respectively.
To improve the effectiveness of the protection scheme,the selectivitymustbeguaranteedforarange offaultcurrents.For selectivitypurposes,isconsideredpfaultcurrentlevelsinsideeach primary protectionzone, asshown in (6). For instance,ifp=2, theselectivityisguaranteed,foreachOCR,fortwoexpectedfault levels:theminimumandmaximum.For p>2,morefaultlevels betweentheexpectedminimumandmaximumareconsideredfor theselectivity.Eq.(7)showsthesizeofthediscretizationsteps ofthe selectivityinterval(Icckj), forfaults withintheprimary protectionofRj.
Forphase OCRs,themaximumand minimumexpectedfault currents are usually the close-in three-phase and the far-end two-phasefaults,respectively.ForgroundOCRs,theclose-inphase- to-ground and the far-end phase-to-ground(through a contact impedance) faults might be used as maximum and minimum expectedfaultcurrents.
Ti,jk =TDSi·Ki,jk (1)
Ki,jk =
Ai IcckjIpi
Pi−1
+Bi (2)
Table4
ConstantsrelatedtothecurvetypesfortheU.S.relay[7].
Curvetype A B N
M.I 0.023 0.010 0.020
V.I 0.097 3.880 2.000
S.I 0.003 0.003 0.020
I 0.180 5.950 2.000
E.I 0.035 5.670 2.000
Please cite this article in press as: A.A. Kida, L.A. Gallego, A high-performance hybrid algorithm to solve the optimal coordi- R1 R2 R3
F1 F2 F3
Fig.1.Radialsystemwiththreerelaysandtheirrespectiveprimaryprotection zones.
Ki,jk =
Ai IcckjIpi
Ni−1
(3)
Ki,jk =Ai+ Bi Icckj
Ipi −Ci
+ Di
Icckj Ipi −Ci 2+ Ei Icckj Ipi −Ci 3 (4)Ki,jk =Ai+ Bi
Icckj Ipi Pi−1
(5)
Icckj =Iccjmin+(k−1)·Icckj (6) Icckj =Iccjmax−Iccjmin
p−1 , p>1 (7)
whereTi,jk istheoperationtimeofRiforIcckj.TDSiistheTDSofRi. Ki,jk isrelatedtotherelayoperationaltimeanditvarieswiththe standardofRi.Icckj istheklevelofshort-circuitwhereRjactas primaryprotection.Ai,Bi,Ci,Di,Ei,NiandPiareconstantsrelated tothecurvetypesfor,Ri.Icckjisthesizeofthediscretizationstep oftheselectivityinterval.IccjmaxandIccjminarethemaximumand minimumshort-circuitcurrentsinsidetheprimaryprotectionzone ofRj,respectively.
3. Coordinationproblem
InFig.1isshownaRDN.WhereR1,R2andR3refertorelays1,2 and3,respectively.F1,F2andF3correspondtothefaultslocation inthesystem.ForthefaultinF3,R3andR2willactasprimaryand back-upprotection(PPandBP),respectively.ForthefaultinF2,R2
andR1willactasPPandBP,respectively.Finally,forthefaultinF1, R1willactasPPanditistheonlyprotectionavailable.Theareas boundedbydottedlinesaretheprotectionzonesofeachrelay.
AsthefaultissensedbybothBPandPPsimultaneously,the difference betweentheir operational times must be greater or equalthanthecoordinationtimeinterval(Trelay),toguarantee theselectivity.Thisway,thePPwillhavesufficienttimetoclearthe fault,whereintheBPmustactonlyifthePPfailsinclearingthefault.
Usually,isadoptedTrelay=0.4sbecausethecircuitbreakeroper- atingtime,themanufacturingtolerancesandthedesignofsafety timeareapproximately0.13,0.10and0.17s,respectively[1].
4. Mathematicalmodel
Inthissection,thecoordinationproblemofOCRsisformulated asanoptimizationproblem,containinganobjectivefunction(OF), responsibleforminimizingtheoperatingtimesoftherelays,and asetofconstraints.Thisproblemisformulatedasanonlinearand non-convexoptimizationproblem,withahighnumberofrestric- tions[23,29].Inthispaper,Ip,TDS,curvetype,andrelaytypeare consideredasvariables.Ifanyoftheseparametersistreatedasa discrete,theproblembecomesmixed-integer,whichhasagreater
complexity.Theadditionofcurveandrelaytypesasdecisionvari- ables is supportedby thefact that some microprocessor-based OCRsacceptseveralcurvetypesandstandards.Forinstance,the SEPAMSeries20(SchneiderElectric)[30]andthe735/737(Gen- eralElectric)[6]acceptmultiplecurvestandards,suchasIEEE,IEC andIAC.
4.1. Objectivefunction
Inafaultsituation,oneoftheconsequencesfortheelectrical systemisthesuddenincreaseincurrentlevelstodangerousval- ues.Thefasterthefaultisisolated,theloweristhethermaland mechanicaleffortsinthesystem.Intheoptimalcoordinationof OCRs,theobjectiveistoobtainthesettings(Ip,TDS,curvetypes andrelaytypes)thatminimizetheoperationaltimeoftheprimary protectionOCRs[3,31–33].Theoptimalsettingsaredirectlyrelated tothespeedcriteria.TheOFconsistsofminimizingthesumofall operationaltimesoftheOCRs,forallthepfaultlevelsconsidered withinitsprimaryprotectionzone,asshownin(8).
min z= 1 p
pk=1
mi=1
Ti,ik (8)
wherem,kand parethenumberofOCRs,theindexrelated to thefaultlevelanalyzedandthenumberoffaultlevelsconsidered withintheprimaryprotectionzones,respectively.Ti,ik istheopera- tionaltimeofRiforafaultinsideitsprimaryprotectionzone,and itcanbecomputedbysettingj=iin(1).
4.2. Constraints
The constraint shown in (9) refers tothe Trelay needed to ensuretheselectivitybetweenBPandPP.Theconstraintshownin (10)preventsthattherelaytakesalongtimetooperate,avoiding theequipmentdamageandtheinstabilityofthepowersystem.The constraintsrelatedtotheminimumandmaximumboundariesof TDSandIpareshownin(14)and(11),respectively.Therelaysmust notactduringthenormaloperationofthesystem,asitisshownin (12).RicannotactasBPiftheminimumshort-circuitcurrentinside itsprotectionzone(Iccprotected,i
min )islessorequalthanIpi,asshown in(13).
TBPk
i,i−Ti,ik ≥Trelay (9)
Ti,jk ≤Tmax (10)
Ipmini ≤Ipi≤Ipmaxi (11)
Ipi>LGF·Iloadi (12)
Ipi<Iccprotected,i
min (13)
TDSmini ≤TDSi≤TDSmaxi (14)
whereTBPk
i,iistheoperationaltimefortheBPofRi,forIccki.TDSi,min andTDSi,maxaretheminimumandmaximumpossibleTDSforRi, respectively.TmaxisthemaximumoperationaltimeoftheOCR,for Icckj.Ipmini andIpmaxi aretheminimumandmaximumpossibleIpfor Ri,respectively.Iccprotected,i
min istheminimumshort-circuitinsidethe protectionzoneofRi.LGFistheloadgrowthfactorthatincludes apossibleincreaseonthesystemdemand.Iiloadisthemaximum expectedloadcurrentinthesystem.
5. Thehighperformancehybridalgorithm
The proposed algorithm is based in the main ideas of the GApresentedin[34],whichwasinitiallydevelopedtosolvethe
Specify the control parameters of the HPHA
(kps and MaxIter)
Create the initial population using HCA-PI
Stop criteria satisfied?
Carry out phases:
- Selection - Recombination - Mutation
Apply Local search no
yes
Acceptation criteria
Stop:
Optimal TDS, Ip, relay and curve types Evaluate the fitness and
unfitness functions
Calculate the optimum TDS using EHA (Pseudocode 3)
Fig.2. FlowchartoftheproposedHPHA.
generalizedassignmentproblem.Thisalgorithmhasseveraldif- ferenceswhencomparedtotheclassicalGA:(1)ineachgeneration cycle,onlyoneoffspringisgeneratedanditcanenterinthecurrent populationifitsatisfiestheacceptationcriteria;(2)theOFiscom- posedbyfitnessandunfitnessfunctions;(3)alocalsearchisusedto improvetheOFoftheoffspring.
SomemodificationsintheGAproposedin[34]weremadeto adaptittothecoordinationproblem.Thecodification,population initialization,OFcomputationandlocalsearchareperformedin adifferentway.TheproposedmethodcombinesEHAwithaGA, inordertoreducethedimensionoftheproblem, makingthis a hybridtechnique.TheflowchartfortheHPHAisshowninFig.2.The parameterskpsandMaxIterreferstothesizeoftheinitialpopulation andthestopcriteria,respectively.TheHPHAstopsiftheincumbent solutiondoesnotchangeafterMaxItergenerationcycles.
5.1. Codification
In this paper,theTDS, Ip,relayand curvetypes are consid- ereddecisionvariables.TheTDSarenotcodedinthechromosome becauseitsoptimalvaluesaredeterminedusingtheEHA.Anexam- pleofachromosomeforasystemcontainingfiveOCRisshownin Fig.3.WhereIpgene,RelaygeneandCurvegeneareIp,relaytypeand curvetypesgenes,respectively.Eachchromosomeisdividedinto threeparts:oneforselectingIp,oneforcurvetypes,andtheother forrelaytypes. Adecimal codification isconsidered.Each gene assignedinIpgenewillcorrespondtoafeasibleIpvalueaccepted bytherespectiveOCR.EachvalueRelaygeneisrelatedtoonerelay type(IEEE,IEC,IACorU.S.),soitvaryfromonetofour.Eachvalueof Curvegeneisrelatedtoonestandardizedcurvetypeoftherespective OCRanditmayvaryfromonetofive.
2 6 1 5 7 2 3 2 1 2 1 1 3 2 2
Fig.3.Exampleofachromosomeoftheproposedalgorithm.
5.2. Initialpopulation
TheinitialpopulationofHPHAcanbecreatedrandomly,butthis canleadtohavingapopulationofpoorquality(veryhighopera- tionaltimesoftherelaysorunfeasibleproposals).Tosolvethis issue,theinitialpopulationcanbecreatedusingaheuristicalgo- rithmthattakessomecharacteristicsoftheproblemtobesolved.
Inthis paper,isproposedaheuristicconstructivealgorithm for thepopulationinitialization(HCA-PI).Thisalgorithmisshownin Pseudocode1,whereIpgenearelimitedby(12)and(13),andthe CurvegenearelimitedbytherespectiveRelaygene.Themainideaof thisalgorithmconsistsintoeliminatesomeinfeasibleproposalsin thepopulationinitialization.
Pseudocode1. Heuristicconstructivealgorithmforthepopula- tioninitialization(HCA-PI).
1: for(Allindividualsonthepopulation)do 2: for(i=1tonumberofrelays)do
3: Ipgene(i)←randomintegervaluethatcorrespondtoaIpthat satisfiesIiload·LGF<Ip<Iccprotected,i
min ;
4: Relaygene(i)←randomintegervaluethatvaryfrom1to4;
5: Curvegene(i)←randomintegervaluethatvaryfrom1tothe numberofavailablecurvetypesofRi;
6: endfor
7: endfor
5.3. Objectivefunction
First,itisnecessarytodecodetheinformationofIp,relaytypes andcurvetypesofthechromosome,inordertocomputetheTDS usingtheEHA(moredetailsinSection5.5).Thisway,thefitness functionisevaluatedusing(8).Theunfitnessfunctionispropor- tionaltothenumberofconstraints(11)–(14)violated,multiplied byapenalizationfactor.Thefitnessandunfitnessfunctionsarecom- binedandformtheOF.DuringtheiterativeprocessoftheHPHA, theOFiscomputedseveraltimes.Therefore,theEHAisinteresting duetoitsspeed.
5.4. Localsearch
Afterthephasesofselection,recombinationand mutation,a newoffspringisgeneratedanditcanbefeasibleorinfeasible.In bothcases,alocalsearchisperformedtoimproveitsOFbyperform- inganeighborhoodsearchinIpgeneandCurvegene.Thealgorithmis showninPseudocode2.
Pseudocode2. Localsearchalgorithm.
1: fori=1tonumberofrelaysdo
2: PerformaneighborhoodsearchintheIpgene(i)byincrementingand decrementingoneunit;
3: IftheneighborhoodsearchintheIpgene(i)improvedtheOF,update theIpgene;
4: PerformaneighborhoodsearchintheCurvegene(i)byincrementing anddecrementingoneunit;
5: IftheneighborhoodsearchintheCurvegene(i)improvedtheOF, updatetheCurvegene;
6: endfor
5.5. Efficientheuristicalgorithm(EHA)tocalculatetheoptimum TDS
TheLPisawellknowntechniqueusedtofindtheoptimalTDS [2].Inthispaper,isproposedanalternativemethodentitled“effi- cientheuristicalgorithm(EHA)”tofindtheoptimalTDSinRDN.
ThisalgorithmcanworkwithdiscreteandcontinuousTDS,unlike theLPtechniques.
Please cite this article in press as: A.A. Kida, L.A. Gallego, A high-performance hybrid algorithm to solve the optimal coordi- Theproposedalgorithmisdividedintotwosteps:relaynum-
beringanditerativeprocess.Inthefirststep,thebrancheswhere OCRarelocatedarearrangedinlayers.Inthenextsteptheoptimal TDSiscomputed.
5.5.1. Relaynumbering
In [35] is proposeda methodology for branches numbering basedinlayerstosolvethethree-phasepowerflow.Thesameideas areappliedfortheOCRnumbering.Thisway,theOCRinonelayer isnumberedonlyafterallOCRfromthepreviouslayerwasnum- bered.InFig.4isshownanexampleofasystemwithtenOCRafter thenumbering.InthecaseofR10,R9,...,R1wereanalyzedinthat particularorder,thePPwillalwaysbeanalyzedbeforetheBP.This methodologyallowsasystematicwaytoanalyzetheOCRonlyonce, duringtheEHA.Thisprocedureisperformedonlyonceforafixed RDN.
5.5.2. Iterativeprocess
Thealgorithm is showedin Pseudocode 3.In this step, it is assumedthatalltheOCRarepreviouslynumberedasshownabove.
ThevariablesKi,ik andKBPk
i,iarecomputedwith(2)–(5),depending onthetypeofRiandRBPi,respectively.Moreover,itisnecessaryto checkifthenewTDSdoesnotviolatetheboundofTDSmaxinthe steps10and12.
In this algorithm, each backup OCR hastheminimum TDSs necessarytobecoordinatedwiththeirprimaryprotections.This conditionisachievedwiththestep6ofthePseudocode3.Thepro- cessbeginsintherelaysfurtherfromthesubstationandendsin it.Whenareconsidereddiscretesettings,itisnecessarytoper- form roundingas shown in step 10 of Pseudocode 3 to avoid miscoordination.
Pseudocode3. Efficientheuristicalgorithm(EHA).
1: InitializeallrelayswithTDSmin;
2: fori=mto0do misthenumberofrelays.
3: ifRihasabackuprelaythen 4: RBPi←backuprelayofRi;
5: fork=1topdo pisthenumberoffaultsinside eachprotectionzone.
6:
Taux←TDSi·Ki,ik+Trelay;
theminimumoperationaltime requiredofRifortheconsidered faultlevelplusTrelay. 7: TDSaux←Taux/KBPk
i,i; TDSBPirequiredforRBPitohave anoperationaltimeofTauxforthe consideredfaultlevel.
8: ifTDSaux>TDSBPithen
9: ifTDSisconsidereddiscretethen
10: TDSBPi←roundTDSauxtothenextavailablesetting;
11: else forcontinuousTDS.
12: TDSBPi←TDSaux;
13: endif
14: endif
15: endfor
16: endif 17: endfor
6. Methods
TheproposedHPHAisappliedintwotestsystems:I(Fig.4)andII (Fig.5).Themaximumcurrentload,currenttransformerratio(CTR), theinitialrelayandcurvetypesandthemaximum/minimumshort- circuitcurrentsinsidetheprotectionzoneofeachOCR,forboth systems,areshowninTables5and6,respectively.Initially,allOCR areIECwithinversecurvetype.Itisassumedthatallrelayandcurve typescanbechanged(eitherbyreplacementorinputparameters).
ItisconsideredTDSmin=0.1,TDSmax=10,Tmax=5s,LGF=150%and p=2.TheTDSstepsis0.05and0.01forthetestsystemsIandII, respectively.TheIpvariesfrom50to200%oftheCTR,withsteps
R
1R
2R
3R
4R
5R
6R
7R
8R
9R
10Layer 1
Layer2 Layer 3 Layer4
Layer5
Fig.4.OCRsrenumberinginaRDN(testsystemII).
R
1R
3R
21
2 3 5
R
5R
4 4 6Fig.5.TestsystemI.
Table5
OCRdataforthetestsystemI.
R1 R2 R3 R4 R5
Iload(A) 199.5 130.8 68.7 100.7 50.0
CTR 300/5 300/5 100/5 200/5 100/5
Iccmax(A) 3115.0 2010.7 2010.7 1512.5 878.4
Iccmin(A) 1510.5 1046.3 975.1 500.3 325.1
16 16 31 7 7
Ip1 Ip2 Ip3 Ip4 Ip5 Fig.6. Chromosomeusedforexample.
of15%.Also,theGAparameterskpsandMaxIteraresetto100and 1500,respectively.
7. Resultsanddiscussions 7.1. AnexampleoftheHPHA
AnexampleoftheprocedureusedforcalculationoftheTDSsand OFoftheproposedalgorithminthetestsystemIisshownasfol- lows.Thisproceduretakesplaceinstagesforthecreationofinitial population,mutation,recombinationandlocalsearch.Forsimplic- ity,onlythevaluesofIparedecisionvariables.Thus,thecurveand relaytypesarefixed,whereallrelaysareIECwithinversecurve type.ThechromosomeoftheGAusedinthisexampleisshown inFig.6.EachgenecorrespondstoIpavailableinthecorrespond- ingrelay.Forexample,asthegenerelatedtoIp1is16,soIp1gets the16thavailableIpavailableatR11(Ip1←375A).Theremaining decodedIpsareIp2=375,A,Ip3=200,A,Ip4=160,AandIp5=70,A.
1TheIpsavailableatR1are{150,165,180,195,...,600A}.
Table6
OCRdataforthetestsystemII.
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10
Iload(A) 399.5 120.8 278.7 50.7 70.1 79.2 199.5 199.5 100.7 99.2
CTR 600/5 200/5 500/5 100/5 150/5 600/5 200/5 500/5 100/5 150/5
Iccmax(A) 3115.0 2010.7 2010.7 1512.5 1512.5 1190.0 1190.0 950.4 780.1 780.1
Iccmin(A) 1510.0 1046.3 975.1 630.3 599.1 510.5 699.3 519.1 398.3 372.1
First,allrelaysareinitializedwithTDSmin.Thecountersiand k are initialized withthe number of relays (i←5) and (k←1), respectively.
7.1.1. Step1–coordinationbetweenR3andR5
Thecoordinationisperformedfor325.1A(Icc15),whichisone oftheconsideredfaultlevelsinsidetheprimaryprotectionzone ofR5.Inthiscase,Ri←R5andRBPi←R3.Tauxiscomputedasthe minimumoperationaltimeofR3forfaultsinsideitsprotectionzone plusTrelay,asshownin(15).
Taux=TDS5·K5,51 +Trelay=0.1·4.9228+0.4=0.8923s (15) ThevariableTauxhastheminimumoperationaltimerequired forthebackupprotection(R3)tobecoordinatedwiththeprimary protection(R5).ThenecessaryTDSforthebackupprotectionhave anoperationaltimeofTauxisTDSaux,anditiscalculatedasshown in(16).
TDSaux= Taux
K3,51 = 0.8923
14.3389=0.0622 (16)
SinceTDSaux<TDS3,theTDS3 isnotupdated.Thecounterkis increased(k←2)andthecoordinationisheldfor878.4A(Icc25),for thesamepairofOCRs,asshownin(17)and(18).
Taux=TDS5·K5,52 +Trelay=0.1·2.8520+0.4=0.6852s (17) TDSaux= Taux
K3,52 =0.6852
4.6608=0.1470 (18)
TheTDSaux>TDS3,soTDS3←0.15,because0.1470isnotavail- ableattherelay.2ThecoordinationbetweenR3andR5isfinished, thecounteriisdecremented(i←4)and(k←1).
7.1.2. Step2–coordinationbetweenR2andR4
Thecoordinationisrealizeforthefaultlevelof500.3A(Icc14), Ri←R4andRBPi←R2.ThevariablesTauxandTDSauxarecomputed asshownin(19)and(20).
Taux=TDS4·K4,41 +Trelay=0.1·6.0704+0.4=1.0070s (19) TDSaux= Taux
K2,41 = 1.0070
24.2119=0.0416 (20)
As TDSaux<TDS2, theTDS2 is not updated. The counter k is increased(k←2)andthecoordinationisheldfor1512.5A(Icc24),for thesamepairofOCRs.TheTauxandTDSauxarecomputedasshown in(21)and(22).
Taux=TDS4·K4,42 +Trelay=0.1·3.0467+0.4=0.7047s (21) TDSaux= Taux
K2,42 =0.7047
4.9497=0.1424 (22)
In this case, TDSaux>TDS2, so TDS3←0.15. The coordination betweenR2andR4isendedandthecounteriisdecremented(i←3) and(k←1).
2 TheTDSavailableattherelayare0.1,0.15,0.20,0.25,...,10.
7.1.3. Step3–coordinationbetweenR1andR3
Thecoordinationis performedfor975.1A(Icc13),Ri←R3 and RBPi←R1.ThevariablesTauxandTDSauxarecomputedasshown in(23)and(24).
Taux=TDS3·K3,31 +Trelay=0.15·4.3489+0.4=1.0523s (23) TDSaux=Taux
K1,31 =1.0523
7.2554=0.1450 (24)
AsTDSaux>TDS1, so TDS1←0.15. The counter k is increased (k←2)andthecoordinationisperformedfor2010.7A(Icc23),for thesamepairofOCRs.ThevariablesTauxandTDSauxarecomputed asshownin(25)and(26).
Taux=TDS3·K3,32 +Trelay=0.15·2.9636+0.4=0.8445s (25) TDSaux=Taux
K1,32 =0.8445
4.0988=0.2060 (26)
Onceagain,theTDSaux>TDS1,soTDS1←0.25.Thecoordination betweenR3 andR1isfinishedandthecounteriisdecremented (i←2)and(k←1).
7.1.4. Step4–coordinationbetweenR1andR2
The coordination is realized for 1046.3A (Icc12), Ri←R2 and RBPi←R1.TheTauxandTDSauxarecomputedasshownin(27)and (28).
Taux=TDS2·K2,21 +Trelay=0.15·6.7523+0.4=1.4128s (27) TDSaux=Taux
K1,21 =1.4128
6.7523=0.2092 (28)
As TDSaux<TDS1, the TDS1 is not updated. The counter k is increased(k←2)andthecoordinationisheldfor2010.7A(Icc22),for thesamepairofOCRs.TheTauxandTDSauxarecomputedasshown in(29)and(30).
Taux=TDS2·K2,22 +Trelay=0.15·4.0988+0.4=1.0148s (29) TDSaux=Taux
K1,22 =1.0148
4.0988=0.2476 (30)
DuetoTDSaux<TDS1,theTDS1isnotupdated.Thecoordination betweenR1 andR2isfinishedandthecounteriisdecremented (i←1)and(k←1).AsRi←R1anditdoesnothavebackupprotec- tion,theiterativeprocessends.TheoptimumTDSsareTDS1=0.25, TDS2=0.15,TDS3=0.15,TDS4=0.10andTDS5=0.10.TheOFinthis caseis3.231s.
7.2. ResultsfortestsystemsIandII
Forbothsystems,theOCRcoordinationwillbedoneforthree cases:A,BandC.InthecaseA,TDSandIpareconsidereddecision variables.IncaseB,thereisanadditionofthecurvetypesasdeci- sionvariables.IncaseC,thereisanadditionoftherelaytypesas decisionvariables.TheresultsareshowninTables7and8.
WhentheresultsofcasesAandBareconfronted,theaddition ofcurvetypesasdecisionvariablesimprovedtheOFby25.63and 35.74%forthesystemsIandII,respectively.Whentheresultsof
Please cite this article in press as: A.A. Kida, L.A. Gallego, A high-performance hybrid algorithm to solve the optimal coordi- Table7
ResultsfortestsystemI.
CaseA CaseB CaseC
Ip(A) TDS Relay Curve Ip(A) TDS Relay Curve Ip(A) TDS Relay Curve
R1 375 0.25 IEC I 375 0.20 IEC I 420 6.15 U.S. S.I
R2 375 0.15 IEC I 375 0.10 IEC I 240 2.35 IAC E.I
R3 200 0.15 IEC I 170 0.15 IEC E.I 125 0.25 IEC E.I
R4 160 0.10 IEC I 160 0.10 IEC E.I 160 0.10 IAC S.I
R5 80 0.10 IEC I 80 0.10 IEC E.I 80 0.10 IAC S.I
OF 3.231s 2.403s 1.394s
Table8
ResultsfortestsystemII.
CaseA CaseB CaseC
Ip(A) TDS Relay Curve Ip(A) TDS Relay Curve Ip(A) TDS Relay Curve
R1 440 0.28 IEC I 500 0.17 IEC E.I 500 2.02 U.S. M.I
R2 160 0.21 IEC I 160 0.14 IEC I 160 8.14 IAC S.I
R3 370 0.21 IEC I 310 0.18 IEC I 250 3.17 IAC E.I
R4 80 0.10 IEC I 80 0.10 IEC V.I 80 0.10 IAC S.I
R5 80 0.10 IEC I 80 0.10 IEC E.I 80 0.10 IAC S.I
R6 65 0.10 IEC I 65 0.10 IEC E.I 65 0.10 IAC S.I
R7 250 0.19 IEC I 130 0.47 IEC E.I 160 0.30 IEC E.I
R8 280 0.10 IEC I 130 0.20 IEC E.I 160 1.59 IAC E.I
R9 65 0.10 IEC I 65 0.10 IEC E.I 65 0.10 IAC S.I
R10 65 0.10 IEC I 65 0.10 IEC E.I 65 0.10 IAC S.I
OF 6.539s 4.202s 3.465s
Table9
Relayoperationaltimes(caseC),forthetestsystemI.
PP BP Iccmin Iccmax
TPP TBP TBP−TPP Icc(A) TPP TBP TBP−TPP Icc(A)
R1 – 0.827 – – 1510.5 0.531 – – 3115.0
R2 R1 0.722 1.158 0.436 1046.3 0.274 0.677 0.404 2010.7
R3 R1 0.334 1.254 0.920 975.1 0.078 0.677 0.600 2010.7
R4 R2 0.007 3.175 3.168 500.3 0.005 0.406 0.401 1512.5
R5 R3 0.006 3.470 3.464 325.1 0.005 0.413 0.409 878.4
casesBandCareconfronted,theadditionofrelaytypesasdecision variablesimprovedtheOFby41.99and17.54%forthesystemsI andII,respectively.Agreaterimprovementhappenedwhencon- frontedcasesAwithC,whichtheadditionofrelayandcurvetypes asdecisionvariablesimprovedtheOFby56.86and47.01%forthe systemsIandII,respectively.Theresultsshowedthattheaddition ofmoredecisionvariablesintotheproblemgreatlyreducedthe OCRoperationaltimes.Theconsiderationoftherelaysandcurves typesasdecisionvariables,resultinawiderangeofcurvesshapes
thatcanbechosen.Thisflexibilityimprovedthecoordinationof OCR.
ForthecaseC,thecoordinationgraphicsfortheOCRforthetest systemIandIIareshowninFig.7.Also,theoperationaltimesfor bothPPandBPareshowninTables9and10.Theselectivitywas achievedfortheconsideredfaultlevels,becauseofthedifferences betweenTBPandTPParegreaterthanTrelay,forallOCRspairs.Also, theOCRdidnottaketoolongtooperate,sincealltheTBPandTPP
arelessthanTmax.
Table10
Relayoperationaltimes(caseC),forthetestsystemII.
PP BP Iccmin Iccmax
TPP TBP TBP−TPP Icc(A) TPP TBP TBP−TPP Icc(A)
R1 R0 0.985 – – 1510.5 0.609 – – 3115.0
R2 R1 0.432 1.457 1.024 1046.3 0.389 0.789 0.400 2010.7
R3 R1 1.177 1.607 0.430 975.1 0.389 0.789 0.400 2010.7
R4 R2 0.005 0.501 0.496 630.3 0.004 0.404 0.400 1512.5
R5 R2 0.005 0.512 0.506 599.1 0.004 0.404 0.400 1512.5
R6 R3 0.005 4.507 4.502 510.5 0.004 0.842 0.838 1190.0
R7 R3 1.325 2.212 0.886 699.3 0.441 0.842 0.400 1190.0
R8 R7 0.827 2.519 1.692 519.1 0.300 0.700 0.400 950.4
R9 R8 0.005 1.421 1.416 398.3 0.004 0.406 0.401 780.1
R10 R8 0.005 1.656 1.651 372.1 0.004 0.406 0.401 780.1
Fig.7.CoordinationgraphicsforthecaseC.
AperformancebenchmarkbetweenEHAandLPtechniqueswas realized,thus,theTDSweretreatedascontinuousvalues.TwoLP solverswereutilized:thestate-of-the-art CPLEX® andtheopti- mizationtoolofMatlab®.ThetestsweredoneinaIntel®CoreTM [email protected], and theresultsare shown inTable 11.
TheEHAandtheLPsolversprovidedthesameanswers,butthey demandeddifferentcomputationaltimes.In theworstcasesce- nario(testsystemII),theEHAwas2.69timesfasterthanthefastest LPsolver(CPLEX®).TheMatlab®solverwastheslowestalternative tosolvethisproblem.Inaddition,theEHAcanhandlediscreteTDS differentlyfromLPtechniques.Thisway,theEHAshowedtobea superiortechniquetofindtheoptimumTDSinRDN(Fig.8).
Table11
TimecomparisonforfindingtheoptimumTDSforthecaseA(consideringcontinu- ousTDS).
Testsystem EHA(ms) PL(CPLEX®)(ms) PL(Matlab®)(ms)
I 0.39 1.21 15.25
II 0.58 1.56 15.87
Fig.8.ConvergenceoftheHPHA.
8. Conclusion
This paper presented a high-performance hybrid algorithm (HPHA)tosolvetheproblemofovercurrentrelays(OCRs)coordi- nationinradialdistributionnetworks(RDNs).TheHPHAcombines ageneticalgorithm(GA)withanefficientheuristicalgorithm(EHA) todecreasethesearchspaceoftheGA,astheoptimumtimedial settings(TDS)arecomputedwiththeEHA.Severaladvantagesare obtainedusingtheEHA:(1) itcanhandlediscreteandcontinu- ousTDS;(2)itdoesnotdependoncommercialsolvers;(3)itis fasterthanthelinearprogramming(LP)techniquesand(4)ithasa simpleimplementation.TheEHAshowedtobeamoreinteresting approachthanLPtechniquesforRDN.
Severaldecision variablesareconsideredintheoptimization problem:TDS, pickupcurrent (Ip),curvetypes andrelaytypes.
Foreachdecisionvariablesaddedtotheproblem,theOCRoper- ationaltimeswerereduced.Therefore,itisinterestingtoconsider intheoptimizationproblemtheadjuststhatdonotimplyaddi- tionalcosts,like TDS,Ip and curvetypes.The additionof relay