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基于C-PSO的水火电混合电力系统电源规划 预览 被引量:3

Generation expansion planning of hydro-thermal mixed power system based on C-PSO
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摘要 提出了一种粒子群算法与遗传算法结合的组合粒子群算法,并将其用于求解复杂的、非线性的水火电混合电力系统电源规划问题。该结合算法引入的遗传算法成功地提高了基本粒子群算法的全局搜索能力。同时也比基本遗传算法的收敛速度更快。算例结果表明:对于短期规划,该算法能可靠、快速地收敛到全局最优解,对于大型电力系统的中长期电源规划问题也可得到较好解。 A composite particle swarm optimization algorithm(C-PSO) in which the particle swarm optimization (PSO) is integrated with genetic algorithm (GA) is proposed and applied to a complicated and nonlinear generation expansion planning of hydro-thermal mixed power system. This integrated algorithm improves the global search ability of PSO, and the convergence speed is faster than GA. Case analysis result shows clearly that this algorithm can reliably and fast search for global optimal solution in short-term planning. To solve the problems of large scale and long-term generation expansion planning of power system, it is feasible as well.
作者 吴耀武 王峥 唐权 熊信银 娄素华 WU Yao-wu, WANG Zheng, TANG Quan, XIONG Xin-yin, LOU Su-hua ( 1. College of Electric and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; 2. East China Grid Company Ltd, Shanghai 200002, China)
出处 《继电器》 CSCD 北大核心 2006年第9期 64-69,共6页 Relay
关键词 水火电混合 组合粒子群算法 加速变步长搜索法 可靠性计算 环保约束 hydro-thermal mixed C-PSO accelerated search method with variable step reliability evaluation environment constraint
作者简介 吴耀武(1963-),男,副教授,从事电力系统及其自动化等方面的科研和教学工作,研究方向为电力系统可靠性及电力系统最优规划。 王峥(1976-),男,工程师,从事电力系统规划工作。 唐权(1982-),男,硕士研究生,研究方向为电力系统电源规划,最优化理论在电力系统中的应用。E-mail:tangaaa@sina.com
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