电力系统保护与控制2012，Vol.40Issue(10)：42-47,6.
基于多Agent粒子群优化算法的电力系统经济负荷分配
An economic load dispatch method of power system based on multi-Agent particle swarm optimization algorithm
摘要
Abstract
An improved multi-Agent particle swarm optimization algorithm (RN-MAPSO) based on multi-Agent system competition and collaboration mechanism is proposed for solving the discontinuous, non-convex and nonlinear economic load dispatch(ELD) problems of power system. The algorithm combines the swarm search feature of the PSO with the intelligent search feature of the agent based on the particle swarm optimization algorithm and technology of agent. In the search process, each agent is treated as one particle of PSO that can take advantage of the group information and the environmental information to determine the search tactics. By competition and cooperation with the randomly selected neighbors, the agent can adaptively adjust its global searching ability and local exploring ability, and converge the global optimal solution more accurately at higher speed. To verify the effectiveness of the proposed algorithm, RN-MAPSO is tested in the IEEE 3 nodes, 13 nodes and 40 nodes system and the experiment results show that the proposed algorithm for ELD problems can acquire high-quality solutions rapidly.This work is supported by National Natural Science Foundation of China (No. 60905066).关键词
电力系统/经济负荷分配/粒子群优化算法/多Agent系统/竞争/合作Key words
power system/ economic load dispatch (ELD)/ particle swarm optimization algorithm (PSO)/ multi-Agent system (MAS)/ competition/ cooperation分类
信息技术与安全科学引用本文复制引用
唐贤伦,张衡,李进,周维..基于多Agent粒子群优化算法的电力系统经济负荷分配[J].电力系统保护与控制,2012,40(10):42-47,6.基金项目
国家自然科学基金项目(60905066) （60905066）
重庆市自然科学基金项目(sstc2011jjA1313) （sstc2011jjA1313）
