摘要
提出一种新的混沌粒子群优化(CPSO)算法,将其用于求解复杂的电力系统经济负荷分配(ELD)问题。该算法保持了粒子群优化(PSO)的简单结构,先利用PSO算法的全局收敛能力进行搜索,以获得近似解(即粒子经过的最佳位置),然后利用混沌优化的混沌运动特性在近似解的邻域内进行局部搜索,从而获得精确的全局最优解。多个算例的仿真结果表明,该算法能快速有效求取电力系统ELD问题更精确的最优解。
A new chaotic particle swarm optimization （CPSO） algorithm is proposed to solve the complicated economic load dispatch （ELD） problems of power system. The simple framework of the basic particle swarm optimization （PSO） algorithm is maintained in the proposed algorithm. During the course of optimization, the approximate solution, namely the best locations the particles have visited, can be obtained by PSO algorithm. Then the accurate optimal solutions can be reached using chaotic optimization, which locally exploit the neighborhood of the approximate solutions according to the rules of chaotic motion. The simulation results of several examples show that the proposed algorithm for ELD problems can acquire the accurate optimal solutions rapidly.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2007年第2期114-119,共6页
Proceedings of the CSU-EPSA
关键词
电力系统
经济负荷分配
混沌优化
粒子群优化算法
混沌粒子群优化
power system
economic load dispatch（ELD）
chaotic optimization
particle swarm optimization （PSO） algorithm
chaotic particle swarm optimization（CPSO）
