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基于改进粒子群算法的分布式电源在配电网中选址定容研究.docx

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基于改进粒子群算法的分布式电源在配电网中选址定容研究 Title:ResearchonOptimalSitingandSizingofDistributedGeneratorsinDistributionNetworksbasedonImprovedParticleSwarmOptimization Abstract: Withtheincreasingintegrationofrenewableenergyresourcesindistributionnetworks,theoptimalsitingandsizingofdistributedgeneratorsplaysacrucialroleinensuringefficientandreliablepowersupply.Thispaperpresentsastudyontheapplicationofimprovedparticleswarmoptimization(PSO)algorithmfortheoptimalsitingandsizingofdistributedgeneratorsindistributionnetworks.Theproposedalgorithmaddressesthechallengesoffindingtheoptimallocationsandcapacitiesofdistributedgeneratorsbyconsideringbothtechnicalandeconomicfactors.Simulationresultsdemonstratetheeffectivenessoftheproposedapproachinenhancingtheperformanceofdistributionnetworkswithdistributedgenerators. 1.Introduction: Therapidgrowthofdistributedenergyresources(DERs)suchassolarpanelsandwindturbines,coupledwiththeincreasingdemandforrenewableenergy,hasledtothewidespreadadoptionofdistributedgenerators(DGs)indistributionnetworks.DGscanprovidenumerousbenefits,includingvoltageregulation,lossreduction,andimprovedreliability.However,theoptimalsitingandsizingofDGsisachallengingtaskduetothecomplexnatureofdistributionnetworks.ThispaperproposesanimprovedPSOalgorithmtoovercomethesechallengesandenhancetheperformanceofdistributionnetworks. 2.LiteratureReview: ThissectionreviewstheexistingstudiesonthesitingandsizingofDGsindistributionnetworks.Thetraditionalmethods,suchasheuristicalgorithmsandgradient-basedmethods,havelimitationsinhandlingthenon-linearandnon-convexoptimizationproblemsassociatedwithDGsitingandsizing.ThePSOalgorithmhasgainedsignificantattentionduetoitsabilitytohandlesuchproblemseffectively.However,thetraditionalPSOalgorithmsuffersfromprematureconvergenceandslowconvergencespeed.Toaddresstheselimitations,variousimprovementshavebeenproposed,suchasdiversitymaintenance,mutationoperation,andhybridizationwithotheralgorithms. 3.Methodology: ThissectiondescribestheproposedimprovedPSOalgorithmfo