基于改进烟花算法的配电网优化重构  

Optimal reconfiguration of distribution network based on improved fireworks algorithm

作　　者：彭博 邹乐 李昕 张育臣 陈沐乐 谭大帅 PENG Bo;ZOU Le;LI Xin;ZHANG Yuchen;CHEN Mue;TAN Dashuai(State Grid Beijing Haidian Electric Power Supply Company,Beijing 100089,China;Dongfang Electronics Corporation,Yantai 264000,China)

机构地区：[1]国网北京海淀供电公司,北京100089 [2]东方电子股份有限公司,山东烟台264000

出　　处：《应用科技》2023年第4期84-89,共6页Applied Science and Technology

基　　金：山东省自然科学基金项目(ZR202103030510);国网北京市电力公司科技项目(SGBJHD00DQJS2100459)。

摘　　要：为了提高配电网重构效率,构建了降低网损和开关次数最少的多目标优化函数。同时为了解决求解过程中原始烟花算法和其他传统智能优化算法精度不高和求解速度慢的问题,提出了一种改进的烟花算法。算法采用实数编码减少变量维数,用环路开关数组确定烟花个体爆炸空间,减少了寻优中的无效搜索;引入柯西变异代替传统高斯变异,提出一种自适应爆炸半径和精英方向学习选择策略,大大提高了优化算法的求解速度和精度。以IEEE33节点系统为例进行仿真验证,仿真结果证明本文改进算法具有寻优速度快、寻优成功率高的优点。In order to improve the efficiency of distribution network reconfiguration,a multi-objective optimization function is constructed to reduce network loss and minimize switching times.In order to solve the problems of low accuracy and slow speed of the original fireworks algorithm and other traditional intelligent optimization algorithms,an improved fireworks algorithm is proposed.The algorithm adopts real number coding to reduce the variable dimension,and employs the loop switch array to determine the fireworks individual explosion space,so as to reduce the invalid search in the optimization.At the same time,by introducing Cauchy mutation to replace traditional Gaussian mutation,an adaptive explosion radius and an elite opposition-based learning selection strategy are proposed,which has greatly improved the solution speed and accuracy of the optimization algorithm.Finally,the IEEE33 bus system is taken as an example to verify that the improved algorithm has the advantages of fast optimization speed and high optimization success rate.

关 键 词：重构 多目标 改进烟花算法 最小网损 最少开关动作 配电网 优化 柯西变异 

分 类 号：TM732[电气工程—电力系统及自动化]