Fault identification in distribution lines using intelligent systems and statistical methods

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Ziolkowski, Valmir
Da Silva, Ivan Nunes
Flauzino, Rogerio [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]

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The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.



Electric lines, Electric power distribution, Intelligent systems, Neural networks, Statistical methods, Distribution lines, Fault identification, Electric fault currents

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Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1122-1125.