Allocation Of Charging Stations For Electric Vehicles Considering Spatial Land Price And Limited Budget

Electric vehicle is the inevitable way for the development of the automobile industry.As the infrastructure construction of electric vehicles,the allocation of charging station is important for the development of electric vehicles.The allocation of charging station includes a variety of factors and problems.There are a lot of perspectives for scholars,such as objectives,solutions,factors,etc.In this thesis,the physical model of charging station allocation is established according to the random geometric graph and queuing theory.The allocation of charging station aiming at minimizing the average travel time of users is studied.The concept of spatial land price is introduced.The construction cost of charging piles on nodes is linked with its location,which makes the allocation of charging station closer to reality and brings many changes.The location and budget planning are two key poiunts of charging stations allocation.This thesis guides the location of charging stations with the help of node importance in complex networks.The node importance performs best is selected and verified in multiple scenarios.A budget planning algorithm(BPA)is designed based on tabu-search algorithm.This algorithm could get the optimal solution of the limited budget under spatial land price.The effectiveness of the algorithm is also verified in multiple scenarios.Mean while,this thesis makes a detailed discussion and analysis of the impact and cause brought by spatial land price.The work and innovations in this thesis are as follows:1.The traffic network model is established by random geometric graph.The traffic network is divided into regions,so that nodes in each region have their own advantages such as performance and price.The spatial land price model is appropriate to the reality.On this basis,the node importance in complex networks is used to provide guidance for charging station location.The four node importances are: degree centrality,weighted betweeness centrality,weighted closeness centrality and k-shell.Among them,the weighted betweeness centrality could get the minimum average travel time for users in different scenarios.The advantage of weighted betweeness centrality is mainly due to it could reduce the driving time of electric vehicles.2.Based on the weighted betweeness centrality,a budget planning algorithm is designed based on tabu-search algorithm.BPA could give a optimal budget planning under limited budget and spatial land price.The budget planning obtained by BPA allows EV users to obtain the minimum traveling time.Its performance is also proved to be universal in different scenarios.It is found that BPA can quickly and effectively find the saturated budget of the current spatial land price.It could effectively avoid the waste of budget.The change that spatial land price brought is analyzed.Under spatial land price,the three budget planning schemes on the waiting time performs as:BPA<Equal<Proportion.When the difference of land price gradually increases,the budget under BPA will gradually move away from the central area to the edge area.It will increase the number of charging piles in charging system,which leading to the increase of the carrying capacity.