Research On The Location Problem Of Electric Vehicle Charging Station Intra-area

With the global problem such as environment pollution and oil resources is becoming more and more serious,low carbon,economic and environmental protection has become the theme of China’s economic development.New energy electric vehicle is famous for its clean environmental protection,energy saving and emissions reduction,whose development has got the relevant national policy support.It also will become the mainstream of future transport development.However,the construction of electric vehicle charging station network is far behind the development of electric vehicle.Although domestic has built some charging piles,mostly built in residential area with low charging speed,which only services a single electric vehicle user.Even if there are part of the public charging stations,they are at the technical validation and demonstration stage,who cannot meet the daily charging demand of the electric vehicle user,which reduces purchase intention of potential electric vehicle users.Charging station location problem has become one of the key factors restricting electric vehicle’s popularization in China.Reasonable scheme of charging station location can reduce the charging cost of electric vehicle user,increase operating benefits of charging station,promote the construction of charging station and the development of electric vehicle,Which is of great significance to improve the traffic environment.At present,the electric vehicle is at the stage of substantial promotion.In order to rapidly improve the using convenience of electric vehicle and promote more potential users to buy electric vehicle,the cost is no longer the key consideration of the charging station construction.Therefore,from the point of view of users’ satisfaction to consider the electric vehicle charging station’s location problem.Based on satisfactory optimization theory,the evaluation function of electric vehicle users’ satisfaction is proposed firstly.By introducing the conception of multi-grade of recharging stations,a mixed integer programming model on location of multi-grade electric vehicle recharging stations is developed,whose objective function is to maximize the average electric vehicle users’ satisfaction.And an algorithm based on immune algorithm is proposed to solve this model.The test results show that the model proposed in this paper can effectively determine the locations,grades and the service regions of the recharging stations,and the algorithm to solve it is quick and effective.When the electric vehicle development to a certain stage,electric vehicle charging station location should consider the benefit of operator.From the perspective of the electric vehicle users and operators to consider electric vehicle charging station location problem.from the perspective of the electric vehicle user,two optimum indexes are proposed to measure user’s satisfaction——the distance between user and charging station and user’s waiting time in charging station.From the perspective of the operator,construction cost of charging station is proposed as an optimum index.On this basis,a multi-objective nonlinear mixed integer programming model is established.To make this model more practical,a charging queuing simulation process is used to replace the traditional queuing theory.An improved tabu-genetic algorithm is proposed to solve this model,and a random example is designed to prove the validity of the model and algorithm.Finally,we make a series of model parameters’ sensitivity analysis about the multi-objective electric vehicle charging station location and optimization model,studying the effect of the charging station number for each cost,the charging rate on the influence of waiting time cost,the charging rate on the influence of the number of charging piles and the effect of the increasing customers for charging rate decision.As there is a stochastic process involved in the basic model,this paper conducts multiple tests combining with test case.Related test results can provide reference information for practical projects.