中压配电网优化规划的改进单亲遗传算法

配电网优化规划是一个多目标、不确定、多阶段的复杂系统优化问题,故提出了一种基于树形编码的中压配电网优化规划的改进单亲遗传算法。此算法结合实际配电网结构多为树形的特点进行编码,将染色体长度设定为用户(负荷)的节点数目。遗传操作采用交换变异和插入变异,并同时加强控制,修补染色体,避免了不可行解的产生,加快了算法的计算效率和收敛速度,并消除了早熟现象。以一个具有16节点的变电站算例,费时3.59 s,在60代左右收敛到最优解,验证了该算法的有效性和实用性,同时表明该算法也适用于配电网扩展规划。

Improved Partheno-Genetic Algorithm for Medium Voltage Distribution Network Optimal Planning

This paper presents an improved partheno-genetic algorithm based on spanning tree coding for medium voltage distribution network optimal planning.Considering that real distribution network just likes a spanning tree,the length of the chromosome is set equal to the number of customers or loads.Furthermore,two mutation methods are introduced,namely exchange mutation and insertion mutation.A control scheme along with genetic operation in evolution,which is used to repair chromosome,avoids unfeasible solution and accelerates computing efficiency and convergence speed.Therefore immature convergence is dispelled in this algorithm.The optimal result of a 16-bus test system is achieved using the proposed algorithm by costing 3.59s and iterating 60 times.The simulation results show that the algorithm is effective and practical,and can be applied to distribution network expansion planning.