文章摘要
韦明杰,张恒旭,石访,等.基于谐波能量和波形畸变的配电网弧光接地故障辨识[J].电力系统自动化,2019,43(16):148-154. DOI: 10.7500/AEPS20180912005.
WEI Mingjie,ZHANG Hengxu,SHI Fang, et al.Identification of Arcing Grounded Fault in Distribution Network Based on Harmonic Energy and Waveform Distortion[J].Automation of Electric Power Systems,2019,43(16):148-154. DOI: 10.7500/AEPS20180912005.
基于谐波能量和波形畸变的配电网弧光接地故障辨识
Identification of Arcing Grounded Fault in Distribution Network Based on Harmonic Energy and Waveform Distortion
DOI:10.7500/AEPS20180912005
关键词: 配电网  弧光接地故障  高阻故障  归一化谐波能量  随机性  波形畸变
KeyWords: distribution network  arcing grounded fault(AGF)  high impedance fault  normalized harmonic energy  randomness  waveform distortions
上网日期:2019-07-09
基金项目:国家重点研究发展计划资助项目(2017YFB0902800);国家电网公司科技项目(52094017003D)
作者单位E-mail
韦明杰 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061  
张恒旭 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061  
石访 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061 shifang@sdu.edu.cn 
谢伟 国网上海市电力公司, 上海市 200233  
张勇 国网上海市电力公司, 上海市 200233  
方陈 国网上海市电力公司, 上海市 200233  
摘要:
      配电网弧光接地故障会产生严重的弧光过电压并释放大量热能,从而造成设备损坏,引发火灾并危害人员生命安全。针对传统电弧模型无法正确描述电弧不稳定燃烧过程中的间歇性燃熄弧和随机波动等问题,提出了基于随机控制变量的改进Mayr电弧模型;通过对故障特征的分析,提出归一化谐波能量描述方法,实现了包括高阻故障在内的不同接地故障情况下谐波含量的一致性描述和整定,并根据归一化谐波能量在时间尺度上的随机分布特性以及故障波形畸变特征,实现对弧光接地故障的准确辨识。最后,结合配电网新型智能测量终端的发展应用,提出基于三相电压和零序电流录波数据的弧光接地故障综合辨识算法,并通过PSCAD仿真算例和某10 kV配电网的实测故障试验数据对算法的可靠性和安全性进行验证。
Abstract:
      Arcing grounded faults(AGFs)happening in the distribution network can produce great arcing over-voltage and release considerable heat, resulting in equipment damages, fire hazards and human injuries. For the problem that traditional arc models cannot accurately describe the intermittence and randomness during the unstable arcing period, an improved Mayr arc model based on the random control variables is proposed. By analyzing the fault features, a description method of normalized harmonic energy is proposed to unify the quantitative description and threshold setting with different types of grounded faults, including the high impedance faults. Moreover, the characteristics of random of distribution in the time domain and the fault waveform distortions for normalized harmonic energy are utilized to realize the detection and distinction of AGFs. An integrated detection algorithm of AGFs is exhibited, according to the recording data of three-phase voltage and zero-sequence current with the prospectively applied phasor measurement units(PMUs)in the distribution network. Finally, the reliability and security of the algorithm are analyzed with simulations in PSCAD and field examinations of a 10 kV distribution network.
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