基于粒子群优化算法的输变电设备检修优化  

Particle Swarm Optimizer Based Maintenance Scheduling for Power Transmission and Transforming Equipments

作　　者：周刚[1] 王红斌[1] 

机构地区：[1]广东电网公司电力科学研究院,广州510080

出　　处：《南方电网技术》2013年第3期109-112,共4页Southern Power System Technology

摘　　要：传统的检修优化模型中,设备的检修状态变量采用0、1二元变量表示,无法用粒子群优化算法(PSO)求解。提出了一种新的输变电设备检修优化模型。该模型用整数表示检修状态变量,使得检修约束得以简化,有利于PSO的求解。仿真结果表明,与遗传算法(GA)相比,在该模型下PSO收敛速度更快,获得更优的解。The particle swarm optimizer （PSO） is unable for the traditional maintenance scheduling （MS） as its maintenance status variables of equipments are represented by 0 or 1 of binary number. This paper presents a novel model for maintenance scheduling （MS） for generators and transmission lines, in which the maintenance status variables are represented by integer numbers as to simplify maintenance constraints and favor PSO. The simulation results show that in comparison with the genetic algorithm （GA）, the PSO with the proposed scheduling can implement with fast convergence and achieve better solution.

关 键 词：输变电设备 检修优化 粒子群优化算法 遗传算法 

分 类 号：TM307.2[电气工程—电机] TM755