Electric Vehicle Fast Charging Station Planning Based On Travel Probability Matrix

In order to deal with the challenges brought by environmental pollution and energy security,it is of great significance to promote the application of electric vehicles(EVs)in the field of transportation.The production of EVs in China has now ranked first in the world.EV charging loads have a marked impact on the future of power grid.Meanwhile,fast charging stations are the key link in the promotion and development of EVs.Therefore,reasonable EV charging load prediction and fast charging station planning are important guarantees for the development of EVs.This paper focuses on the study of charging load prediction,siting and sizig of fast charging stations,which is shown as follows:(1)Firstly,The main factors which affect fast charging demands were analyzed from EV behavioral characteristics,driver travel characteristics and power battery charging characteristics.Secondly,driving characteristics of EVs were simulated based on urban road topology and improved speed-flow relationship model.Then driving path of EVs was simulated based on the trip probability matrix and Dijkstra algorithm.Monte carlo method was used to predict the spatial and temporal distribution of fast charging demands.Finally,the spatial and temporal distribution of EV charging loads were obtained based on the analysis of traffic network and distribution network.(2)Based on the spatial and temporal distribution of EV fast charging demands,the optimal siting and sizing of fast charging stations were studied under the constraint of distribution network.From the perspective of user-friendly charging,based on comprehensively construction and operation costs,minimizing driving and waiting costs for drivers,a constant volume model for the position of fast charging stations was established based on the constraints of the safety of distribution network and the distance between adjacent charging stations.The optimal sizing of fast charging station was optimized by M/M/c queuing theory model.The optimal siting and service partition were obtained based on Voronoi diagram and improved particle swarm optimization strategy.Finally,a simulation analysis of fast charging stationplan in a central urban area has been conducted to verify the feasibility and effectiveness of the model and method.