Research On Electric Vehicle Charging Station Location Based On Charging Demand Analysis

Charging infrastructure has a great influence on the development of new energy vehicle industry,and the current layout of charging infrastructure is unreasonable,resulting in low charging efficiency,wasted operator cost and bad charging experience for users;to address the problem,this paper conducts a research on the location of charging stations based on charging demand,and takes Jiangbei District of Chongqing City as an example for a reasonable location of charging infrastructure.First,the charging demand of electric vehicles is analyzed,and the obtained POI data are processed by density clustering and K-mean clustering algorithm to get the coordinate location of the cluster center and the spatial characteristics of electric vehicles.Considering the travel time characteristics and spatial characteristics of electric private cars,the corresponding probability density function is obtained,and the charging behavior of users is analyzed in terms of charging starting state,and the demand for fast charging is obtained by using MC simulation;the starting power and starting charging moment of electric cabs are considered and analyzed by using Monte Carlo.Finally,the charging demand of electric private cars and the charging demand of electric cabs are superimposed to get the final total charging demand.Then,based on the charging demand analysis,the charging station site selection is studied.A multi-objective siting model is established with the lowest user charging demand and operator cost.The NSGA-Ⅱ algorithm,which solves the multi-objective optimization problem,is used to introduce the selection of reference points,and the reliability of the algorithm is verified by analyzing different scales of arithmetic cases,and the model is solved with the improved NSGA-Ⅱ algorithm.Finally,the analysis is carried out with the fast charging station site selection in Jiangbei District of Chongqing in 2023.The charging demand analysis is carried out using MATLAB with the ownership of electric cabs and electric private cars.The model is solved using the improved NSGA-Ⅱ algorithm to obtain the Parteo dominant solution set for different cases of site selection,which provides different site selection options for business development and provides reference for decision makers.