Research On The Layout Problem Of Electric Vehicle Charging Station

In recent years,problems such as the energy crisis and environmental pollution have emerged endlessly.As a representative of new energy vehicles,electric vehicles are gradually gaining popularity due to their clean,pollution-free and high energy utilization.The support of national policies and the rapid development of the economy have made the scale of electric vehicles continue to grow.However,the number and distribution of charging facilities on the market are unreasonable,which makes it difficult for users to charge.Therefore,as the supporting facilities for the development of the electric vehicle industry,whether the construction of charging stations and charging facilities is perfect and reasonable will affect the development of electric vehicles,and will also have an impact on the investment of operators,the cost of charging users and the loss of power companies.In order to select the location of the charging station reasonably,this paper proposes to plan the location of charging stations and determine the number of charging facilities at the corresponding stations.After reading a large number of relevant literature at home and abroad,this paper has a certain understanding about the development status of electric vehicles and charging facilities.Firstly,it introduces electric vehicles and charging methods,clarifies the construction principles of charging facilities.Then considering the impact of economic growth on the development of the transportation industry,the elasticity coefficient method based on the second exponential smoothing is used to predict the private car ownership.The number of electric vehicles in the study area is predicted by the established vehicle ownership model,and the queuing theory model is used to analyze the number of charging facilities and their service capabilities.Besides,the satisfaction of the user’s charging experience proposed in this paper has also been used to assess the efficiency of the facilities in the station.In order to better optimize the location problem,this paper improves the original intelligent optimization algorithm—artificial searching swarm algorithm.Firstly,“dynamic parameters” are introduced to improve the problem of poor population diversity caused by fixed parameters,and they can also improve the exploitation ability of dominant populations at the later stage of convergence.Then this paper adds a “lead-forward” rule to improve the shortcomings of slow convergence and low convergence accuracy caused by blind searching in the algorithm’s early stage.Several different types of test functions for verification are selected in this paper to test the performance of the improved algorithm.The superiority of the improved algorithm is proved by comparison with the original algorithm.In addition,a Voronoi diagram which has certain advantages in solving location problem is introduced in this paper to divide the study area.Then it has been combined with the improved artificial searching swarm algorithm,in order to make full use of their advantages to optimize the mathematical model.Finally,a specific area in Tianjin is selected as an example to analyze in this paper.The minimum value of the objective function is consisted of the operators’ investment,the users’ charging cost and the power companies’ loss,and the constraint conditions include the number of charging facilities which is determined by the car ownership and the charging facility service capacity,the maximum distance between charging stations,the charging station and the charging demand point.According to the distribution of charging demand points,the study area is divided into 34 small grid areas.Then,the charging station site division’s experiment is carried out.The simulation experiment is implemented in the operating environment of Windows 10 system and MATLAB R2014 a.The model is solved by the improved method of artificial searching swarm algorithm and Voronoi diagram,and the optimal simulation result is obtained.Through of the analysis of the simulation optimization results,it can be seen that the charging station location and volume problem in the study area have been optimized reasonably by the model,and the goal of minimum total cost has also been achieved,which proves the effectiveness and reasonableness of the model.