AI and ML Innovations in EV Charging: Transforming Smart Grids with Vehicle-to-Grid Technologies

Authors: Aditya Kumar Sharma

Country: United States

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Abstract: The rapid ascendancy of electric vehicles (EVs) marks a significant pivot towards sustainable transportation, addressing the pressing concerns of energy conservation and environmental degradation. With the global surge in EV adoption, underscored by a 75% sales increase in the early months of 2022 compared to the previous year, the integration of these vehicles into the existing electrical grids emerges as both a challenge and an opportunity. This integration is facilitated by Vehicle-to-Grid (V2G) systems, which leverage EV batteries as dynamic energy storage units, offering ancillary services such as peak shaving and voltage regulation, thereby enhancing grid efficiency and promoting renewable energy utilization. Despite the potential benefits, the practical implementation of V2G technologies is still at a nascent stage, primarily confined to pilot projects with limited scalability. The academic discourse has extensively explored EV charging strategies, yet the operational and economic facets of V2G, especially in discharge scheduling and dynamic pricing strategies, remain underexplored. This paper ventures into this relatively uncharted territory, examining the role of artificial intelligence (AI) in revolutionizing forecasting, scheduling, and dynamic pricing models relevant to EV charging and discharging practices. This research aims to provide a comprehensive analysis of current AI-driven methodologies in EV management, elucidating the synergies between forecasting accuracy, scheduling efficiency, and dynamic pricing efficacy. It identifies significant gaps in existing studies and proposes future research directions to foster the integration of EVs into smart grids. The study underscores the critical need for advanced forecasting models, innovative dynamic pricing strategies, and reinforcement learning-based optimization models to navigate the complexities of EV charging and discharging in a rapidly evolving energy landscape. As the cornerstone of smart city infrastructure, the integration of EVs and the development of intelligent charging systems are imperative for mitigating urbanization pressures and ensuring environmental sustainability. This paper highlights the challenges and opportunities in EV management, emphasizing the importance of machine learning techniques in enhancing charging infrastructure and integrating renewable energy sources into distributed microgrids. It concludes with a call for multidisciplinary research efforts to realize the full potential of EVs in smart grids, paving the way for a sustainable, efficient, and interconnected energy future.

Keywords: Electric Vehicles (EVs), Vehicle-to-Grid (V2G) Technology, Artificial Intelligence (AI) in Energy Management, Dynamic Pricing Strategies, Smart Grid Integration

Paper Id: 230540

Published On: 2023-09-05

Published In: Volume 11, Issue 5, September-October 2023

Cite This: AI and ML Innovations in EV Charging: Transforming Smart Grids with Vehicle-to-Grid Technologies - Aditya Kumar Sharma - IJIRMPS Volume 11, Issue 5, September-October 2023.

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