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时间:2020-03-28
《基于适应性权重遗传算法的多目标无功优化研究.pdf》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、第38卷第6期电力系统保护与控制VO1.38No.62010年3月16日PowerSystemProtectionandControlMar.16.2Ol0——基于适应性权重遗传算法的多目标无功优化研究陈得宇,张仁忠,沈继红2高世伟。(1.哈尔滨工程大学自动化学院,黑龙江哈尔滨150001;2.哈尔滨工程大学理学院,黑龙江哈尔滨1500013.天津电力公司,天津300201)摘要:研究一种多目标无功优化问题的求解方法。基于无功分层分区平衡以及保证紧急情况下电网安全的原则,给出了在电网正常情况下优先投切电容器、调节变压器分接头,然后设定机端电压的
2、优化调控顺序,进一步提出将优化问题分解为连续变量优化和离散变量优化问题,并分别求解,迭代直至收敛的求解思路。鉴于多目标无功优化模型的复杂性,以及连续、离散控制变量并存,采用遗传算法求解,重点研究了控制变量的编码方案以及选择、交叉、变异以及保留操作策略。针对于多目标无功优化各个目标权重难以确定问题,又进一步引入了适应性权重遗传算法,随着遗传代数的进化算法能自适应地给出各个目标权重。仿真算例验证了文中所提的多目标无功优化求解方法的合理性。关键词:多目标无功优化;电容器投切;变压器分接头调节;机端电压设定;适应性权重遗传算法Studyoilmulti
3、—objectivereactivepoweroptimizationbasedougeneticalgorithmwithadaptiveweightCHENDe.yu,ZHANGRen.zhong,SHENJi.hong2GAOShi—wei3,(1.CollegeofAutomation,HarbinEngineeringUniversity,Harbin150001,China;2.CollegeofScience,HarbinEngineeringUniversity,Harbin150001,China;3.TianjinElect
4、ricPowerCompany,Tianjin300201,China)Abstract:Thesolutionformulti—objectivereactivepoweroptimizationiSstudied.Basedontheprincipleofhierarchicalandregionalbalanceofreactivepowerandguaranteeforpowersystemstabilityinemergencycases,regulationorderisconfirmed,thatcapacitorswitchin
5、gandtransformertapadjustingarefirst,andgeneratorterminalvoltagesettingfollows.Furthermore,thesolvingthinkingispresented,thatoptimizationproblemisdecomposedintocontinuousvariableoptimizationanddiscretevariableoptimization,thentheyaresolvedrespectivelyandcrossiterationuntilcon
6、vergence.Inviewoftheoptimizationcomplexityandthecoexistenceofdiscretevariablesandcontinuousvariables,geneticalgorithmispresentedforfindingglobaloptimalsolution.Thecodingofcon~olvariablesandstrategiesfortheselection,cross,mutationandretentionoperationaremainlystudied.Aimingat
7、determiningeachobjectiveweightofmulti—objectiveoptimization,thegeneticalgorithmwithadaptiveweightisintroducedfurther,withgeneticevolutioneachobjectiveweightisgivenadaptivelybythealgorithm.Casestudiesshowthattheproposedthinkingandalgorithmforsolvingmulti-objectivereactivepowe
8、roptimizationarereasonable.Keywords:multi—objectivereactivepoweroptimizatio
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