电力系统保护与控制2009，Vol.37Issue(13)：13-18,57,7.
基于随机聚焦粒子群算法的多机系统PSS参数优化
Parameter optimization of multi-machine power system stabilizers based on stochastic focusing particle swarm optimization
摘要
Abstract
Stochastic focusing particle swarm optimization (SFPSO) applied to continuous space is a swarm intelligence optimization algorithm with preferable ability of global search and search rate. SFPSO is proposed to optimize the multi-machine power system stabilizer (PSS). Based on optimal control principle, the performance of PSS and excitation system is considered into the method. The parameter optimization is converted to a problem of constraint inequality, and according to the least error with system output, the control object is considered as the ability of tracking reference value. The simulation results and the comparison results with various optimization algorithms demonstrate that PSS could obtain the favorable performance using SFPSO under different disturbance and could restrain the low frequency oscillation. Simultaneously, the validity and superiority of SFPSO is proved.关键词
电力系统稳定器/随机聚焦粒子群算法/多机系统/参数优化Key words
power system stabilizer/stochastic focusing particle swarm optimization/multi-machine power system/parameter optimization分类
信息技术与安全科学引用本文复制引用
李奇,陈维荣,段涛,刘述奎,刘元勋..基于随机聚焦粒子群算法的多机系统PSS参数优化[J].电力系统保护与控制,2009,37(13):13-18,57,7.基金项目
西南交大博士生创新基金资助项目(2007-3) （2007-3）
