An ANN routine for fault detection, classification, and location in transmission lines

D V Coury, M Oleskovicz, R K Aggarwal

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

This article presents an Artificial Neural Network (ANN) approach to simulate a complete scheme for distance protection of transmission lines. The protection technique is based on a modular approach whereby different neural network modules have been adopted for fault detection, fault classification and fault location. Three-phase voltage and current samples were utilized as inputs for the proposed scheme. The Alternative Transients Program (ATP) software was used to generate data for the transmission line (400 W). The results obtained show that the global performance of the ANN architectures is highly satisfactory under a wide variety of different fault conditions.
Original languageEnglish
Pages (from-to)1137-1149
Number of pages13
JournalElectric Power Components and Systems
Volume30
Issue number11
DOIs
Publication statusPublished - 2002

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Fault detection
Electric lines
Neural networks
Electric fault location
Network architecture
Electric potential

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An ANN routine for fault detection, classification, and location in transmission lines. / Coury, D V; Oleskovicz, M; Aggarwal, R K.

In: Electric Power Components and Systems, Vol. 30, No. 11, 2002, p. 1137-1149.

Research output: Contribution to journalArticle

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