基于小波分析和支持向量机的10kv配电网永暂故障识别

Yang Liu, Lisheng Li, Kai Chen, Linli Zhang, Shidong Zhang
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引用次数: 0

摘要

传统的自动合闸可能会对永久性故障进行合闸,在延时后不判断故障类型,造成严重后果。提出了利用断路器脱扣后的故障记录数据实时识别故障类型的方法。如果是暂态故障,则开关闭合;然后恢复供电。当确定为永久性故障时,将不关闭开关,等待维护。本文采用小波分析从故障记录数据中提取实时特征,然后利用支持向量机(SVM)模型进行永久故障和暂态故障的识别,避免了盲目自动重合闸。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Permanent and Transient Fault Identification for 10 kV Distribution Network Using Wavelet Analysis and Support Vector Machine
Conventional automatic closing may reclose on a permanent fault and cause severe consequences without judging the fault type after a delay. It is proposed to use the fault recording data after the circuit breaker trips to identify the types of faults in real-time. If it is a transient fault, the switch will be closed; then the power supply will be restored. While it is identified to be a permanent fault, the switch will not be closed and wait for maintenance. In this paper, wavelet analysis is adopted to extract real-time features from the fault recording data, and then the support vector machine (SVM) model is used to identify permanent and transient faults, which can avoid blind automatic reclosing.
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