基于粒子群优化算法的PSS参数优化  

Parameter optimization of power system stabilizer on particle swarm optimization algorithm

作　　者：吴峰[1] 陈维荣[1] 李奇[1] 鲁晓帆[1] 

机构地区：[1]西南交通大学电气工程学院,四川成都610031

出　　处：《电力系统保护与控制》2009年第10期53-58,共6页Power System Protection and Control

摘　　要：粒子群算法(PSO-ω)是一种应用于连续空间的、具有较好的全局搜索能力和寻优速度的群体智能优化算法。基于单机无穷大系统模型,通过采用PSO-ω算法对电力系统稳定器(PSS)进行参数优化,以抑制低频振荡。该方法是以最优控制原理为基础,综合考虑PSS与励磁系统的性能,将PSS参数优化协调转化为带有不等式约束的优化问题,控制目标为系统输出按照最小误差跟踪给定值的能力(ITAE准则)。用Matlab软件进行仿真,结果表明,利用该方法设计的PSS,它的稳定性有了较大的提高。Particle swarm optimization （PSO-ω） applied to continuous space is a swarm intelligence optimization algorithm with preferable ability of global search and search rate. Based on the single machine infinity system, PSO-ω is proposed to optimize the parameter of 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 consider as the ability of tracking reference value（the principle of ITAE）. MATLAB simulation results show that the stability of the PSS with the method is enhanced.

关 键 词：电力系统稳定器 粒子群算法 单机系统 参数优化 ITAE准则 

分 类 号：TM712[电气工程—电力系统及自动化]