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Monika Singh
Sunil Kumar Sharma
Keywords:
Electric Vehicle (EV), Solar Photovoltaic, Grid-Connected Charging System, Energy Management System, Optimization Algorithms, Smart Grid.
Abstract:
The rapid adoption of electric vehicles (EVs) has significantly increased the demand for efficient, reliable, and sustainable charging infrastructure. Grid-connected solar photovoltaic (PV)-based EV charging systems have emerged as one of the most promising solutions to reduce greenhouse gas emissions, decrease dependency on fossil fuels, and improve energy security. These systems combine renewable energy generation with intelligent charging strategies to address challenges associated with increasing electricity demand, grid stability, and charging efficiency. Recent advancements in power electronic converters, bidirectional charging technologies, energy storage systems (ESS), smart grid communication, and artificial intelligence (AI)-based energy management have considerably enhanced the operational performance of solar-powered EV charging stations. This review presents a comprehensive assessment of recent developments in grid-connected solar EV charging systems, emphasizing system architectures, power management strategies, optimization techniques, and performance evaluation methods. Various optimization approaches, including classical mathematical optimization, metaheuristic algorithms, machine learning, deep learning, and reinforcement learning, are critically analyzed based on charging efficiency, computational complexity, renewable energy utilization, battery life, operational cost, and grid reliability. Furthermore, this review compares different optimization methods reported in recent literature and identifies current research gaps. The study concludes that hybrid AI-enabled optimization combined with advanced forecasting and vehicle-to-grid (V2G) technologies represents the future direction for sustainable EV charging infrastructure. The findings of this review provide valuable insights for researchers, engineers, policymakers, and industry practitioners involved in the development of next-generation smart charging systems.
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International Journal of Recent Research and Review
ISSN: 2277-8322
Vol. XIX, Issue 3
August 2026
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PUBLISHED
August 2026
ISSUE
Vol. XIX, Issue 3
SECTION
Articles
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