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基于希尔伯特-黄变换的新型配电系统行波故障定位仿真研究 被引量:4

Simulation study on traveling wave fault location of new distribution network system based on Hilbert-Huang transform
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摘要 “双碳”背景下的新型配电系统中,故障快速定位和恢复愈发重要。针对配电网多支路和故障行波的波头时间难以在时域精确捕捉的问题,提出了一种基于希尔伯特-黄变换(Hilbert-Huang transform,HHT)和多分支配电网D型行波测距原理的故障定位方法。HHT包括经验模态分解和希尔伯特变换2个重点流程。首先,采用故障电流行波信号的经验模态分解获得其固有模态函数,再经过希尔伯特变换获取其瞬时频谱分布图(即希尔伯特谱);然后,以希尔伯特谱中的首个突变点确定初始行波到达各测量点的时刻;最后,基于配电网D型行波测距原理测算获得故障距离。仿真结果表明,此方法能够实现精准的故障定位且不受故障点接地电阻影响。 The rapid fault location and recovery of new distribution systems in the context of dual carbon is becoming increasingly important.In this paper,a fault location method based on the Hilbert-Huang transform(HHT)and the principle of multi-branch distribution network D traveling wave ranging is proposed to solve the problem that the wave head time of multi-branch and fault traveling wave in the distribution network is difficult to accurately capture in the time domain.Firstly,the empirical mode decomposition(EMD)of fault current traveling wave signal is used to obtain its intrinsic mode function(IMF);The instantaneous spectrum distribution(Hilbert spectrum)is obtained by Hilbert transform;Then the time when the initial traveling wave reaches each measuring point is determined by the first abrupt point in the Hilbert spectrum;Finally,the fault distance is calculated based on the D-type traveling wave fault location principle of distribution network.The simulation results show that this method can achieve accurate fault location without being affected by the grounding resistance of the fault point.
作者 王凯亮 曾远方 李家淇 雷一 李海波 蒋宗南 WANG Kailiang;ZENG Yuanfang;LI Jiaqi;LEI Yi;LI Haibo;JIANG Zongnan(Dongguan Power Supply Bureau,Guangdong Power Grid Corporation,Dongguan 523120,China;Sichuan Energy Internet Research Institute,Tsinghua University,Chengdu 610200,China)
出处 《供用电》 2023年第9期43-49,共7页 Distribution & Utilization
基金 广东电网有限责任公司项目(0319002022030201JF00039)。
关键词 希尔伯特-黄变换 配电网 故障定位 行波测距 经验模态分解 Hilbert-Huang transform(HHT) distribution network fault location travelling wave ranging empirical mode decomposition
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