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求解机组组合问题的改进离散粒子群算法
引用本文:刘涌,侯志俭,蒋传文.求解机组组合问题的改进离散粒子群算法[J].电力系统自动化,2006,30(4):35-39.
作者姓名:刘涌  侯志俭  蒋传文
作者单位:上海交通大学电子信息与电气工程学院,上海市,200030
摘    要:电力系统机组组合问题是一个高维数、离散、非线性的大规模复杂工程优化问题.文中提出了一种基于改进离散粒子群优化算法求解机组组合问题的新方法.首先采用新的策略生成粒子,以保证所有生成的粒子均为满足基本约束条件的可行解,使整个算法只在可行解区域进行优化搜索;然后引入优化窗口的概念和启发式的规则以缩短计算时间和提高优化精度.仿真结果表明所提出的算法具有解的质量高、收敛速度快的特点,充分证明了它能很好地解决机组组合问题.

关 键 词:机组组合  离散粒子群优化算法  优化窗口  启发式规则
收稿时间:2005-09-20
修稿时间:2005-09-20

Unit Commitment via an Enhanced Binary Particle Swarm Optimization Algorithm
LIU Yong,HOU Zhi-jian,JIANG Chuan-wen.Unit Commitment via an Enhanced Binary Particle Swarm Optimization Algorithm[J].Automation of Electric Power Systems,2006,30(4):35-39.
Authors:LIU Yong  HOU Zhi-jian  JIANG Chuan-wen
Affiliation:Shanghai Jiaotong University, Shanghai 200030, China
Abstract:Unit commitment is a large scale, discrete and non-linear optimization problem. A solution to unit commitment via an enhanced binary particle swarm optimization (BPSO) algorithm is presented. A new strategy for particles generation is proposed which can make all the particles feasible and narrow the search space within the feasible solutions. Optimization window and heuristic rules are introduced into the methodology to improve the speed and the solution precision. The simulation results clearly show that the proposed method is effective.
Keywords:unit commitment  binary particle swarm optimization (BPSO) algorithm  optimization window  heuristic rule
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