Research on site selection and expansion planning of urban charging stations based on density clustering and user guidance^*

With the increase in the number of electric vehicles, the demand for electric vehicle charging is increasing, and more charging stations are needed to solve the problem of increasing charging demand. In the case that there are already some charging stations in the city, in order to build new charging stations more rationally or expand the capacity of the existing charging stations, this paper proposes a study on the expansion planning of urban charging stations based on Density Peak Clustering and charging guidance. Firstly, the charging demand is analyzed by Density Peak Clustering to determine the location of new charging stations, and then two-layer planning is carried out. The upper layer plans the location expansion plan by constraining the investment cost and user cost; the lower layer uses the digital map to obtain the traffic information of the road network and guides the users with the goal of minimizing the queuing time and then uploading the user's queuing time to the upper layer. Finally, the two-layer planning model is solved by the successive planning method with economic coefficients. The algorithm selects the Shanghai area for capacity expansion planning analysis to verify the feasibility and effectiveness of the proposed method.