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Titre: Contrôle avancé de la fréquence des réseaux avec une forte pénétration des systèmes à énergie renouvelable
Auteur(s): Messasma, Chaouki
Mots-clés: Photovoltaic (PV)
Wind turbine (WT)
Date de publication: 28-oct-2025
Résumé: This study develops advanced frequency control strategies to enhance the stability of electrical grids with high penetration of renewable energy sources (RES), specifically photovoltaic (PV) solar plants and wind turbines. Due to their intermittent nature, these RES introduce significant challenges to grid stability. A novel frequency control strategy is introduced, characterized by simplicity, efficiency, and precision. Unlike conventional methods, it operates independently of auxiliary equipment such as batteries, reducing costs and complexity while ensuring reliable grid performance. Initially designed for PV-integrated grids, its effectiveness is validated using proportional-integral (PI) controllers. A deloading mechanism is combined with real inertia from decommissioned synchronous generators (SGs) to form hybrid inertia (HI), enhancing overall stability. To further improve performance, advanced control techniques, including fuzzy logic and genetic algorithms, are incorporated. These AI-driven enhancements enable dynamic adaptation to PV variability, improving grid stability and facilitating higher RES penetration. The study then extends this strategy to wind energy integration,developing a robust control approach to maintain frequency stability under fluctuating wind conditions. A wind turbine (WT) deloading strategy is further refined through AI-based techniques and advanced control methodologies, creating a comprehensive frequency management solution adaptable to diverse renewable energy scenarios.Finally, the research investigates hybrid PV-wind systems and their decoupling strategies with deloading mechanisms.Robust control techniques are employed to ensure stability and reliability in these multi-source configurations.All proposed strategies undergo rigorous testing and validation in MATL.
URI/URL: http://dspace.univ-setif.dz:8888/jspui/handle/123456789/6091
Collection(s) :Thèses de doctorat

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