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ID:36510803
大小:2.25 MB
页数:63页
时间:2019-05-11
《搜寻者优化算法在电力系统最优潮流中的应用》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、西南交通大学硕士学位论文搜寻者优化算法在电力系统最优潮流中的应用姓名:张倩申请学位级别:硕士专业:电力系统及其自动化指导教师:陈维荣20080601西南交通大学硕士研究生学位论文第fI页AbstractWiththerapiddevelopmentofelectricpowersystem,thegridsbecomelargerandlarger.Howtoguaranteethepowersystemrunmngeconomically,safelyandstablybecomeafocusintheworld.Inordertorealizetheoptim
2、aldistributionofthepowerflOW,differentcontrollingvariablesarechosentodotheadjustment.Theincreaseofvariablosandnon-linearconstraintsalongwiththecomplicatedrelationshipbetweenthemmakestheoptimalpowerflow(OPF)problemacomplicated,largerunmathematicalprogrammingone.Theswarmintelligenceopti
3、mizationalgorithmhastheobviousadvantagesinsearchingthebestsolutionforthelargerun,non—linearproblem,offeringnewwaystosolvetheOPFproblem.+ThetraditionalOPFalwaystakestheeconomicalrunoftheelectricpowersystemasthedestination,andgetstheOPFresultsthroughaajustingthegeneratorvoltages,transfo
4、rmertapsandcapacitortanks.However,thevoltagestabilityisoftenneglected.Infact,intheconditionoftheelectricpowermarketatpresent,consideringtheinfluenceofenvironmentalandeconomicalelements,thepowersystemisapttoruncloselytothemarginstatus,resultingintheinsufficientvoltagestableredundancy.T
5、hereforethevoltagecollapsewillhappensoreetime.PowerlossesandvoltagestabilityarebothtakenintoaccountwhencreatingtheOPFmodelinthethesis.Duetothedifferentdimensionandvaluationcriteria,thenormalizationwascarriedoutSOastoconvertthemulti.objectiveoptimizationproblemintoasingleone..Inthethes
6、is,thereviewoftheOPFresearchwascarriedout,includingsummarizingthedifferentobjectivefunctionsandmathematicalmodelsofOPFandcomprisingthedifferentalgorithmsusedintheOPFsoluti.on.Furthermore,seekeroptimizationalgorithm(SOA)isanovelmethodintheswarmintelligencecomputationandappearsitsgoodpe
7、rformanceinsomefields,whichwasintroducedinthethesis.Thebackground,mathematicalmodelandtheoDtiniizationprocessofSOAworedescribed.AndthecomparisonswithPSO—W(Particleswarmoptimizerwithinertiaweight),PSo.CF(particleswarmoptimizerwi.thconstrictionfactor),andCLPSO(Comprehensivelearningparti
8、cle西南
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