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A Survey on Power Grid Faults and Their Origins: A Contribution to Improving Power Grid Resilience

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  • Adriana Mar

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, 2829-516 Caparica, Portugal
    Center of Technology and Systems (CTS), Instituto Desenvolvimento de Novas Tecnologias (UNINOVA), 2829-517 Caparica, Portugal)

  • Pedro Pereira

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, 2829-516 Caparica, Portugal
    Center of Technology and Systems (CTS), Instituto Desenvolvimento de Novas Tecnologias (UNINOVA), 2829-517 Caparica, Portugal)

  • João F. Martins

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, 2829-516 Caparica, Portugal
    Center of Technology and Systems (CTS), Instituto Desenvolvimento de Novas Tecnologias (UNINOVA), 2829-517 Caparica, Portugal)

Abstract

One of the most critical infrastructures in the world is electrical power grids (EPGs). New threats affecting EPGs, and their different consequences, are analyzed in this survey along with different approaches that can be taken to prevent or minimize those consequences, thus improving EPG resilience. The necessity for electrical power systems to become resilient to such events is becoming compelling; indeed, it is important to understand the origins and consequences of faults. This survey provides an analysis of different types of faults and their respective causes, showing which ones are more reported in the literature. As a result of the analysis performed, it was possible to identify four clusters concerning mitigation approaches, as well as to correlate them with the four different states of the electrical power system resilience curve.

Suggested Citation

  • Adriana Mar & Pedro Pereira & João F. Martins, 2019. "A Survey on Power Grid Faults and Their Origins: A Contribution to Improving Power Grid Resilience," Energies, MDPI, vol. 12(24), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4667-:d:295646
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    6. Rizeakos, V. & Bachoumis, A. & Andriopoulos, N. & Birbas, M. & Birbas, A., 2023. "Deep learning-based application for fault location identification and type classification in active distribution grids," Applied Energy, Elsevier, vol. 338(C).
    7. Moamin A. Mahmoud & Naziffa Raha Md Nasir & Mathuri Gurunathan & Preveena Raj & Salama A. Mostafa, 2021. "The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review," Energies, MDPI, vol. 14(16), pages 1-27, August.
    8. Stanley, Andrew P.J. & King, Jennifer, 2022. "Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant," Applied Energy, Elsevier, vol. 317(C).
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