基于改进鲸鱼算法的分布式电源规划方法  

Planning method for distributed generation based on improved WOA

作　　者：于艾清 濮梦燕 王育飞 薛花 金彪 YU Aiqing;PU Mengyan;WANG Yufei;XUE Hua;JIN Biao(School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China)

机构地区：[1]上海电力大学电气工程学院,上海200090

出　　处：《电测与仪表》2024年第8期63-69,共7页Electrical Measurement & Instrumentation

基　　金：上海市科技创新行动计划项目(19DZ2204700,20DZ2205500)。

摘　　要：随着分布式电源并入配电网的比例不断增大,为了提高系统电压稳定性和经济性,文中提出了一种基于改进鲸鱼算法的分布式电源规划方法。利用拉丁超立方采样和改进的K-means聚类算法处理风、光和负荷的不确定性问题。提出一种负荷加权电压稳定指标来量化网络电压稳定性,再结合年综合费用建立分布式电源多目标规划模型。针对现有WOA算法在解决复杂规划问题方面的不足,引入对数权重距离控制因子和Nelder-Mead方法加快收敛速度,融合Pareto存档进化策略提高种群的多样性,在搜索中应用反向学习策略防止算法陷到局部最优。在IEEE 33节点系统上进行了仿真分析,结果表明所提模型与算法可行有效。As the proportion of distributed generation connected to the distribution network continues to increase,in order to improve the voltage stability and economy of the system,this paper proposes a planning method for distributed generation based on the improved whale optimization algorithm(WOA).Firstly,the Latin hypercube sampling and the improved K-means clustering algorithm are used to deal with the uncertainties of wind,light and load.Secondly,a load-weighted voltage stability index is proposed to quantify the network voltage stability,and then,combining with the annual comprehensive cost,a distributed power generation multi-objective planning model is established.Finally,in view of the shortcomings of the existing WOA algorithm in solving complex planning problems,the logarithmic weight distance control factor and the Nelder-Mead method are introduced to accelerate the convergence speed,and the Pareto archive evolution strategy is integrated to increase the diversity of the population.The opposition-based learning strategy is used in the searching process to prevent stuck into local minima.The simulation analysis on the IEEE 33-node system shows the effectiveness and feasibility of the proposed model and algorithm.

关 键 词：分布式电源 选址定容 电压稳定指标 K-MEANS聚类 鲸鱼优化算法 

分 类 号：TM715[电气工程—电力系统及自动化]