Research On The Hierarchical Location-sizing Problem Of Electric Vehicle Charging Infrastruture Deployment In The City

The high dependence on oil resources has brought about a series of problems such as energy crisis,political turmoil,air pollution,global warming and so on,which has attracted worldwide attention.Studies have shown that transportation industry is playing a key role in both energy consumption and pollution emission.Over the past 10 years,transportation systems have accounted for more than one-third of the total oil consumption around the world.In the meantime,transport has also contributed 25%of the world’s total growth rate of carbon dioxide emissions,which can even be up to 50%in East Asia.In this context,electric vehicle is gradually becoming the main alternative to traditional vehicles for its energy-saving and environmentally friendly characteristics.In order to advance the development and popularization of electric vehicles,many countries are vigorously promoting the construction of supporting facilities such as charging infrastructure.So how to plan the location and capacity of charging stations scientifically has become a major issue imminent to solve in this process.The problem of electric vehicle charging infrastructure layout planning is systematically studied in this paper to deal with some practical issues encountered in cities of China,especially those with an early electric vehicle market.Firstly,given the dissimilar traffic characteristics of different regions in a city,especially the different impact of static traffic distribution and dynamic traffic flow on electric vehicle charging demand,it is proposed that a hierarchical planning model is needed to achieve the correspondence between demand and supply,avoiding waste of resources.Secondly,the charging demands of electric vehicles at city centers and periphery areas are classified into two types:node demand and flow demand.Correspondingly,the slow charging infrastructure planning model is proposed aimed at node demand using mixed integer programming with an objective of maximizing the demand nodes covered and minimizing the total distance cost,while the fast charging infrastructure planning model is aimed at flow demand with an objective of maximizing the total captured flow.After the optimal locations of charging stations have been determined,the sizing model are presented to determine the best service capability of the stations in order to achieve the equilibrium between supply and demand.Finally,the City of Nanjing is taken as a case study.Combined with the simulated data of electric vehicle charging demand,the proposed models are tested to deploy charging infrastructure in city center and periphery area.Heuristic algorithms like greedy algorithm and genetic algorithm are adopted to solve the model.The results show that the hierarchical planning model is able to find effective solutions in a large-scale traffic network.