基于SAPSO的梯级水电站中长期优化调度  

Long-term Optimal Operation of Cascade Hydropower Stations Based on Self-adaptive Particle Swarm Optimization Algorithm

作　　者：董新亮[1] 马光文[1] 黎凯[2] 张秋菊[1] 

机构地区：[1]四川大学水电学院,成都610065 [2]四川省水利勘测设计研究院,成都610072

出　　处：《中国农村水利水电》2008年第7期103-105,共3页China Rural Water and Hydropower

基　　金：国家自然科学基金项目(50539140);国家自然科学基金项目(50679098)

摘　　要：针对粒子群算法存在早熟收敛现象和后期振荡现象,给出一种动态改变惯性权的自适应粒子群算法[1]。该算法原理简单,易编程实现,占用计算机内存少,能以较快的速度收敛到全局最优解,从而为梯级水电站中长期优化调度问题提供了一种有效的解决办法。To solve the premature convergence problem and late-time oscillation problem of the particle swarm optimization（PSO）, a self-adaptive particle swarm optimization（SAPSO） algorithm with dynamically changing inertia weight（DCW） is presented in this paper. This method is simple and can easily be programmed, and lower memory requirements with faster speed to converge the fullscale optimization results. Therefore, an effective method is put forward for medium and long- term optimal operation of cascade hydropower stations.

关 键 词：中长期优化调度 SAPSO 梯级水电站 

分 类 号：TV737[水利工程—水利水电工程]