基于改进粒子群算法的低压配电网故障自动识别方法  

Automatic Fault Identification Method for Low-Voltage Distribution Network Based on Improved Particle Swarm Optimization Algorithm

作　　者：刘利军 LIU Lijun(Engineering Technology Research Center of Fukuang Group,Fushun,Liaoning 113008,China)

机构地区：[1]抚矿集团工程技术研究中心,辽宁抚顺113008

出　　处：《自动化应用》2023年第22期50-51,54,共3页Automation Application

摘　　要：传统的故障识别方法存在准确性低、效率低下的问题。为此,本文提出了一种基于改进粒子群算法的低压配电网故障自动识别方法。利用粒子群算法的全局搜索和优化能力,实现粒子群算法的快速收敛。采集低压配电网的运行信息并进行预处理,获得故障特征向量,并利用改进粒子群算法对特征向量进行优化搜索,实现快速准确的故障识别。此外,通过仿真实验验证了该方法的有效性和性能优势。The traditional fault identification method has some problems,such as low accuracy and low efficiency.Therefore,a low-voltage distribution network automatic fault identification method based on improved particle swarm optimization is proposed in this paper.The global search and optimization ability of particle swarm optimization algorithm is used to achieve rapid convergence of particle swarm optimization algorithm.The operation information of low-voltage distribution network is collected and preprocessed to obtain the fault feature vector,and the improved particle swarm optimization algorithm is used to search the feature vector to achieve fast and accurate fault identification.Additionally,the effectiveness and performance advantages of the proposed method are verified by simulation experiments.

关 键 词：低压配电网 故障识别 粒子群算法 优化搜索 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]