Detection and Classification of Faults in Power Transmission Lines Using Functional Analysis and Computational Intelligence

The transmission line is the most vulnerable element of any electrical power system due to its large physical dimension. As a consequence, many fault diagnosis algorithms have been proposed in the literature. In general, most proposals use signal-processing analysis and computational intelligence. I...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2013-07, Vol.28 (3), p.1402-1413
Main Authors: de Souza Gomes, A., Costa, M. A., de Faria, T. G. A., Caminhas, W. M.
Format: Article
Language:English
Subjects:
Applied sciences
Detection and classification of faults
Electrical engineering. Electrical power engineering
Electrical power engineering
Equations
Exact sciences and technology
Mathematical model
Miscellaneous
Noise
Power networks and lines
Power transmission lines
Random variables
Stochastic processes
Testing. Reliability. Quality control
Wavelet transforms
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Summary:The transmission line is the most vulnerable element of any electrical power system due to its large physical dimension. As a consequence, many fault diagnosis algorithms have been proposed in the literature. In general, most proposals use signal-processing analysis and computational intelligence. In this paper, a new model to functionally represent the phases of a transmission line is proposed. The detection and classification strategy are developed from the analysis of the model's parameters and were evaluated using a set of simulated faults and a real database. The results show that the proposed model detects faults very quickly, using a vastly simplified mathematical process, and is able to classify faults accurately.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2013.2251752