Abstract

Forecasting in smart grids is of utmost importance due to the existence of hybrid and electric grid-connected vehicles. The grid flow capacity, especially during peak hours, cannot bear adding a large number of charging stations (CS). Rapid EVCSs are a suitable option for promoting people's interest in using these vehicles, instead of gasoline-burning vehicles. Lack of long and tiresome lines for charging the vehicles and available CSs can greatly impact EVs' penetration. Accordingly, this study aimed to design an EVCS while considering different sources and equipment such as PV system, battery, and diesel for drivers' comfort and taking into account multi-level charge. Thus, the optimal design of the station for the grid-connected mode was converted into an optimization problem and a developed hybrid PSO and gray wolf algorithm were used for solving it. As the result of this optimization, the energy storage system's power and capacity, as well as the diesel generator's and the energy storage system's performance duration can be determined in continuous hours. The results showed that the proposed model successfully used all the options available for designing the EVCS.

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