改进蜘蛛群优化算法的分布式电源优化配置  

Optimal Allocation of Distributed Generation Based on Improved Spider Swarm Optimization Algorithm

作　　者：李晓东 吴孔平[1] 马文飞[1] 张洪斌 LI Xiaodong;WU Kongping;MA Wenfei;ZHANG Hongbin(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China)

机构地区：[1]安徽理工大学电气与信息工程学院

出　　处：《安徽理工大学学报（自然科学版）》2019年第5期48-53,共6页Journal of Anhui University of Science and Technology:Natural Science

基　　金：安徽省高校优秀人才培育基金资助项目(gxfx ZD2016077)

摘　　要：针对分布式电源定容选址问题,提出了一种改进蜘蛛群优化算法,并将遗传算法中的变异环节引入蜘蛛群算法中,加强了算法的全局搜索能力,并对分布式电源定容选址过程中的约束问题提出了一种自适应罚函数,避免了罚函数设置不恰当导致算法前期搜索时罚函数达不到惩罚作用或后期影响算法的边界搜索等问题的出现,最后在考虑电源出力的时序性的条件下用IEEE33节点配电网络进行验证上述所提方法,其结果表明所得分布式电源定容选址方案有效的改善了配电网的线路损耗、节点电压和快速电压稳定指数,同时表明的搜索算法和罚函数的有效性。Aiming at the problem of distributed power source location selection, an improved spider group optimization algorithm is proposed, and the mutation link in the genetic algorithm is introduced into the spider group algorithm, which enhances the global search ability of the algorithm and meanwhile selects the distributed power source. The constraint problem in the address process proposes an adaptive penalty function, which avoids the problem that the penalty function is not properly set, leading to the penalty function of the algorithm in the early searchor the boundary search of the later influence algorithm. The IEEE 33-node distribution network was used to verify the above proposed method under the conditional timing conditions. The results show that the distributed power supply fixed-capacity location scheme effectively improves the line loss and node voltage of the distribution network and the Fast voltage stability index, and indicates the effectiveness of the search algorithm and penalty function.

关 键 词：分布式电源 改进蜘蛛群优化算法 网损 电压质量 自适应罚函数 快速电压稳定指数 

分 类 号：TM71[电气工程—电力系统及自动化]