基于5G的配电网智能故障诊断方法

闫明; 郭文豪; 胡永乐; 覃团发

闫明,郭文豪,胡永乐,覃团发.基于5G的配电网智能故障诊断方法[J].电测与仪表,2024,61(4):15-20.
YAN Ming,GUO Wenhao,HU Yongle,QIN Tuanfa.Intelligent fault diagnosis method of distribution network based on 5G[J].Electrical Measurement & Instrumentation,2024,61(4):15-20.

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

DOI：10.19753/j.issn1001-1390.2024.04.003

中文关键词: 5G GRNN 正、零序电流检测法配电网故障诊断

英文关键词:5G, GRNN, positive and zero sequence current detection method, distribution network, fault diagnosis

基金项目:国家自然科学基金（61563004），国家自然科学基金（61761007），广西研究生创新管理项目（YCSW2020061）

作者中文名	作者英文名	单位
闫明	YAN Ming	广西大学计算机与电子信息学院
郭文豪	GUO Wenhao	广西大学计算机与电子信息学院
胡永乐	HU Yongle	润建股份有限公司
覃团发	QIN Tuanfa	广西大学计算机与电子信息学院

摘要点击次数: 533

中文摘要:

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。

英文摘要:

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.

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