系统仿真学报 ›› 2016, Vol. 28 ›› Issue (5): 1225-1231.

• 短文 • 上一篇    下一篇

基于SRC和LCD的行波检测故障定位方法

高艳丰1,2, 朱永利1, 闫红艳2, 张媛媛1   

  1. 1.华北电力大学新能源电力系统国家重点实验室,河北 保定 071003;
    2.河北工程大学水电学院,河北 邯郸 056038
  • 收稿日期:2015-07-22 修回日期:2015-11-11 发布日期:2020-07-03
  • 作者简介:高艳丰(1979-),男,邯郸,博士生,讲师,研究方向为输电线路故障定位和电力系统运行、分析与控制。
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(2014xs74)

Traveling Wave Detection Fault Location Method Based on SRC and LCD

Gao Yanfeng1,2, Zhu Yongli1, Yan Hongyan2, Zhang Yuanyuan1   

  1. 1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University,Baoding 071003, China;
    2. Hebei University of Engineering, Handan 056038, China
  • Received:2015-07-22 Revised:2015-11-11 Published:2020-07-03

摘要: 故障行波检测的准确性是输电线路行波测距的关键之一。从减少量化误差着手,兼顾信号分解的真实性,提出一种基于采样率转换 (Sampling Rate Conversion, SRC)和局部特征尺度分解(Local Characteristic scale Decomposition, LCD)相结合的故障行波检测方法。对某一采样频率的电流线模分量进行采样率转换,实现对重构信号的重采样;对重采样信号进行局部特征尺度分解,利用Teager能量算子提取首个内禀尺度分量的瞬时频率,确定故障初始行波到达检测点的时刻;利用三测点行波定位算法计算故障点位置。仿真验证了该方法的正确性和准确性。

关键词: 输电线路, 行波测距, 量化误差, 采样率转换, 局部特征尺度分解

Abstract: The accuracy of fault detection by traveling wave is a key for distance measurement on transmission lines. A new traveling wave detection method was proposed based on SRC (Sampling Rate Conversion) and LCD (Local Characteristic scale Decomposition), which considered quantization error reduction and the signal decomposition. The sampling rate of the current line mode components with fixed sampling rate was converted to realize resampling of reconstructed signal. The local characteristic scale of resampling signal was decomposed and the instantaneous frequency of the first intrinsic scale component was calculated by using Teager energy operator, which identified the moment of fault first traveling wave arriving detecting point. The fault location was calculated with three points traveling wave localization algorithm. Simulation results verify the proposed method validity and accuracy.

Key words: transmission lines, traveling wave location, quantization error, sampling rate conversion, local characteristic scale decomposition

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