Deadline-Aware EV Smart Charging: Reinforcement Learning vs. Urgency-Based

Abstract

Deadline-aware electric vehicle (EV) smart charging is an intelligent energy management approach designed to schedule EV charging activities according to users’ departure times, required battery energy, electricity prices, and power system operating conditions. Unlike conventional charging strategies that begin charging immediately after an EV is connected to a charging station, deadline-aware charging considers the time available before each vehicle must depart and ensures that the required energy is delivered within the available charging window. This approach is particularly important as the growing adoption of EVs increases electricity demand and creates additional challenges for distribution networks, especially during peak-load periods. The primary objective is to minimize charging costs, reduce peak demand, improve grid stability, and satisfy individual mobility requirements without compromising user convenience. In a typical deadline-aware charging framework, each EV is characterized by its arrival time, departure deadline, initial state of charge (SoC), target SoC, battery capacity, and maximum charging power. Based on these parameters, an optimization algorithm determines the most suitable charging schedule while respecting battery constraints, charger limitations, and available grid capacity. Time-of-use electricity tariffs can be incorporated to prioritize charging during low-price periods, while demand-response signals can encourage charging during periods of surplus renewable energy generation or reduced grid demand. Furthermore, renewable energy sources, such as solar photovoltaic systems and wind power, can be integrated into the charging infrastructure to reduce dependence on conventional electricity generation and lower associated carbon emissions. Advanced optimization techniques, including mixed-integer linear programming, model predictive control, and reinforcement learning, can improve scheduling decisions under dynamic operating conditions and uncertain user behavior. The framework may also incorporate vehicle-to-grid (V2G) functionality, allowing compatible EVs to supply electricity back to the grid when necessary, provided that mobility requirements and battery degradation constraints are satisfied. Effective implementation requires reliable communication between EVs, charging stations, electricity providers, and energy management systems to update charging schedules in response to changing conditions. Performance can be evaluated using indicators such as total charging cost, peak-to-average demand ratio, renewable energy utilization, deadline satisfaction rate, and charging-related emissions. Ultimately, deadline-aware EV smart charging provides a practical pathway toward cost-effective, user-centric, and grid-responsive transportation electrification while supporting the integration of renewable energy and the development of sustainable smart grids.