基于改进粒子群算法的分布式光伏集群划分与 无功优化策略  

Distributed Photovoltaic Cluster Partition and Reactive Power Optimization Strategy Based on Improved Particle Swarm Optimization Algorithm

作　　者：胡雪凯 尹瑞 时珉 朱鹏程[3] 李铁成 王一峰 胡鹏飞[3] HU Xuekai;YIN Rui;SHI Min;ZHU Pengcheng;LI Tiecheng;WANG Yifeng;HU Pengfei(Electric Power Research Institute of State Grid Hebei Electric Power,Shijiazhuang 050021,China;State Grid Hebei Electric Power,Shijiazhuang 050021,China;Zhejiang University,Hangzhou 310024,China)

机构地区：[1]国网河北省电力有限公司电力科学研究院,石家庄050021 [2]国网河北省电力有限公司,石家庄050021 [3]浙江大学,杭州310024

出　　处：《电力电容器与无功补偿》2021年第4期14-21,共8页Power Capacitor & Reactive Power Compensation

基　　金：河北省电力公司科技项目“分布式光伏发电集群灵活并网群调群控关键技术研究”的资助

摘　　要：分布式光伏系统在电网中的应用越来越广泛,光伏波动性强,稳定性差,其大规模接入不仅增加了配电网结构的复杂性,而且使电力系统的调节更加困难,给电网运行带来不利的影响。本文主要研究了含大规模分布式电源配电网的集群划分和无功优化问题。首先应用PSO改进的K-means聚类算法,找出较好的初始聚类中心,然后根据节点间的电气距离,对配电网进行集群划分。以节点的电压偏移总量和线路的有功损耗最小作为目标,采用动态调整粒子群算法对电力系统进行无功优化。最后在Matlab平台上仿真验证了所提集群划分和无功优化方法的有效性。The application of distributed photovoltaic system in power grid is more and more extensive.The photovoltaic system has strong volatility and poor stability.Its large-scale access not only increases the complexity of distribution network structure,but also makes the adjustment of power system more difficult,which brings adverse effects to the operation of power grid.This paper mainly studies the cluster partition and reactive power optimization of distribution network with large-scale distributed generation.Firstly,the K-means clustering algorithm improved by PSO is applied to find the better initial clustering center,and then the distribution network is divided into clusters according to the electrical distance between nodes.Aiming at minimizing the total voltage offset of nodes and the active power loss of lines,the dynamic adjustment particle swarm optimization algorithm is used to optimize the reactive power of power system.Finally,the effectiveness of the proposed method is verified by simulation on MATLAB platform.

关 键 词：分布式能源 集群划分 无功优化 粒子群优化算法 

分 类 号：TM615[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]