Advanced intelligent control for photovoltaic-vehicle-to-grid integration

• Datum: 2026
• Hauptverfasser: Lachheb, A., Chrouta, J., Telmoudi, A. J., Zaafouri, A.
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine 2026
• Schlagworte: artificial neural network; terminal sliding mode control; fuzzy logic; maximum power extraction; renewable energy
• Online Zugang: https://eie.khpi.edu.ua/article/view/343893
• Назва журналу: Electrical Engineering & Electromechanics

Introduction. The increasing penetration of electric vehicles (EVs) and renewable energy has intensified concerns about grid stability and energy sustainability. Integrating photovoltaic (PV) systems with vehicle-to-grid (V2G) technology provides a promising solution but requires efficient energy ma...