A new wavelet based fault detection, classification and location in transmission lines

•Voltage and current signals from both the ends of the line are analyzed with Wavelets.•Fault detection and classification are achieved in half cycle using d-coefficients.•Approximate coefficients are fed to ANN to locate the fault on the line.•Proposed scheme has been tested successfully for variou...

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Bibliographic Details
Published in:International journal of electrical power & energy systems 2015-01, Vol.64, p.35-40
Main Authors: Shaik, Abdul Gafoor, Pulipaka, Ramana Rao V.
Format: Article
Language:English
Subjects:
Algorithms
Classification
Electric potential
Fault Index
Faults
Multi resolution analysis
Position (location)
Transmission line protection
Transmission lines
Voltage
Wavelet transforms
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Summary:•Voltage and current signals from both the ends of the line are analyzed with Wavelets.•Fault detection and classification are achieved in half cycle using d-coefficients.•Approximate coefficients are fed to ANN to locate the fault on the line.•Proposed scheme has been tested successfully for various type and nature of faults.•The variation incidence angle has have no effect on performance of the scheme. This paper deals with the application of wavelet transforms for the detection, classification and location of faults on transmission lines. A Global Positioning System clock is used to synchronize sampling of voltage and current signals at both the ends of the transmission line. The detail coefficients of current signals of both the ends are utilized to calculate fault indices. These fault indices are compared with threshold values to detect and classify the faults. Artificial Neural Networks are employed to locate the fault, which make use of approximate decompositions of the voltages and currents of local end. The proposed algorithm is tested successfully for different locations and types of faults.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2014.06.065