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Photovoltaic (PV) powered Electric Vehicle Charging Stations (PVCS) have received extensive attention recently due to the complementary relationship of PV energy and electric vehicles. This paper proposes a methodology aimed at assisting a Charging Point Operator (CPO) in determining the size of the main components of such PVCS. The modular structure of the method gives flexibility for possible use on a new sizing problem by modifying key parameters such as the EV charging demand (i.e., arrival/departure times and energy needed to fill the battery), the EV charging strategy or the business model, independently from each other. It is of particular interest for a CPO that sizes many PVCS operated in the same environment (for example, a car park at a workplace). In that case, the CPO first has to apply the method on a representative charging station. Next, he can re-use parts of the obtained results to drastically speed up (from weeks to hours) the sizing of the other charging stations. The proposed method has been applied to the EVCS of an industrial research complex in southern France. The input dataset used to apply the method consists of more than 32,000 charging transactions spanning over 6 years with 350 EV users and 80 charging points. Three charging strategies with different levels of complexity are investigated, including Mean Power, Plug and Charge, and Solar Smart Charging. The considered business model is based on the maximization of the self-production rate. The numerical findings reveal that employing a straightforward charging strategy, such as Mean Power, leads to a substantial reduction of nearly half in the required size of the PV plant compared to the basic Plug and Charge mode. In addition, our analysis demonstrates that Solar Smart Charging has the potential to decrease the PV plant size by nearly three times.

Sales of electric vehicles, for commercial use and personal use, keep rising. In parallel of the development of the associated Electric Vehicle Charging Infrastructure (EVCI), systems for controlling the charging of EVs will have to be developed in order to reduce the impact of such a development on the power grid. In this paper, we present a supervision system that controls the electric vehicle charging of employees of CEA Cadarache research center. The EVCI of Cadarache, set up in 2016, is constituted of more than 80 22-kW AC charging points spread over 30 zones. This EVCI currently supplies more than 376 vehicles including taxis, service vehicles as well as employees’ vehicles. This infrastructure is one of the largest private EVCIs in the region. The supervision system controls electric vehicle (EV) charging in real-time according to two objectives: respecting user preferences, by fully charging the EV battery, and synchronizing the power consumption of a fraction of the EVCI, i.e., 24 charging points, with the power production of a solar photovoltaic plant. This paper details the supervision system that is used to carry out these experiments and presents experimental results. These results show that it is technically feasible to increase (up to 60 percentage points) the self-production ratio while satisfying EV users.