Research On Layout Optimization Of Urban Electric Vehicle Charging Facilities Based On Agent Simulation

With the depletion of natural resources,the energy crisis and the deterioration of the ecological environment have become the focus of sustainable development in the world.As a new type of environmentally friendly transportation vehicle,electric vehicles play a vital role in the development of low-carbon transportation.In order to promote the development of the electric vehicle industry,the Chinese government has invested a large amount of money to purchase electric vehicle subsidies and support the construction of charging piles.At present,the mainstream construction mode of charging piles is to divide the fixed parking space for the construction of charging piles on the basis of the existing parking lot.However,due to the failure to accurately predict the regional charging demand,the hot-spot parking lot often has no piles to be recharged,and the unpopular area is idle and wasteful.In this case,the configuration of the charging pile is in conflict with the "difficult parking" of the fuel vehicle.Therefore,it is necessary to reasonably predict the charging demand of each charging station and to reasonably allocate the number of charging piles.Therefore,based on the investigation of the spatio-temporal characteristics of electric vehicle charging in two charging stations in Hangzhou,this paper constructs an agent simulation model,which has functions such as charging demand forecasting,path planning,charging information release,and charging pile optimization layout.Taking the nine parking lots in the Wulin Commercial Circle of Hangzhou as an example,the prediction of regional charging demand and the optimization of charging pile layout are explained.The charging demand forecast results show that there is a huge difference in the demand for charging piles between different charging stations,and there is a large space for layout optimization;the demand for slow charging piles is nearly twice the demand for fast charging piles.With the increase in the proportion of electric vehicles,the demand for fast charging piles has increased non-linearly,and the demand for slow charging piles has increased approximately linearly.Based on the prediction of charging demand,the input parameters of the combination of fast charging pile,slow charging pile and common parking space in each parking lot are constructed,and the sum of the minimum queuing time of electric car and fuel car and the time of transfer to new parking lot are constructed.Optimize the model for the layout of the objective function.Optimized by genetic algorithm.The simulation results show that when the proportion of electric vehicles is small,the time cost of queuing or transferring to the new charging station is the same as the time cost of the fuel car queue or the transfer to the new charging station.More will increase the sum of the time and cost of all vehicles;after increasing the weight of the electric vehicle travel time,by optimizing the number of charging piles,the target function is reduced by 17.1%compared with the initial charging pile.