基于动态规划和遗传算法的宿迁市城区配电网无功电源优化配置研究

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1、目录AbstractWiththerapiddevelopmentofeconomyandchangeofmanagemethodofpowersystemoperationandprogrammingofdistributionpowersystemarefacingnewproblems．Reactivepowercompensationis觚importantapproachtoimprovethevoltagesofdistributionsystemandreduceenergylosses．Inourcountrycapacitorco

2、mpensationisamainmethodinthelOkvleveldistributionsystem．ThispaperpresentedanewmethodattheoptimalplacingofcapacitorsinthedistributionsystembasedupoDdynamkprogrammingandgeneticalgorithm(GA)toachievethebesteconomicbehaviorwitheligiblevoltage．Thesumofpowerlossesandinvestmentsinthe

3、newaddingVARequipmentwhichhasbeendividedineachyearisusedasobjectivefunction．Atthesametimeineligiblevoltageisconsideredbyapunishingterm．Weresolvethecomplexmathematicalmodelusingdynamicprogrammingandgeneticalgorithm．EqualityandinequalityconsWaintsmakethemodelmorecomplywiththeact

4、ualsituationandavoidthelimitofsingleloadoperationcondition．Thisalgorithmismorerationalandcomprehensiveintheevaluationofpowersystemsecurityandeconomy．Dynamicprogrammingisamethodforexcessivephasesoptimaldecision-一makingprocedure．Thereactivepowercompensationproblemisdisassembledt

5、omanysubproblemsandresolvedonebyone．Everyphaseshouldmakeitsdecisionandthisdecisionwillbeusedasinitialvaluesfornextdecision．Whendecisionofeveryphaseisbasedonoptimizationthebestgoalisgotinthefinal．hIthispapersensitivityOAPL／aQfisusedtomaasuretheeffectofunitreactivepowercompensat

6、iononpowerlosses．Thisalgorithmhasapprovingspeed．ButbecausesomepredigestionisintroducedinsensitivitycalculationandanalyseisbasedonlocalnodestheresultisnOtveryprecise．Comparedwiththeclassicalanalyticalmethodsgeneticalgorithmhaslessconf'mementsabouttheproblems．Theonlyrequirementi

7、sresoluble．Ithasnorequirementfordifferentiableorcontinuity．TheobjectivefunctionalsoneedIl’ttobeconvexfunction．GAstaffsfrommulti—pointsinthebestgoalseekingprocedure．Itcalladjustparameterscontinuouslyandhasstrongerabilitytoreachtheoptimalgoalinwholespace．hlthecalculationweconsid

8、eredthetraitofdistributionnetworkofthecityofSuCheng．Forexampl