Optimal Allocation Planning for Public EV Charging Station Considering AC and DC Integrated Chargers

Abstract The adoption of AC and DC integrated charger(ADC) is considered as a mean to increase the comprehensive utilization rate and reduce the total cost of charging stations. In this paper a simulation-based optimization framework is proposed to solve the allocation problem for public charging stations equipped with multi-type of facilities, including AC slow chargers(ACCs), DC rapid chargers(DCCs) and ADCs. First of all, the characteristics of AC and DC charging demand are predicted, considering private EVs(PEVs) and electric taxis(TEVs). Then a stochastic queuing and service simulation model of multi-type chargers is developed based on agent-based modeling and simulation(ABMS) method, in order to model the complicated interactions among different types of EVs and chargers in detail. On the basis of the simulation model, an allocation optimization model is formulated to minimize the comprehensive annual cost, including charger investment cost, land purchase cost, grid reinforcement cost and queuing time cost. The simulation-based allocation optimization model is solved by embedded the simulation model as a black box into the meta-heuristics solver engine OptQuest. The proposed optimization framework is implemented in different allocation planning scenarios under different situations. The effects of ADC adoption in public charging stations are discussed by comparing the optimal plans with and without ADCs.