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基于自适应混沌粒子群优化算法的多目标无功优化
引用本文:李娟,杨琳,刘金龙,杨德龙,张晨.基于自适应混沌粒子群优化算法的多目标无功优化[J].电力系统保护与控制,2011,39(9):26-31.
作者姓名:李娟  杨琳  刘金龙  杨德龙  张晨
作者单位:1.东北电力大学电气工程学院,吉林 吉林 132012;2.华北电力大学电气与电子工程学院,北京102206
摘    要:针对粒子群无功优化中由于随机生成代表控制变量值的粒子,使得在优化迭代过程中易陷入局部最优解,而且后期收敛速度慢等问题,将混沌优化算法融合到粒子群算法中,提出了混沌粒子群算法求解多目标无功优化问题。该算法在初始化粒子即无功优化控制变量值时,采用混沌思想,增加控制变量取值的多样性;通过粒子群无功优化算法计算各个粒子对应的适应值即无功优化目标函数值,并按照其大小择优选取控制变量值进行混沌优化以帮助无功优化控制变量跳出局部极值区域;并根据无功优化目标函数值自适应地调整其惯性权重系数以提高全局与局部搜索能力。通过算例分析表明,采用自适应混沌粒子群算法进行无功优化,能够及时跳出局部最优得到全局最优解,且收敛速度快。

关 键 词:自适应  混沌粒子群优化算法  无功优化  惯性权重

Multi-objective reactive power optimization based on adaptive chaos particle swarm optimization algorithm
LI Juan,YANG Lin,LIU Jin-long,YANG De-long,ZHANG Chen.Multi-objective reactive power optimization based on adaptive chaos particle swarm optimization algorithm[J].Power System Protection and Control,2011,39(9):26-31.
Authors:LI Juan  YANG Lin  LIU Jin-long  YANG De-long  ZHANG Chen
Affiliation:LI Juan1,YANG Lin1,LIU Jin-long1,YANG De-long2,ZHANG Chen2 (1. School of Electrical Engineering,Northeast Dianli University,Jilin 132012,China,2. School of Electrical and Electronics Engineering,North China Electric Power University,Beijing 102206,China)
Abstract:Particle swarm algorithm used in reactive power optimization always falls into local optimal solution and final slow convergence due to generating particles as controlling variable values randomly.Consequently,by integrating the chaotic opitimization algorithm into the particle swarm algorithm, a new adaptive chaotic particle swarm optimization based on chaos theory is adopted to solve the problem.Through the using of chaos ergodicity firstly,the control variables in the system are initialized to enhance th...
Keywords:adaptive  chaotic particle swarm optimization algorithm  reactive power optimization  inertia weight  
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