Abstract

Fast fault clearance and fault localization is of great interest in the context of power systems operations and economics. Conventional distance protection schemes provide adequate information in fault isolation but do not provide sufficient information for fault localization and characterization in required accuracy. This study develops a distance relay observer model using fault transient analysis to be used in radial and in branched networks. Wavelet analysis together with traveling wave behavior of fault transients obtained from wide band substation voltage transformers are used to retrace the fault transient history. Modal transform associated with Daubechies filtration of fault transients identifies successive impulses. The resulted fault transient voltage graph together with network topology is used to calculate the fault distance and fault category. The polarity, magnitude and timing of the reflections originated from network boundary discontinuities and from the fault are analyzed to locate the fault. Simulation studies in MATLAB/SIMULINK environment demonstrate that this scheme is capable of locating and characterizing the faults accurately.

Highlights

  • Electric power systems are susceptible to various types of faults caused by transient weather or animal induced situations as well as maintenance circumstances with human and asset related failures

  • Fast fault clearance and fault localization is of great interest in the context of power systems operations and economics

  • This study develops a distance relay observer model using fault transient analysis to be used in radial and in branched networks

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Summary

Introduction

Electric power systems are susceptible to various types of faults caused by transient weather or animal induced situations as well as maintenance circumstances with human and asset related failures. Fault Localization using Wavelet Transforms in 132kV Transmission Lines Abstract: Fast fault clearance and fault localization is of great interest in the context of power systems operations and economics.

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