Research On Layout Of Electric Vehicle Charging Station Under The Consideration Of User's Choice Behavior

In recent years,with the increasingly serious problems of environmental pollution and energy shortage,as new energy vehicles,electric vehicles which have significant advantages that are different from traditional energy vehicles,have attracted much attention.The development and promotion of electric vehicles is of great significance to the sustainable development of human society.However,the imperfection of the charging facility network has seriously restricted the popularization and application of electric vehicles,so it is necessary to scientifically plan the charging station network.With the development of the economy,the user's choice on charging stations becomes more and more significant,which has a crucial impact on the layout of the charging station network.Therefore,this paper studies the location planning problem of electric vehicle charging stations considering user's selection behavior.Firstly,this thesis studies the location planning problem of single-objective electric vehicle charging station considering user's selection behavior.The comprehensive utility function is constructed to quantify the user utility,the calculation method on user's selection probability for the charging station and the configuration rules of the charging piles are proposed.Then,the utility-oriented location planning model of electric vehicle charging station and the costoriented location planning model of electric vehicle charging station are established respectively,and an adaptive immune algorithm is designed.The effectiveness of the algorithm is verified by numerical experiments.Then,the sensitivity analysis of the relevant parameters of the two models is carried out,and the corresponding management insights are given.The results show that,for the utility-oriented charging station planning model,user rationality,the coverage radius of charging station,characteristic gravitational utility weight and minimum total construction cost are all important factors affecting the layout of charging stations;for the cost-oriented charging station location planning model,the daily average charging frequency of the electric vehicles,the fixed construction cost coefficient of the charging station,and the minimum user total weighted average utility all affect the final location result greatly.Finally,related layout strategies of electric vehicle charging stations are proposed.Then,this paper studies the location planning problem of multi-objective electric vehicle charging station considering user choice behavior.A multi-objective location planning model of charging station is formulated to minimize total construction cost of the charging stations,maximize overall user utility and minimize daily average carbon emissions.In this paper,the non-dominated sorting genetic algorithm II is used to solve the problem.The effectiveness of the model and algorithm is verified by numerical experiments,and the experimental results show that,in general,as the total cost increases,the overall user utility increases,and the daily average carbon emissions decrease.Subsequently,the sensitivity analysis for the construction number of charging stations is carried out.And the results show that,with the increase of the number for the two types of charging stations to be constructed,the optimal Pareto frontier surface moves in the direction of increase of total cost,the overall user utility and reduction of the daily carbon average emission.Finally,some layout strategies of the electric vehicle charging station are further proposed.The research in this paper enriches the location planning theory of electric vehicle charging stations,and provides the theoretical basis for the location planning problem of electric vehicle charging stations considering user selection behavior.In practice,this research makes the charging station location layout problem more close to the reality,improves the rationality of the charging station layout scheme and provides a decision-making reference for the charging station enterprises.