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陈振宁,李勇汇,彭 辉,等. 基于零序电压小波包能量比的配网单相高阻接地故障辨识分析[J]. 科学技术与工程, 2020, 20(20): 8202-8209.
CHEN Zhen-ning,PENG Hui,et al.Identification Analysis of Single-phase High Resistance Earth Fault in Distribution Network Based on Wavelet Packet Energy Ratio of Zero Sequence Voltage[J].Science Technology and Engineering,2020,20(20):8202-8209.
基于零序电压小波包能量比的配网单相高阻接地故障辨识分析
Identification Analysis of Single-phase High Resistance Earth Fault in Distribution Network Based on Wavelet Packet Energy Ratio of Zero Sequence Voltage
投稿时间:2019-09-27  修订日期:2020-04-03
DOI:
中文关键词:  小波包能量比  高阻故障辨识  高频分量  暂态特征  适用性
英文关键词:wavelet packet energy ratio  high resistance fault identification  high frequency component  transient characteristics  applicability
基金项目:
           
作者单位
陈振宁 武汉大学电气与自动化学院
李勇汇 武汉大学电气与自动化学院
彭 辉 武汉大学电气与自动化学院
刘雯静 武汉大学电气与自动化学院
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中文摘要:
      配网高阻故障大多是架空线接触高阻抗物体引起的单相高阻接地故障,难以通过稳态特征进行识别。本文基于等值网络分析故障产生高频分量的原因并考虑了正常状态对辨识的影响,提出了一种基于零序电压小波包能量比的配网单相高阻接地故障辨识方法。利用小波包频段分解对零序电压进行能量特征提取,提取出低频段能量与高频段能量的比值作为高阻故障的识别特征量。基于某10 kV配电网对本文方法进行测试,通过BP神经网络的辨识对比结果,证实了方法的有效性;通过中性点接地方式、拓扑结构及故障条件变化等多种因素的分析及仿真,验证了方法的适用性。
英文摘要:
      Most of high resistance faults in distribution network are single-phase earth faults caused by overhead line contacting high impedance objects. These faults are difficult to identify by steady-state features. In this paper, the high frequency components of faults are analyzed based on equivalent network and the influence of normal state on identification are considered. An identification method of single-phase high resistance earth fault in distribution network based on wavelet packet energy ratio of zero sequence voltage is then proposed. Wavelet packet decomposition is used to extract energy features of zero sequence voltage. The ratio of energy in low-frequency band to energy in high-frequency band is used as the identification feature of high resistance faults. Based on a typical radial 10 kV distribution network, the performance of the proposed identification feature is evaluated. The validity of the method is evaluated by the identification and comparison results of BP neural network. The applicability of the method is verified by the analysis and simulation of different neutral grounding modes, different topologies and the change of fault conditions.
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