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山东大学学报(工学版) ›› 2008, Vol. 38 ›› Issue (6): 15-20.

• 论文 • 上一篇    下一篇

基于粒子群与模拟退火相结合的无功优化算法

王振树 李林川 李波   

  1. 王振树,李林川: 天津大学电力系统仿真控制教育部重点实验室, 天津 300072; 王振树:山东大学电气工程学院, 山东 济南 250061;
    李波: 山东电力工程咨询院, 山东 济南 250013
  • 收稿日期:2008-10-07 出版日期:2008-12-16 发布日期:2008-12-16
  • 作者简介:王振树(1963-),男,山东济宁人,副教授,博士研究生,研究方向为电力系统运行与控制. E-mail: zhenshuwang@sdu.edu.cn
  • 基金资助:

    山东省自然科学基金资助项目(Y2007F27)

Reactive power optimization based on particle swarm optimization and simulated annealing cooperative algorithm

  1. WANG Zhen-shu,LI Lin-chuan:Key Laboratory of Power System Simulation and Control of Ministry of Education, Tianjin University, Tianjin 300072, China;
    WANG Zhen-shu: School of Electrical Engineering, Shandong University, Jinan 250061, China;
    LI Bo:Shandong Electric Power Engineering Consulting Institute, Jinan 250013, China
  • Received:2008-10-07 Online:2008-12-16 Published:2008-12-16

摘要:

针对电力系统无功优化采用粒子群算法容易陷入局部最优、模拟退火算法约束条件多和收敛速度慢的问题,提出一种新的基于粒子群与模拟退火相结合的算法.该算法根据粒子群的易实现性、快速收敛性及模拟退火的全局收敛性,进行协同搜索,求取系统无功优化的解集.对IEEE14、57、118节点系统进行了无功优化仿真计算,结果表明该算法原理简单易实现,计算效率高且能获得质量更高的解.

关键词: 无功优化;粒子群算法;模拟退火算法; 相结合的算法

Abstract:

Particle swarm optimization (PSO) and simulated annealing algorithm (SA) have several problems when they are used for power system reactive optimization. A novel cooperative algorithm based on PSO and simulated SA was presented  according to the characteristics of PSO and SA. The new method efficiently combines PSO and SA and takes full advantage of the easily implementing performance and fast convergence performance of PSO and global convergence performance of SA to make them cooperate to find the best solution. The simulation results of the IEEE 14, 57,118 systems demonstrated that the proposed cooperative algorithm  can be  easily realized with high efficiency and can obtain higher quality solutions than PSO or SA alone.

Key words: cooperative algorithm; particle swarm optimization; simulated annealing algorithm; reactive power optimization

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