Kingsuk Majumdar, Puja Das, P. Roy, Subrata Banerjee
{"title":"Solving OPF Problems using Biogeography Based and Grey Wolf Optimization Techniques","authors":"Kingsuk Majumdar, Puja Das, P. Roy, Subrata Banerjee","doi":"10.4018/IJEOE.2017070103","DOIUrl":null,"url":null,"abstract":"Thispaperpresentsbiogeography-basedoptimization(BBO)andgreywolfOptimization(GWO)for solvingthemulti-constrainedoptimalpowerflow(OPF)problemsinthepowersystem.Inthispaper, theproposedalgorithmshavebeentestedin9-bussystemundervariousconditionsalongwithIEEE 30bustestsystem.Acomparisonofsimulationresultsrevealsoptimizationefficacyoftheproposed schemeoverevolutionaryprogramming(EP),geneticalgorithm(GA),mixed-integerparticleswarm optimization(MIPSO)fortheglobaloptimizationofmulti-constraintOPFproblems.Itisobserved thatGWOisfarbetterincomparisontootherlistedoptimizationtechniquesandcanbeusedfor aforesaidproblemswithhighefficiency. KEyWORdS Biogeography Based Optimization, Grey Wolf Optimization, Migration, Mutation, Optimal Power Flow","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Energy Optim. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJEOE.2017070103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Thispaperpresentsbiogeography-basedoptimization(BBO)andgreywolfOptimization(GWO)for solvingthemulti-constrainedoptimalpowerflow(OPF)problemsinthepowersystem.Inthispaper, theproposedalgorithmshavebeentestedin9-bussystemundervariousconditionsalongwithIEEE 30bustestsystem.Acomparisonofsimulationresultsrevealsoptimizationefficacyoftheproposed schemeoverevolutionaryprogramming(EP),geneticalgorithm(GA),mixed-integerparticleswarm optimization(MIPSO)fortheglobaloptimizationofmulti-constraintOPFproblems.Itisobserved thatGWOisfarbetterincomparisontootherlistedoptimizationtechniquesandcanbeusedfor aforesaidproblemswithhighefficiency. KEyWORdS Biogeography Based Optimization, Grey Wolf Optimization, Migration, Mutation, Optimal Power Flow
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