Enhancing Electric Vehicle Charging Schedules: A Surrogate-Assisted Approach
Résumé
This paper addresses the pressing issue of efficiently scheduling electric vehicle (EV) charging at public stations to alleviate strain on the electrical grid. EV drivers provide their charging needs beforehand, and the scheduler optimizes charger allocation and power distribution to minimize discrepancies in state-of-charge levels at departure. To tackle the complexity of this NP-hard problem, this study proposes a solution framework combining a genetic algorithm with linear programming. Surrogate models are also investigated to expedite problem-solving. Simulation results demonstrate the effectiveness of these approaches in managing the complexities of EV charging scheduling.