基于5G的配电网智能故障诊断方法  

Intelligent fault diagnosis method of distribution network based on 5G

作　　者：闫明 郭文豪 胡永乐 覃团发[1,2] YAN Ming;GUO Wenhao;HU Yongle;QIN Tuanfa(School of Computer and Electronic Information,Guangxi University,Nanning 530004,China.;Guangxi Key Laboratory of Multimedia Communications and Network Technology,Nanning 530004,China.;Runjian Co.,Ltd.,Nanning 530007,China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004 [2]广西多媒体通信与网络技术重点实验室,南宁530004 [3]润建股份有限公司,南宁530007

出　　处：《电测与仪表》2024年第4期15-20,共6页Electrical Measurement & Instrumentation

基　　金：国家自然科学基金资助项目(61563004,61761007);广西研究生教育创新计划资助项目(YCSW2020061)。

摘　　要：配电网是电网中发生短路故障最多且智能化程度较低的地方。目前主要使用基于零序电流比幅法来进行接地故障的故障诊断,但存在非接地故障识别率低和无法快速识别等问题。采用5G通信技术,提出三序复合电流检测法并结合广义回归神经网络(GRNN,generalized regression neural network)来实现配电网故障诊断的实时传输与快速决策。测试结果表明可提升非接地故障的识别率达20%以上,解决了以往通信不可靠和故障诊断智能化不高等问题。Distribution network is the place with the most short circuit faults and low degree of intelligence.At present,the zero-sequence current amplitude comparison method is mainly used for fault diagnosis of grounding fault,but there are some problems such as low recognition rate of non-grounding fault and unable to identify quickly.5G communication technology is adopted,three-sequence composite current detection method is proposed,and generalized regression neural network(GRNN)is combined to realize real-time transmission and rapid decision-making of fault diagnosis in distribution network.The test results show that the recognition rate of non-grounding fault can be improved by more than 20%,which solves the problems of unreliable communication and low intelligent fault diagnosis.

关 键 词：5G GRNN 三序复合电流检测法 配电网 故障诊断 

分 类 号：TM930[电气工程—电力电子与电力传动]