基于遗传算法的随机最优潮流求解-研究

《基于遗传算法的随机最优潮流求解-研究》由会员上传分享，免费在线阅读，更多相关内容在教育资源-天天文库。

1、广东工业大学硕士学位论文ABSTRACTReliabilityandeconomyusuallyconflictwitheachotherincomplexpowersystem．Foronehand，thepowergridofChina，whichalsoisthelargestandmostcomplicatednetworkintheworld，askforhighreliabilityofsafeoperation．Ontheotherhand，duetotheresourcespentineconomicdevelopmentofChinabecomemo

2、reandmore，it’Shightimethatweshouldmakethemostefficientuseoftheavailableresources．Sothepowergridmustplayanimportantpartinalleviatingtheconflictofreliabilityandeconomy,especiallywhendifferentkindsofdifferentuncertainfactorsmustbeconsidered．StochasticOptimalPowerFlow(SOPF)isproposedtostudy

3、thekindofproblem．SOPFisbroadlyappliedinmanyaspectsofpowermarket，suchasoptimaldispatch，optimalancillarycontrol，biddingstrategy，demandsidemanagementandSOon．Forthisreason，theresearchandapplicationofSOPFplayanimportantroleinsmartgridbuildinganddevelopment．However，thefitnessandsolutioneffici

4、encyinpresentalgorithmtoSOPFproblemdon’tagreewitheachother．ThealgorithmtoSOPFproblemappliedinreal-timecomputationisstillunderresearch．Inordertothis，thisthesismakesanintroductionofthekindsofSOPFmodelsandtheequivalencetopowerinjected，putsforwardanalgorithmwithhighfitness，prospectstheresea

5、rchanddevelopmentofSOPF．FromthebeginningofthedevelopmentofOPF,thisthesismakesanintroductionofSOPF，aswellasthesignificanceoftheSUbjectstudyatpresent．TothesummaryonthesituationofSOPFresearch，thisthesisconductsstudyonthesignificanceofSOPFwithLoadUncertainty．Italsoputsforwardanalgorithmwith

6、highfitnessandthestochasticmodelconsideringthechanceconstraintofvoltageandtransmissionlimitappliedinpractice．ApplyingthismodelintoIEEE5-bussystemandHeyuanpowersystem，wecangettheresultofoptimization．TheSOPFproblemusesthegeneticalgorithmtodealwiththeuncertaintiesandcommonPFmethodwithMonte

7、CarloSimulationtofulfillchanceconstraints，whichhashighfitness．Atlast，bycontrastbetweengeneticalgorithmandcertaintyalgorithm，thisthesismakesaconclusionthatgeneticalgorithmismoreadaptabletoSOPFinreal—timecomputationandmuchmoreofprospect．¨ASBTRAC丁KeyWords：UncertaintyFactors；Chance