Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy

SHANG Liqun; LI Yao

doi:10.7652/xjtuxb202205012

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Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy

更新时间：2025-07-09

- Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy
- Vol. 56, Issue 5, Pages: 119-126(2022)
- 作者机构：
  
  西安科技大学电气与控制工程学院,西安,710054
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202205012
  CLC： TM76
- Online First：10 May 2022，
  
  Published：2022
- 稿件说明：
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SHANG Liqun, LI Yao. Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy[J]. 2022, 56(5): 119-126.
DOI：

SHANG Liqun, LI Yao. Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy[J]. 2022, 56(5): 119-126. DOI： 10.7652/xjtuxb202205012.

摘要

针对目前含逆变型分布式电源配电网故障选线方法无法在各种故障类型下准确选线的问题

提出一种利用组合模量特征结合S变换算法和信息熵理论的有源配电网故障选线方法。提取配电网各出线端的电流信号

通过组合模量行波电流变换以消除在不同故障类型下故障特征失效的情况; 将组合模量行波电流进行S变换以提取故障信号处的幅值和相角信息

结合信息熵理论通过故障信号最大幅值处的短窗数据在多频段下求取各条出线的多尺度能量熵; 通过故障线路与非故障线路之间能量熵差值的实例分析

选取差值最大的频段作为求解能量熵的固定频段以减少运算量; 以各条出线固定频段下的熵值大小作为判据来定位故障线路。数值仿真结果表明

该方法对各种故障类型均能准确地选出故障线路

且不受故障初始角、故障距离以及过渡电阻的影响

特别是在高阻情况下仍然能够实现准确、高效的故障选线。

Abstract

In view that some existing methods cannot identify accurately a faulty line in the distribution network with inverter-interfaced distributed generation(IIDG)

a method of faulty line identification in active distribution network is proposed based on combined modulus characteristics

S-transform algorithm and information entropy theory. Firstly

the current signal at each outlet end of the distribution network is extracted

and the failure of fault characteristics under different fault types is eliminated through combined modulus-based traveling wave current transformation. Secondly

the combined modulus traveling wave current is S-transformed to extract the amplitude and phase angle information at the fault signal

and the multiscale energy entropy of each outgoing line is obtained in multiple frequency bands by basing on the information entropy theory and the short window data at the maximum value of fault signal. Thirdly

the energy entropy difference between the faulty line and the non-faulty line is analyzed

and the frequency band with the largest difference is selected as the fixed frequency band for solving the energy entropy to reduce the amount of calculation. Finally

the entropy value of each outgoing line in a fixed frequency band is used as a criterion to locate the faulty line. Numerical simulation results show that the proposed method can accurately identify the fault line for various types of faults

and is not affected by the initial angle of the fault

the fault distance and the transition resistance. It can still accurately and efficiently identify the fault line

especially in the case of high resistance.

关键词

Keywords

references

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