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Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

Author

Listed:
  • Zakarya Oubrahim

    (Engineering for Smart and Sustainable Systems Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat 10090, Morocco)

  • Yassine Amirat

    (ISEN Yncréa Ouest, L@bISEN, 29200 Brest, France)

  • Mohamed Benbouzid

    (Institut de Recherche Dupuy de Lôme (UMR CNRS 6027), University of Brest, 29238 Brest, France
    Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China)

  • Mohammed Ouassaid

    (Engineering for Smart and Sustainable Systems Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat 10090, Morocco)

Abstract

Several factors affect existing electric power systems and negatively impact power quality (PQ): the high penetration of renewable and distributed sources that are based on power converters with or without energy storage, non-linear and unbalanced loads, and the deployment of electric vehicles. In addition, the power grid needs more improvement in the performances of real-time PQ monitoring, fault diagnosis, information technology, and advanced control and communication techniques. To overcome these challenges, it is imperative to re-evaluate power quality and requirements to build a smart, self-healing power grid. This will enable early detection of power system disturbances, maximize productivity, and minimize power system downtime. This paper provides an overview of the state-of-the-art signal processing- (SP) and pattern recognition-based power quality disturbances (PQDs) characterization techniques for monitoring purposes.

Suggested Citation

  • Zakarya Oubrahim & Yassine Amirat & Mohamed Benbouzid & Mohammed Ouassaid, 2023. "Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review," Energies, MDPI, vol. 16(6), pages 1-41, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2685-:d:1096079
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    References listed on IDEAS

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    Cited by:

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