适用于配电网无功优化的混合鱼群算法  

A Hybrid Fish Swarm Algorithm for Reactive Power Optimization in Distribution Networks

作　　者：管恩齐 何晋[1] 骆通 GUAN Enqi;HE Jin;LUO Tong(School of Electrical Information Engineering,Yunnan Minzu University,Kunming 650000)

机构地区：[1]云南民族大学电气信息工程学院,昆明650000

出　　处：《计算机与数字工程》2024年第4期1205-1209,1256,共6页Computer & Digital Engineering

基　　金：云南省教育厅科学研究基金项目(编号:2021Y654)资助。

摘　　要：人工鱼群算法同传统群智能算法一样,由于基础种群的随机性以及寻优路线的不确定性等原因可能导致算法寻不到最优解。为解决以上问题,利用混沌变换序列生成遍布更加均匀的初始值;采用自适应的视野与步长动态改变搜索范围;引入改进的生物“进化”机制,利用当代和精英个体的基因来对鱼群进行淘汰,加快收敛速度。将该混合算法用于IEEE33节点系统配电网的无功优化中,结果表明改进的算法更易跳出局部最优,且收敛速度较快,收敛性能较好,提高了寻优效率。The artificial fish swarm algorithm is the same as the traditional swarm intelligence algorithm.Because of the ran-domness of the basic population and the uncertainty of the optimization route,the algorithm may not find the optimal solution.In or-der to solve the above problems,chaotic sequence is used to generate more uniform initial values.The adaptive field of view and step size are used to dynamically change the search range.An improved biological"elimination"mechanism is introduced,and the genes of contemporary and elite individuals are used to eliminate the fish schools and speed up the convergence.The hybrid algo-rithm is used in the reactive power optimization of the IEEE33-bus system distribution network.The results show that the improved algorithm is easier to jump out of the local optimum,and the convergence speed is faster,the convergence performance is better,and the optimization efficiency is improved.

关 键 词：人工鱼群算法 混沌变换 自适应 进化机制 无功优化 

分 类 号：TM727[电气工程—电力系统及自动化]