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The use of grid-connected renewable energy sources, such as photovoltaic (PV) systems and battery storage, with electric vehicle (EV) charging infrastructure offers a viable solution to issues encountered in conventional charging stations. This paper investigates intelligent control approaches for EV charging, with a focus on the optimal use of PV energy and batteries for energy optimization. With the increasing popularity of EVs, there is a greater emphasis on sustainable transportation, making renewable energy integration critical. The article opens by discussing the shortcomings of typical EV charging, such as grid stress, capacity constraints, and reliance on nonrenewable sources. It offers a thorough overview of intelligent control strategies that incorporate modern algorithms and computational intelligence to maximize PV and battery use in charging infrastructure. The primary focus is on developing sophisticated optimal controllers for EV charging, demonstrating how intelligent management of PV energy based on aspects such as solar irradiance, battery condition, and grid demand enhances the charging process dramatically. Battery storage effectively captures excess PV energy, minimizing dependency on the grid during peak demand. The report highlights several advantages of intelligent control, including financial savings, reduced environmental impact, and increased energy efficiency. It investigates the predictive analytics potential for EV charging demand forecasting and dynamic allocation of PV and battery resources, hence boosting system efficiency. The paper also discusses essential factors such as hardware requirements, communication protocols, and interoperability in order to apply intelligent control in EV charging in a practical manner. It focuses on cybersecurity measures for safe functioning. The potential of PV and battery integration for energy optimization in EV charging is highlighted in this paper. It provides practical advice for academics, engineers, and policymakers interested in incorporating cutting-edge technology into sustainable transportation infrastructure.
Kumhar et al. (Fri,) studied this question.