Cluster Partition Method of Distributed Power Supply Based on Improved Particle Swarm Optimization Algorithm

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Cluster Partition Method of Distributed Power Supply Based on Improved Particle Swarm Optimization Algorithm

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[1]CHEN Jinghua,ZHANG Linjuan,LU Dan,et al.Cluster Partition Method of Distributed Power Supply Based on Improved Particle Swarm Optimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2023,44(05):77-85.[doi:10.13705/j.issn.1671-6833.2023.05.012]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 44卷 Number of periods: 2023 05 Page number: 77-85 Column: Public date: 2023-08-20

Title:: Cluster Partition Method of Distributed Power Supply Based on Improved Particle Swarm Optimization Algorithm

Author(s):: CHEN Jinghua¹; ZHANG Linjuan¹; LU Dan¹; GUO Pu¹; REN Junyue² ; LI Jingli²; LI Zhongwen²; 1. State Grid Henan Electric Power Company Economic and Technological Research Institute, Zhengzhou 450000, China; 2. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China)

Keywords:: cluster division; particle swarm algorithm; modularity; distributed generation; active power matching degree; reactive power matching degree

CLC:: TM734；TM615

DOI:: 10.13705/j.issn.1671-6833.2023.05.012

Abstract:: With the development of new power system construction, the proportion of grid-connected distributed power gradually increased. In order to solve the difficult problem of the regulation of distributed power in new distribution network, the improved particle swarm optimization algorithm was proposed to cluster the large-scale distributed power. Firstly, on the basis of the modularity division standard, the active power matching degree and reactive power matching degree of the group internal load were introduced, and the comprehensive performance indexes weighted by the three were proposed to construct the cluster division optimization model based on the comprehensive index system. Then the inertia weight dynamic decline strategy was used to improve the binary particle swarm optimization algorithm to make the inertia weight change dynamically, optimizing the updating process of particle position and velocity, and improving the optimization efficiency of particle swarm optimization algorithm. Finally, the improved binary particle swarm optimization algorithm was used to optimize the clustering optimization model based on the comprehensive index system. Based on this, cluster division of IEEE33 nodes and a 10 kV actual distribution network feeder system was carried out. The results showed that the cluster partitioning method based on the comprehensive index system could improve the active power matching degree and reactive power matching degree by about 30%, respectively, on the basis of keeping the modularity of the partitioning result basically unchanged. The improved particle swarm optimization algorithm had obvious effect on improving each index value of partitioning results.

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