A Survey Study on Optimization of Solar Power Systems Used in Charging Electric Vehicles Based on Artificial Intelligence Techniques

Document Type : Original Article

Authors

1 Faculty of Technology and Eduction, Helwan University

2 Faculty of Technology and Education, Helwan University

3 Faculty of Education- Banha university

4 , Faculty of Technology and Education, Helwan University

Abstract

This survey study investigates the current state of research on the optimization of solar power systems used in charging electric vehicles (EVs) through the application of artificial intelligence (AI) techniques. Despite significant advancements, a critical research gap remains: the lack of a comprehensive mathematical model designed to minimize the surface area of photovoltaic panels while ensuring sufficient energy to charge EV batteries. This survey aims to address this gap by reviewing existing optimization methods and their application to solar-powered EV charging systems. The primary research questions posed are: "Which AI-based optimization techniques are most effective in minimizing the solar panel surface area required for EV charging?" and "What are the key factors and constraints that need to be considered in developing such a mathematical model?" Key hypotheses include the potential superiority of certain metaheuristic algorithms over others in achieving these objectives. Findings are systematically presented in tables, comparing various algorithms and highlighting their respective strengths and limitations. This study sets the stage for future research focused on developing a precise mathematical model to optimize solar panel usage for EV charging

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