摘要
为了区分配电网中正常电流和交流串联故障的电弧电流,通过采集电弧电流和弧声超声波作为两个故障特征进行故障电弧的检测。根据UL-1699标准搭建串联故障电弧试验平台,采集不同负载在正常工作和发生故障电弧状态下的电流数据和超声波数据,对电弧电流数据进行2层小波分解,提取小波高频系数,计算小波高频系数的方差值作为故障特征。采集正常和故障情况的超声波,设置合理的阈值来区分故障电弧。结合电弧电流小波高频系数方差和弧声超声波读数可以准确地实现对故障电弧的识别,大大提高了识别串联故障电弧的准确度。
In order to distinguish the normal current and the alternating current series fault arc current in the power grid,the arc fault detection was carried out by collecting the arc current and the arc sound ultrasonic wave as two fault features.A series arc fault test platform was built according to the UL-1699 standard,the current data and ultrasonic data of different loads under normal operation and fault arc status were collected,2-layer wavelet decomposition was performed on the arc current data for extracting the high frequency coefficient of the waveletand calculating the variance value of wavelet high-frequency coefficient as fault feature.For the collected ultrasonic waves of normal and fault conditions,a reasonable threshold was set to distinguish the fault arc.Then,by combining the variance of the high frequency coefficient of the arc current wavelet and the ultrasonic reading of the arc sound,the identification of the fault arc can be accurately realized,which greatly improves the accuracy of identifying the series fault arc.
作者
舒奇航
刘希喆
王阳
Shu Qihang;Liu Xizhe;Wang Yang(School of Electric Power Enginering,South China University of Technology,Guangzhou Guangdong 510641,China;Guangdong Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid,Guangzhou Guangdong 510641,China)
出处
《电气自动化》
2023年第3期23-25,29,共4页
Electrical Automation
关键词
串联故障电弧
小波分解
弧声超声波
高频分量
电弧
series fault arc
wavelet decomposition
arc-acoustic ultrasonic wave
high-frequency component
electric arc