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A Review of Fault Diagnosing Methods in Power Transmission Systems

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Department of Electrical Engineering, the University of Lahore, Lahore 54000, Pakistan
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Department of Electrical Engineering, Ecole Militaire Polytechnique, Algiers 16111, Algeria
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Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Department of Engineering & Mathematics, Sheffield Hallam University, Sheffield S1 1WB, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(4), 1312; https://doi.org/10.3390/app10041312
Received: 20 January 2020 / Accepted: 1 February 2020 / Published: 14 February 2020
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
Transient stability is important in power systems. Disturbances like faults need to be segregated to restore transient stability. A comprehensive review of fault diagnosing methods in the power transmission system is presented in this paper. Typically, voltage and current samples are deployed for analysis. Three tasks/topics; fault detection, classification, and location are presented separately to convey a more logical and comprehensive understanding of the concepts. Feature extractions, transformations with dimensionality reduction methods are discussed. Fault classification and location techniques largely use artificial intelligence (AI) and signal processing methods. After the discussion of overall methods and concepts, advancements and future aspects are discussed. Generalized strengths and weaknesses of different AI and machine learning-based algorithms are assessed. A comparison of different fault detection, classification, and location methods is also presented considering features, inputs, complexity, system used and results. This paper may serve as a guideline for the researchers to understand different methods and techniques in this field. View Full-Text
Keywords: AC networks; artificial intelligence (AI), deep learning (DL), fault detection (FD), fault-type classification (FC), fault location (FL), machine learning (ML) AC networks; artificial intelligence (AI), deep learning (DL), fault detection (FD), fault-type classification (FC), fault location (FL), machine learning (ML)
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MDPI and ACS Style

Raza, A.; Benrabah, A.; Alquthami, T.; Akmal, M. A Review of Fault Diagnosing Methods in Power Transmission Systems. Appl. Sci. 2020, 10, 1312.

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