Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于多维数据的线路电压互感器在线监测技术研究

来源:电工电气发布时间:2022-07-18 13:18 浏览次数:291

基于多维数据的线路电压互感器在线监测技术研究

徐卫东,何文志,廖肇毅,刘勤锋
(广东电网有限责任公司东莞供电局,广东 东莞 523000)
 
    摘 要:针对线路电压互感器电压波动受运行方式、负荷大小、线路长度等客观因素的影响,从利用在线监测技术替代线路电压互感器传统停电预试进行研究。通过研究 110 kV 及以上输电线路首末两端电压互感器实时采集数据,以及电压偏差范围,采用神经网络算法对不同运行工况下的输电线路电压偏差进行自适应学习。结果表明,线路首末两端电压偏差符合正态分布曲线规律,神经网络方法制定输电线路首末两端电压互感器的告警规则更加合理,经故障案例验证,证明线路首末两端电压互感器电压阈值设定的准确性,完善了电压互感器在线监测阈值设定的空缺。
    关键词: 电压互感器;神经网络;误差分析;在线监测
    中图分类号:TM451     文献标识码:A     文章编号:1007-3175(2022)07-0050-06
 
Research on Online Monitoring Technology of Line Voltage
Transformer Based on Multi-Dimensional Data
 
XU Wei-dong, HE Wen-zhi, LIAO Zhao-yi, LIU Qin-feng
(Dongguan Power Supply Bureau of Guangdong Power Grid Co., Ltd, Dongguan 523000, China)
 
    Abstract: The voltage fluctuation of the line voltage transformer is affected by objective factors, such as operation mode, load size, line length, etc. This paper studied the perspective of using online monitoring technology to replace the traditional power failure pre-test technology of line voltage transformers. It collected real-time data and voltage deviation range by studying the initial and ending of the voltage transformer of 110 kV and above. Moreover, it used the neural network algorithm to self-adaptive learn the voltage deviation of the transmission line under different operating conditions.The results showed that the voltage deviation of the initial and ending of the circuit matched the normal distribution curve law, and the alarm rules formulated by the neural network method was more reasonable. The fault case verification proves the accuracy of the voltage threshold setting of the voltage transformers and completes the vacancy of the voltage transformer online monitoring threshold setting.
    Key words: voltage transformer; neural network; error analysis; online monitoring
 
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