电力系统保护与控制2009，Vol.37Issue(13)：1-6,6.
基于自适应聚焦粒子群算法的电力系统无功优化
Reactive power optimization in power system based on adaptive focusing particle swarm optimization
摘要
Abstract
Adaptive focusing particle swarm optimization (AFPSO) based on the balance characteristic between global search and local search of particle swarm optimization is an adaptive swarm intelligence optimization algorithm with preferable ability of global search and search rate. AFPSO is proposed to optimize the reactive power optimization. Based on optimal control principle, AFPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. The modeling of reactive power optimization is established by taking the minimum network losses as the objective. The simulation results and the comparison results with various optimization algorithms demonstrate that the proposed approach converges to better solutions much faster than the earlier reported approaches and the algorithm can make effectively use in reactive power optimization. Simultaneously, the validity and superiority of AFPSO is proved.关键词
电力系统/自适应聚焦粒子群算法/无功优化/群体智能Key words
power system/adaptive focusing particle swarm optimization/reactive power optimization/swarm intelligence分类
信息技术与安全科学引用本文复制引用
刘述奎,陈维荣,李奇,林川,段涛..基于自适应聚焦粒子群算法的电力系统无功优化[J].电力系统保护与控制,2009,37(13):1-6,6.基金项目
国家自然科学基金(60870004) （60870004）
西南交通大学博士生创新基金(2007-3) This project is supported by National Natural Science Foundation of China(No.60870004) and Doctoral Innovation Foundation of Southwest Jiaotong University(2007-3). （2007-3）
