Study On Site Selection Of Electric Vehicle Charging Stations In Dalian

In recent years,with the continuous improvement of residents' income levels,the auto industry based on private cars has also developed rapidly.The increase of its overload has brought pressure to the urban road and brought great crisis to the environment and natural resources.Under this development tendency,the electric vehicle industry,which has the advantages of green,low cost and "zero" pollution,has been greatly promoted and attracted more and more attention.Our government has also introduced a series of policies to promote the development of the electric vehicle industry.In order to make electric cars rapidly develop into the indispensable transportation tools for People's Daily travel,it is urgent to promote the improvement of the charging infrastructure network.Prediction is the basis of layout planning and the precondition of scientific decision,which can provide the future development trend and decisive factor for the planner.Therefore,before the layout and location of charging stations,we first need to predict the number of electric vehicles,charging demand and charging facilities in the coming years.In this paper,the Bass model is selected,and the relevant data of traditional cars are selected as the comparative analysis objects,and the quantity of electric vehicles is forecasted.According to the characteristics of three kinds of charging methods,such as conventional charging,fast charging and battery replacement,the prediction model of the demand of three kinds of charging methods for different kinds of electric vehicles is established,the charging demand of electric vehicles and the quantity of the charging facilities in the charging station are predicted.Secondly,from the two aspects of the cost and cost of the charging station,the cost minimization location model is established,and it is brought into the particle swarm optimization algorithm to solve the problem.The optimal position coordinates of the charging station are solved by the strong optimization ability of the particle swarm optimization.After the new site is generated,the site coordinates are used as the growing point of the Voronoi diagram to define the service area for the charging station.Finally,taking Dalian as an example,the layout and location of electric vehicle charging stations is studied.Based on the prediction of traditional motor vehicles in Dalian,the number of small electric vehicles,medium-sized electric vehicles,and large-scale electric vehicles in Dalian from 2018 to 2022 is forecasted,and the charging requirements of three charging methods are obtained according to the number of electric vehicles.The number of construction facilities and the number of charging facilities will be predicted to meet the future development plans for electric vehicles in Dalian in the future years.Taking the Shahekou District of Dalian as the location research object,the location coordinates of the 9 charging stations in Shahekou district are obtained and the service scope is divided.From the optimization results of the calculation example,the location model with the minimum cost as the objective function can be used to select the site of the charging station,and the division of the service area is clear.