Electric Vehicles (EVs) are expected to become the majority of vehicles; The number of BEV (Battery Electric Vehicle) and PHEV (Plug-in Hybrid Electric Vehicle) increases each year. In parallel, the number of charging stations is also growing. However, due to the time needed to fill the batteries, finding the best station becomes a challenge. Moreover, uncoordinated electric vehicle charging may lead to the emergence of load peaks. In the context of a feet of autonomous electrical vehicles, the problem becomes even more complex: how to ensure an efficient and fair battery charging for all of them? Due to the dynamic nature of a traffic network, a multiagent approach seems an adequate. By making charging stations the main actors of a cooperative systems, we propose a multiagent system (MAS) that aims to make the use of EV fleets more green by selecting the adapted time slots and load stations. In this paper, we present a model in which charging stations coordinate to schedule and deliver vehicle charging. We then validate this model through simulation. The results show that the proposed model helps in balancing renewable energy use, grid load, and service satisfaction. This demonstrate the feasibility of MAS approach for smart EV fleet charging.
Crinchon et al. (Thu,) studied this question.
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