| Summary: | The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method.
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