基于改进pso算法的配电网无功补偿优化配置分析

基于改进pso算法的配电网无功补偿优化配置分析

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时间:2019-01-31

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1、万方数据ABSTRCTUnreasonabledistributionofreactivepowerwilldecreasevoltagequality,increasenetworklossesandreducepowersystemstability.Thereactivepoweroptimizationcanintegrateexistingresources,maximumincreaseeconomicbenefitofthesystemandcustomer.Sothatthestudyofthepro

2、blemofreactivepoweroptimizationhasthegreatsignificanceinthetheoryandpracticalapplication.Afterthispaperanalyzestheadvantagesanddisadvantagesoftheexistingoptimizationalgorithm;animprovedParticleswarm0ptimizationalgorithmforthemathematicalmodelcorrespondstotheact

3、ualcalculationisoptimized.Theadvantagesofsimplicityandeasyimplementationofparticleswarmalgorithmhavebeenvalidatedinscienceandengineeringfields.However,theweaknessesofparticleswarmalgorithmarethesameasotherevolutionaryalgorithm’S,suchaseasytofallintolocalminimum

4、,prematureconvergence,etc.ThereasonsofdisadVantagesofParticleSwarmOptimization(PSO)Algorithmwereanalyzed,andaChaoticSequence-CosinePSO(CS—CPSO)algorithmhasbeenproposed.Itmakestheinitialparticlestotraversetheentiresearchspacetousethepopulation-initializedofchaot

5、icsequencesinthealgorithm.Andthatincreasesthediversityofinitialpopulation.ItmakestheparticlesintheearlytohavetheabilityofstrongerglobalsearchthattheinertiaweightoftheSPSOwaschangedbecauseofcosinefunctionsnonlinearity.Alongwiththefrequencyofiterationsincreasing,

6、theinertiaweightdecreases,andthenthelocalsearchcapabilityofparticlereinforced.Theaccuracyofthealgorithmimproves.TheparticleshavestrongabilityofsociallearningatanearlystagebecausethelearningfactorwaschangedbythecosinefunctionofnonlinearsymmetriC,0therparticleswi

7、lldrawc10setotheoptimalrapidly.Particleitselflearningabilityisenhancedlatterly.Itspeedsuptheconvergenceofthealgorithm;BacterialchemotaxishasbeenintroducedintheCS—CPSOalgorithm,whichmaintainsthediversityofpopulation,andpreventstheparticlesfallintolocaloptimumina

8、certainextent.TheCS—CPSOalgorithmissimulatedandanalyzedbyfivetestfunctions,comparedwiththeoriginalparticleswarmoptimizationalgorithmandstandardparticleswarmoptimizationalgor

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