Study on the planning of electric vehicle fast charging facilities considering path selection behavior

The inadequate layout of intercity fast charging facilities leads to difficulties in intercity travel for electric vehicle(EV) users. We incorporate EV users' path selection behavioral preference factors into planning intercity fast charging facilities and propose a bi-level programming model. Firstly, the lower layer constructs a stochastic user equilibrium model for dynamic traffic in Logit form based on general regret theory, and the upper layer constructs a multi-objective planning model that considers minimizing the total annual cost of EV charging station operators and minimizing the average queuing time of EV users; secondly, the NSGA-II nested MSA algorithm is used for solving the bi-level programming model; finally, the feasibility of the model and algorithm is verified by the Nguyen-Dupuis transportation network example. The results show that our proposed model can meet the charging needs of different users, and can effectively reduce the queuing waiting time of EV users and alleviate their travel anxiety.