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Title	Optimization Of Electric Vehicle Charging Control In A Demand-Side Management Context: A Model Predictive Control Approach
ID_Doc	40628
Authors	Fernandez V.; Pérez V.
Year	2024
Published	Applied Sciences (Switzerland), 14, 19
DOI	http://dx.doi.org/10.3390/app14198736
Abstract	In this paper, we propose a novel demand-side management (DSM) system designed to optimize electric vehicle (EV) charging at public stations using model predictive control (MPC). The system adjusts to real-time grid conditions, electricity prices, and user preferences, providing a dynamic approach to energy distribution in smart city infrastructures. The key focus of the study is on reducing peak loads and enhancing grid stability, while minimizing charging costs for end users. Simulations were conducted under various scenarios, demonstrating the effectiveness of the proposed system in mitigating peak demand and optimizing energy use. Additionally, the system’s flexibility enables the adjustment of charging schedules to meet both grid requirements and user needs, making it a scalable solution for smart city development. However, current limitations include the assumption of uniform tariffs and the absence of renewable energy considerations, both of which are critical in real-world applications. Future research will focus on addressing these issues, improving scalability, and integrating renewable energy sources. The proposed framework represents a significant step towards efficient energy management in urban settings, contributing to both cost savings and environmental sustainability. © 2024 by the authors.
Author Keywords	charging stations; energy management; fully electric vehicles; smart city; smart grid; urban planning

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