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改进粒子群优化算法在负荷经济分配中的应用 被引量:70

APPLICATION OF IMPROVED PARTICLE SWARM OPTIMIZATION IN ECONOMIC DISPATCHING
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摘要 提出了一种求解电力系统负荷经济分配问题的改进粒子群优化算法。该算法考虑了机组的爬坡约束、出力限制区约束、非光滑费用函数曲线等非线性特性,用保留可行解的方法处理负荷平衡约束条件,用自适应罚函数法处理爬坡和出力限制区约束条件,加快了算法的收敛速度,对不活动粒子的处理使算法避免了“早熟”现象。仿真计算表明,改进粒子群优化算法是一种求解负荷经济分配问题的有效方法。 An improved particle swarm optimization (PSO) algorithm to solve the economic dispatch (ED) problem in power system is proposed. In the proposed algorithm the non-linear characteristics, such as ramp constraints of the generating units, output restricted zone and non-smooth cost functions, are considered. The constraints of load equalization are processed by reserving feasible solutions and the ramp constraints as well as output restricted zone constraint are processed by employing adaptive penalty function to accelerate the convergence speed of the algorithm, and the prematurity is avoided by reinitializing the inactive particle. Simulation results show that the improved PSO algorithm is an effective approach to solve the economic dispatching.
出处 《电网技术》 EI CSCD 北大核心 2005年第2期1-4,共4页 Power System Technology
基金 "973"重点基础研究发展计划资助项目(2003CB415200)~~
关键词 负荷经济分配 电力系统 粒子群优化算法 出力 机组 非线性特性 有效方法 约束 自适应 可行解 Algorithms Computer simulation Constraint theory Convergence of numerical methods Economics Electric power systems Problem solving
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