摘要
将一种改进的遗传算法应用到配电网电容器的优化配置问题中。该算法将电容器的安装位置与安装容量视为离散变量,将电容器购买费用、安装费用、维护费用与系统有功损耗支出的总和最小作为目标函数,提出了两种实现思路。思路一:先在最大负荷下定出电容器的安装位置和各节点最大安装台数,然后在此基础上计算其他负荷下电容器的投切情况与固定电容器的数目,再定出总收益。思路二:先在最小负荷下计算出固定电容器的数目,然后在此基础上计算其他负荷下所需安装的可投切电容器数目再定出总收益。针对简单遗传算法的一些不足之处(如搜索效率不高和过早收敛),将遗传操作过程中的编码、选择、交叉、变异和终止条件进行了改进。最后将其应用到一个27节点的配电网络中,结果表明这两种思路都是合理可行的。
An improved genetic algorithm for capacitor placement optimization is presented and applied in distribution system. The algorithm considers the location and capability of the capacitor to be installed as discrete variables. The minimization of the sum of various costs, including purchasing cost, installation cost, maintenance cost and active power loss charge, is regarded as objective function. Two methods for solving this optimization problem are provided. The first one needs to determine the locations and the maximal bank sizes under the maximal load level, and then calculates the precise bank sizes of fixed capacitor with other load＇levels, thus the total income is determined. Differing from the former method, the other method determines the sizes of fixed capacitor banks under the minimal load level first, and then calculates the sizes of switched capacitor banks with other load level. Compared with the simple genetic algorithm, the presented algorithm makes improvements on coding, selection, crossover, mutation and termination condition during the process of evolution. Finally, a reasonable result is shown obtained by the proposed methods in a 27-bus distribution system
出处
《电力系统及其自动化学报》
CSCD
北大核心
2006年第5期89-94,共6页
Proceedings of the CSU-EPSA
关键词
电容器优化配置
配电网系统
遗传算法
capacitor placement optimization
distribution system
genetic algorithm
