分布式能源2025，Vol.10Issue(2)：98-108,11.DOI:10.16513/j.2096-2185.DE.(2025)010-02-0098-11
含光伏电源的低压配电网漏电故障识别与触电电流检测
Leakage Fault Identification and Touch Current Extraction in Low-Voltage Distribution Networks With Photovoltaic Power Supply
摘要
Abstract
In low-voltage distribution networks with large-scale integration of distributed photovoltaic(PV)systems,existing residual current devices(RCDs)cannot distinguish between abnormal PV leakage currents and electric shock currents in residual current circuits,leading to frequent misoperations.This poses risks to electrical safety and power supply reliability.To solve this problem,this study proposes a leakage fault identification method based on support vector machine(SVM)and an electric shock current detection method based on extreme gradient boosting(XGBoost).Firstly,variational mode decomposition(VMD)is used to extract components of residual current signals under different leakage scenarios,establishing a fault feature dataset.Then,using these features as input,an SVM model optimized by the sparrow search algorithm(SSA)is developed to identify leakage fault types.For cases where residual currents fail to reflect real electric shock conditions,an XGBoost regression model optimized by grid search and cross-validation(GSCV)is built to accurately extract electric shock currents from residual currents.Test results show that compared to standard SVM and kernel extreme learning machine(KELM)models,the SSA-SVM model achieves the highest leakage fault identification accuracy,with an average of 99.28%.The GSCV-XGBoost model accurately fits the extracted electric shock currents to real values.This work provides a theoretical basis for developing new RCDs with leakage fault identification and electric shock current detection capabilities.关键词
剩余电流装置(RCD)/光伏漏电流/漏电故障识别/触电电流检测/分布式光伏并网Key words
residual current device(RCD)/photovoltaic leakage current/leakage fault identification/touch current extraction/distributed photovoltaic grid connection分类
能源与动力引用本文复制引用
刘晗,刘金东,黄鹤鸣,张莹,王帅,吴杰,池海御..含光伏电源的低压配电网漏电故障识别与触电电流检测[J].分布式能源,2025,10(2):98-108,11.基金项目
国网北京市电力公司科技项目(520213240001)This work is supported by Science and Technology Project of State Grid Beijing Electric Power Company(520213240001) （520213240001）
