A real-time fault diagnosis system for high-speed power system protection based on machine learning algorithms

This paper puts forward a real-time smart fault diagnosis system (SFDS) intended for high-speed protection of power system transmission lines. This system is based on advanced signal processing techniques, traveling wave theory results, and machine learning algorithms. The simulation results show th...

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Bibliographic Details
Published inInternational Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering Vol. 10; no. 6; p. 6122
Main Authors Khoudry, Elmahdi, Belfqih, Abdelaziz, Ouaderhman, Tayeb, Boukherouaa, Jamal, Elmariami, Faissal
Format Journal Article
LanguageEnglish
Published 01.12.2020
Online AccessGet full text
ISSN2088-8708
2722-256X
2722-2578
2722-2578
DOI10.11591/ijece.v10i6.pp6122-6138

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Summary:This paper puts forward a real-time smart fault diagnosis system (SFDS) intended for high-speed protection of power system transmission lines. This system is based on advanced signal processing techniques, traveling wave theory results, and machine learning algorithms. The simulation results show that the SFDS can provide an accurate internal/external fault discrimination, fault inception time estimation, fault type identification, and fault location. This paper presents also the hardware requirements and software implementation of the SFDS.
ISSN:2088-8708
2722-256X
2722-2578
2722-2578
DOI:10.11591/ijece.v10i6.pp6122-6138