基于PSO-GWO混合算法的电力系统经济调度优化

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中图分类号：TM761 文献标识码：A 文章编号：1006-8228（2026）02-40-07

Abstract：Swarmintellgenceoptimizationalgorithmsareefectivemethodsforsolvingeconomicdispatchproblemsinpower systems.However，traditionalalgorithmsstruggletobalanceconvergencespedandglobalsearchcapablityTherefore，basedon particleswarmoptimizationandthegreywolfoptimizer，thispaperproposesahybridalgorithmcaledPGWO，whichcombinesthe advantagesofbothInthenewalgoriththeintroductionofaonlinearinertiaweightadynamicsocialinfluencecoientand adiversity preservationmechanismenablesPGWOtoachieveadynamicbalancebetweenglobalexplorationandlocalexploitation. Whensolvingtheeconomicdispatchotimizationproblem，thePGWOalgorithmisappliedalongwithaquadraicpenaltyfunction tohandlepowerbalanceandoutputconstraints，enhancingsolutionfeasibility.Simulationexperimentsbasedonasix-unittest systemshowthattheproposedPGWOalgorithmcanobtainlowertotalgenerationcostsandbettrconvergencestabilitywhile satisfyingallconstraints.Thisprovidesaneffectivesolutionforcomplex powersystemeconomic dispatch problems.

Keywords：PowerSystem;EconomicDispatch；SwarmIteligenceOptimizationAlgorithm;ParticleSwarmOptimization;GreyWolf Optimization

0引言

电力系统经济调度是电力系统运行优化的核心问题，其自的是在满足负荷需求和系统约束的条件下，合理分配各发电机组出力，使系统总发电成本最小。（剩余9116字）