基于长短期记忆网络的继电保护测试故障诊断研究  

Fault diagnosis of a relay protection test based on a long short-term memory network

作　　者：陈桂芳 董秀成 郑永康 徐洪海 CHEN Guifang;DONG Xiucheng;ZHENG Yongkang;XU Honghai(School of Electrical&Electronic Information,Xihua University,Chengdu 610039,China;State Grid Sichuan Electric Power Research Institute,Chengdu 610041,China;Jiangsu Hongyuan Electric Co.,Ltd.,Nanjing 211103,China)

机构地区：[1]西华大学电气与电子信息学院,四川成都610039 [2]国网四川省电力公司电力科学研究院,四川成都610041 [3]江苏宏源电气有限责任公司,江苏南京211103

出　　处：《电力系统保护与控制》2022年第5期65-73,共9页Power System Protection and Control

基　　金：国家自然科学基金项目资助(11872069);四川省中央引导地方科技发展专项资助(2021ZYD0034);四威高科-西华大学产学研联合实验室资助(2016-YF04-00044-JH)。

摘　　要：为提高智能变电站继电保护测试效率,解决数字式继电保护试验装置无法对整个测试过程中出现的故障自动进行诊断的问题,提出基于长短期记忆(Long Short-Term Memory, LSTM)网络的继电保护测试故障诊断方法。梳理了故障断面特征信息和故障类别,建立了多故障诊断模型,构建了故障诊断流程。以典型220 kV继电保护测试为例,通过将LSTM与循环神经网络、BP网络和深度神经网络进行对比,得到输入实际故障信息和部分不可靠信息时LSTM模型的三项评价标准(平均绝对误差、准确率和综合评价指标)值均最优。通过实验仿真验证了基于LSTM网络的继电保护测试故障诊断方法具有较高的精度与良好的容错性能。The efficiency of intelligent substation relay protection test needs improvement. There is also a problem in that a digital relay protection test device cannot automatically diagnose faults during the whole test process. Thus a relay protection test fault diagnosis method based on long short-term memory(LSTM) network is proposed. In this paper, the fault section characteristic information and fault categories are first established. Then a multi-fault diagnosis model is established, and a fault diagnosis process is constructed. Taking the typical 220 kV relay protection test as an example, by comparing LSTM with cyclic neural, a BP and a deep neural networks, the three evaluation criteria(mean absolute error,accuracy and comprehensive evaluation index) of the LSTM model are found to be optimal when the actual fault information and partial unreliable information are two different inputs. Simulation results show that the relay protection test fault diagnosis method based on the LSTM network has high precision and good fault-tolerant performance.

关 键 词：智能变电站 继电保护测试 数字式继电保护试验装置 长短期记忆网络 故障自动诊断 

分 类 号：TM77[电气工程—电力系统及自动化] TM63[自动化与计算机技术—控制理论与控制工程] TP183[自动化与计算机技术—控制科学与工程]