改进遗传算法在分布式电源选址定容中的应用

提出了基于节点号的Prüfer数编码遗传算法用于分布式电源的选址定容和配电网结构协同优化规划。利用图论生成配电网运行时理论上可行的树型拓扑结构对其按Prüfer数原理编码；用整数编码方式对分布式电源的接入节点和安装容量进行编码使配电网的结构优化和分布式电源选址定容合并为同一染色体基因的进化问题。此编码方法使染色体长度比支路开关二进制编码方式缩短；利用Prüfer数编码的优点对算法中交叉、变异操作进行一定的限制和改进解决了其他编码方式在交叉、变异过程中容易产生非法解及修复难的问题提高了算法效率和收敛速度。最后通过实例计算验证了此算法的可行性和优越性。

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.