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Article Dans Une Revue Energies Année : 2023

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

Zakarya Oubrahim

Résumé

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.

Dates et versions

hal-04119441 , version 1 (06-06-2023)

Identifiants

Citer

Zakarya Oubrahim, Yassine Amirat, Mohamed Benbouzid, Mohammed Ouassaid. Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review. Energies, 2023, 16 (6), pp.2685. ⟨10.3390/en16062685⟩. ⟨hal-04119441⟩
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