%0 Journal Article
%T Dynamic double-population particle swarm optimization algorithm for power system unit commitment<br>电力系统机组组合问题的动态双种群粒子群算法
%A LI Dan
%A GAO Li-qun
%A WANG Ke
%A HUANG Yue
%A <br>李丹
%A 高立群
%A 王珂
%A 黄越
%J 计算机应用
%D 2008
%I 
%X Dynamic Double-population Particle Swarm Optimization (DDPSO) algorithm was presented to solve the problem that the standard PSO algorithm easily fell into a locally optimized point, where the population was divided into two sub-populations varying with their own evolutionary learning strategies and exchanging between them. The algorithm had been applied to power system Unit Commitment (UC). The DDPSO particle consisted of a two-dimensional real number matrix representing the generation schedule. According to the proposed coding manner, the DDPSO algorithm could directly solve UC. Simulation results show that the proposed method performs better in term of precision and convergence property.
%K particle swarm optimization
%K dynamic double-population
%K learning strategy
%K unit commitment<br>粒子群优化
%K 动态双种群
%K 学习策略
%K 机组组合
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=6135561A65FF0B99AF03F262B3CDA717&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=CA4FD0336C81A37A&sid=DBF54A8E2A721A6D&eid=D767283A3B658885&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7