首页 | 本学科首页   官方微博 | 高级检索  
     

基于粒子群与模拟退火相结合的无功优化算法
引用本文:王振树,李林川,李波.基于粒子群与模拟退火相结合的无功优化算法[J].山东大学学报(工学版),2008,38(6):15-20.
作者姓名:王振树  李林川  李波
作者单位: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
基金项目:山东省自然科学基金资助项目(Y2007F27)
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  
收稿时间:2008-10-07

Reactive power optimization based on particle swarm optimization and simulated annealing cooperative algorithm
WANG Zhen-shu,LI Lin-chuan,LI Bo.Reactive power optimization based on particle swarm optimization and simulated annealing cooperative algorithm[J].Journal of Shandong University of Technology,2008,38(6):15-20.
Authors:WANG Zhen-shu  LI Lin-chuan  LI Bo
Affiliation: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
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...
Keywords:cooperative algorithm  particle swarm optimization  simulated annealing algorithm  reactive power optimization  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《山东大学学报(工学版)》浏览原始摘要信息
点击此处可从《山东大学学报(工学版)》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号