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改进PSO算法在电力系统无功优化中的应用
引用本文:詹克明,许小鹏,法智,詹恒富. 改进PSO算法在电力系统无功优化中的应用[J]. 农业科技与装备, 2012, 0(1): 35-37
作者姓名:詹克明  许小鹏  法智  詹恒富
作者单位:1. 本溪供电公司,辽宁本溪,117000
2. 沈阳供电公司,沈阳,110811
摘    要:介绍一种改进粒子群的无功优化方法。采用简化粒子群优化方程和添加极值扰动算子两种策略加以改进,提出简化粒子群优化(SPSO)算法、带极值扰动粒子群优化(DPSO)算法,并将二者结合起来提出带极值扰动的简化粒子群优化(DSPSO)算法。以IEEE6节点系统为例进行无功优化计算,并与其他算法进行比较,结果表明:该算法具有较快的收敛速度及较强的全局搜索能力,可较好地解决电力系统的无功优化问题。

关 键 词:电力系统  无功优化  粒子群算法  应用

Applications of Improved PSO Algorithm in Reactive Power Optimization
ZHAN Keming,XU Xiaopeng,FA Zhi,ZHAN Hengfu. Applications of Improved PSO Algorithm in Reactive Power Optimization[J]. Agricultural Science & Technology and Equipment, 2012, 0(1): 35-37
Authors:ZHAN Keming  XU Xiaopeng  FA Zhi  ZHAN Hengfu
Affiliation:1. Benxi Power Supply Company, Benxi Liaoning 117000, China; 2. Shenyang Power Supply Company, Shenyang 110811, China)
Abstract:This article deals with a reactive power optimization with improved particle swarm optimization. Simplified particle swarm optimization and adding extreme value disturbance operators are adopted to bring about the following two algorithms, namely, SPSO and DPSO. An integration of the two methods leads to DSPSO. Taking IEEE six nodes as an example, reactive power optimization computation is conducted and compared with other methods. The result shows that the convergence rate of the new method is faster and its global search capacity is stronger therefore it is likely to solve the problems in reactive power optimization.
Keywords:electric system  reactive power optimization  particle swarm optimization  application
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