基于微网的分布式电源规划方法分析

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1、’华北I【l力人学顶lj学位论文Abstract’11herenewableenergyhascausedmoreattentionbecauseofthe1ncreaslngdepletionoffossilenergyandthedeterioratingofenVironment．Withthefastadvancesofmicro-network，thetechnologyofdistributedgenerationhasbeenrapidlydeVelopped．Thetechnologyofdis

2、tributedgenerationbasedonthemicro-networkhasmanyadvantagessuchaseconomicale师ciency’nexibilityandcompatib订ity’whichcangreatlyimporVesystemsecurityandeconomicalemciency'enhancethesystemrelidbilityandnexibility'reducethedepletionofnon—renewableresources．Focused

3、ontheresearchonthedistributedgenerationplanningmethodbasedonmicro-grid，thethesisanalyzethedif．ferentmodelsofpowerplanninginordertofindtheef．fectiVealgorithmtosoVletheoptimizations01ution．Finally，thethesisattainstheoptimalplaningaimedatthedistributedgeneratio

4、nplanningmodel．Accordingtotheresearchofthedistributedgenerationplanningmodel，theenconomicmodelbasedonthenumberofmodelindicatorscanbediVidedintothesingle—objectiVemodelandmulti-objectiVemodel．Thispaperhasadopttedgeneticalgorithm，improVedgeneticealgorimmandpar

5、ticleswarnloptimizationtooptimizethesingle—objectiVemodel．wecanfindthattheparticleswamoptimizationhashigheremciencywhichisindicatedbythecomparisonanalysisofthesolution．Thispapertakesuseofmulti—objectiVeeV01utionaryalgorithmandmulti-objectivegenetic10calsearc

6、htooptimizethemulti—objectiVemodelwhichiscompositedbylowinVestmentandhi曲energyoutput．TheresultshowsthatmecostofinVestmenthasgreatinnuenceontheselectionofoptimizationalgoIlitm．theoptimalalgo“thmcorrespondingtothedif-ferentstandardsofinVestmentcosts：itbetterto

7、adoptthemulti—objectiveeV01utionaryalgorithmwhentheinVestmentislow．onthecontrary，themulti—objectiVegeneticlocalsearchisused．Keywords：distributedgenerationplanning，micro—gridmodel，geneticalgorithm，multi—objectiVeeVolutionaryalgorithmH录目录摘要⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

8、⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯IABSTRACT⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯II第l章绪论⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11．1研究背景及意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯l1．2电源规划模型综述⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．31．2．1常规电源规划模型⋯⋯⋯⋯⋯⋯⋯⋯