PV-Battery hybrid system power management based on backstepping control

With the increasing global energy consumption and the need for sustainable solutions, this article focuses on the energy management of a hybrid photovoltaic (PV)-battery system using the backstepping method. The research addresses the challenges of intermittent solar irradiation by implementing an incremental conductance maximum power point tracking (MPPT) algorithm for the PV panel and backstepping control for battery charging and discharging. The system's performance and control effectiveness were validated through laboratory experiments. The results demonstrate the system's robustness, stability, and ability to respond to fast changes, making it a promising solution for efficient energy management in hybrid PV-battery systems. The findings provide valuable insights for future research and advancements in this field. MSC: 34C60, 93C10. REFERENCES [1] MAAMIR, Madiha. Techniques de supervision d’énergie d’un système d’entrainement Electrique hybride. 2020. Thèse de doctorat. Université Mohamed Khider–Biskra. Search in Google Scholar, View [2] DE SOTO, Widalys, KLEIN, Sanford A., et BECKMAN, William A. Improvement and validation of a model for photovoltaic array performance. Solar energy, 2006, vol. 80, no 1, p. 78-88. Search in Google Scholar, https://doi.org/10.1016/j.solener.2005.06.010 [3] ERICKSON, Robert W. et MAKSIMOVIC, Dragan. Fundamentals of power electronics. Springer Science & Business Media, 2007. Search in Google Scholar, View [4] JYOTHI, Vellanki Mehar, MUNI, T. Vijay, et al. An optimal energy management system for pv/battery standalone system. International Journal of Electrical and Computer Engineering, 2016, vol. 6, no 6, p. 2538. Search in Google Scholar, View Article [5] KUMAR, Vinit et SINGH, Mukesh. Derated mode of power generation in PV system using modified perturb and observe MPPT algorithm. Journal of Modern Power Systems and Clean Energy, 2020, vol. 9, no 5, p. 1183-1192. Search in Google Scholar, https://doi.org/10.35833/MPCE.2019.000258 [6] MOURAD, Loucif. Synthèse de lois de commande non-linéaires pour le contrôle d’une machine asynchrone à double alimentation dédiée à un système aérogénérateur. 2016. Thèse de doctorat. Ph. D. thesis, Université Aboubakr Belkaid–Tlemcen–Faculté de Technologie. Search in Google Scholar, View [8] AMARA, Karima, MALEK, Ali, BAKIR, Toufik, et al. Adaptive neuro-fuzzy inference system based maximum power point tracking for stand-alone photovoltaic system. International Journal of Modelling, Identification and Control, 2019, vol. 33, no 4, p. 311-321. Search in Google Scholar, https://doi.org/10.1504/IJMIC.2019.107480 [9] RAHMAN, Sumaiya et RAHMAN, Hasimah Abdul. Use of photovoltaics in microgrid as energy source and control method using MATLAB/Simulink. International Journal of Electrical and Computer Engineering, 2016, vol. 6, no 2, p. 851. Search in Google Scholar, View Article [10] ABD ALLAH, Boucetta et DJAMEL, Labed. Control of power and voltage of solar grid connected. Bulletin of Electrical Engineering and Informatics, 2016, vol. 5, no 1, p. 37-44. Search in Google Scholar, https://doi.org/10.11591/eei.v5i1.519 Communicated Editor: Nabil Khelfallah Manuscript received Dec 06,2023; revised May 19, 2024; accepted Nov 27, 2024; published Dec 28, 2024.