基于多目标人工搜索群算法的分布式电源优化  

Distributed generation optimization based on multi-objective artificial searching swarm algorithm

作　　者：周小婷 陈堂功[1,2] 范佳莹[1] 吕殿利[1,2] 王梦莹 Zhou Xiaoting;Chen Tanggong;Fan Jiaying;Lv Dianli;Wang Mengying(State Key Laboratory of Reliability and Intelligence of Electrical Equipment,Hebei University of Technology,Tianjin 300130,China;Key laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province,Hebei University of Technology,Tianjin 300130,China)

机构地区：[1]河北工业大学省部共建电工装备可靠性与智能化国家重点实验室,天津300130 [2]河北工业大学河北省电磁场与电器可靠性重点实验室,天津300130

出　　处：《电测与仪表》2021年第2期34-39,共6页Electrical Measurement & Instrumentation

基　　金：河北省科技计划项目(16214528)。

摘　　要：分布式电源优化是配电网规划的重要环节,多目标优化算法是该环节的关键因素,目前用于解决这类问题的算法大都将多目标转化为单目标,一定程度上忽略了各目标间的相关性。为解决该问题,提出了一种改进人工搜索群算法,结合Pareto理论,针对每个优化目标并行搜索寻优,配合构建外部存档集,做到对各个目标之间关系的协调,解决了人工搜索群算法不能处理多目标优化问题的缺陷。针对改进算法存在的收敛精度不高,容易陷入早熟的情况,引入动态参数进行调整,改善了算法性能。最后以30节点系统为例,建立了考虑DG投资运行成本、有功网损及节点电压偏移的多目标优化模型,利用改进算法完成优化,通过与粒子群算法的效果对比,验证了算法的有效性。The optimal allocation of distributed generation is an important part of distribution network planning and multiobjective optimization algorithm is the key factor of this link.Most of the algorithms currently used to solve such problems convert multiple goals into single goals,and to some extent,the correlation between the targets is ignored.To solve this problem,an improved artificial searching swarm algorithm is proposed in this paper.Combined with the Pareto theory,parallel search optimization is optimized for each optimization target,and the external archive set is constructed to coordinate the relationship between the targets.The defect that the manual search group algorithm cannot handle the multi-objective optimization problem is solved.The introduction of dynamic parameters is to improve the poor convergence performance and the situation which is easy to fall into premature.Finally,taking the 30-node system as an example,a multi-objective optimization model considering DG investment operation cost,active network loss and load node voltage offset is established.The improved algorithm is adopted to complete the optimization.The effectiveness of the algorithm is verified by comparison with the particle swarm optimization algorithm.

关 键 词：人工搜索群算法 多目标优化 分布式电源 有功网损 电压偏移 

分 类 号：TM731[电气工程—电力系统及自动化]