Research On Multi-Period Planning Of Electric Car Charging Station Based On Credibility

In order to advocate green transport,reduce CO₂emissions and decrease PM_2.5,China vigorously encourages more people to use electric vehicles（EVs）.However,the development of EV charging stations is backward,which seriously hinders the popularization of EVs.Therefore,it is an urgent and important task to improve the layout planning of charging stations in order to better promote the development of EVs and ensure the travel of EVs.Charging stations belong to the infrastructure which are costly.It is difficult to establish a large number of charging stations at one time under the pressure of funds to meet the growing demand for charging.Hence,charging stations are often completed in multiple periods.The distribution of electric vehicle users is uneven.Different levels of charging stations are different in terms of scale,capacity and cost.In addition,the charging demand,construction cost and other parameters will be in uncertainty due to the complexity of the actual environment.Therefore,it is significant to study the position and the level of charging stations in each period under an uncertain environment.Based on this,the main research contents of this dissertation are as follows:Firstly,this dissertation studies the multi-period fuzzy planning problem for multi-level EV charging stations under intra-city based on the point demand of charging station construction..Considering the fuzziness of charging demand,charging station construction cost and operation cost as well as integrating the expected value and chance constrained programming approaches,a fuzzy programming model is established.The objective functions attempt to maximize the satisfaction of EV users as well as minimize the construction cost and the operation cost of charging station in the whole periods based on the credibility theory from the perspective of charging station investors and EV users.Two interactive fuzzy methods are used to deal with the two-objective model,and a multi population genetic algorithm based on adaptive and reverse search mechanism is designed to solve the charging station construction scheme.The comparison and analysis of the improved and standard genetic algorithms as well as two multi-objective transformation methods are provided to demonstrate the efficiency and applicability of the proposed model and algorithm.A number of sensitivity analysis show that different confidence levels and charging station service radius have effects on the objective functions.Secondly,for the construction of charging stations based on the path demand,this dissertation studies the problem of multi-period fuzzy planning for multi-level EV charging stations under the inter-city expressway.Based on the AC-PC location model,considering the fuzziness of travel demand,charging station construction cost and operation cost,a fuzzy programming model with the goal of maximizing the traffic flow of the whole periods is constructed based on credibility theory under the constraints of charging station service capacity and construction budget of each period.The model is justified using the benchmark Sioux Falls road network and compared with myopic method.The results indicate that the charging station layout scheme is subject to a number of major factors,including vehicle range,capital budget and confidence level.