A battery swapping station (BSS) is an enabling facility for battery swapping electric vehicles (EVs). To ensure the high quality of service (QoS) provided for EV customers while providing new batteries, the capacities of batteries and chargers in a BSS should be optimized. To achieve that, an EV battery swapping demand prediction model that specially considers the influences of different seasons, the output of which is the key data for capacity sizing, is firstly developed based on Monte Carlo algorithm. Then, an optimal capacity sizing model targeted at both minimizing the construction and operation cost of the BSS and maximizing the grid-shifting ability is proposed under a proposed optimal battery swapping and charging algorithm. The optimal capacity sizing for the batteries and chargers is finally obtained using the NSGA-II algorithm to solve the developed model with all operation constraints. Case studies based on the real data provided by BSS operation companies in China are done to verify the validity of the proposed method. The results show that the cost of the BSS can be reduced while peak-shifting can be enabled with the proposed capacity sizing and battery charging/discharging algorithm.
Hu et al. (Thu,) studied this question.