Abstract
The electric vehicle (EV) charging scheduling problem has become a research focus to mitigate the impact of large-scale deployment of EV in the near future. One of the main assumptions in literature is that there are enough charging points (CP) in the charging station to meet all charging demands. However, with the deployment of EVs, this assumption is no longer valid. In this paper, we address the electric vehicle charging problem in a charging station with a limited number of heterogeneous CPs and a limited overall power capacity. Before arriving at the station, the EV drivers submit charging demands. Then, the scheduler reserves a suitable CP for each EV and allocates the power efficiently so that the final state-of-charge at the departure time is as close as possible to the requested state-of-charge. We present two variants of the problem: a constant output power model and a variable power model. To solve these problems, heuristic and simulated annealing (SA) combined with linear programming are proposed. Simulation results indicate that the proposed approaches are effective in terms of maximizing the state-of-charge by the departure time for each EV.
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Zaidi, I., Oulamara, A., Idoumghar, L., Basset, M. (2021). Hybrid Heuristic and Metaheuristic for Solving Electric Vehicle Charging Scheduling Problem. In: Zarges, C., Verel, S. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2021. Lecture Notes in Computer Science(), vol 12692. Springer, Cham. https://doi.org/10.1007/978-3-030-72904-2_14
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