Optimization Of Multi-party Interactive Charging Scheduling For Electric Vehicle Based On Real-time Traffic Network

Because of its high energy efficiency and zero pollution emission,electric vehicles have been popularized by various countries,and the number of matching charging infrastructure has increased rapidly,which has also brought about the problems of "having cars without piles" or "having piles without cars" at the same time.Therefore,it is of great theoretical significance and application value to optimize charge scheduling for electric vehicles to effectively balance the utilization rate of charging stations and improve the charging convenience of electric vehicles.Because electric vehicles charging scheduling is affected by the time-varying of traffic network,the competitive behavior among multiple charging stations and the time-varying of owner’s charging scheduling benefits,traditional charging scheduling method for electric vehicles is difficult to provide efficient and feasible charging scheduling scheme according to the above existing problems.As a result,the charging waiting time and charging cost of electric vehicles’ owners are increased,and the charging congestion rate of charging stations is improved.In view of the above problems,this paper proposes the optimization method of multi-party interactive charging scheduling for electric vehicles based on real-time traffic network.The main research contents are as follows:The first chapter is the introduction part,which mainly introduces the research background and significance of electric vehicles charging scheduling,as well as the research status of the traffic network model,multi-party interactive charging scheduling optimization based on multiple charging stations and dynamic driving charging scheduling optimization of electric vehicles.The second chapter improves the traditional traffic network model according to the characteristics of both static and dynamic attributes of the traffic network.Firstly,Based on the road network topology diagram,static road resistance model and dynamic road resistance model,the dynamic and static road resistance factor model of road network is established.Secondly,the dynamic and static comprehensive model of traffic network is established by considering the dynamic and static road resistance model of road network,and the static optimal path solving algorithm is improved to plan the optimal charging path of electric vehicles in real time according to the road condition.Finally,the dynamic and static comprehensive model of traffic network is simulated and analyzed respectively under the condition of destination determination and uncertainty to verify the superiority of the model.In the third chapter,aiming at the real-time information interaction of electric vehicles in the process of charging scheduling among multiple charging stations in the area,a scheduling optimization method based on charging station interaction is proposed.Firstly,a kind of "vehicle-traffic network-station-distribution network"interaction mode is introduced,then the characteristic quantity model of electric vehicles is established to solve the characteristic quantity uploaded to the dispatching center,and the characteristic quantity model based on the interaction among charging stations is established to solve the characteristic constant and characteristic variable of charging stations.Finally,the optimization algorithm is improved and the superiority of the multi-party interactive scheduling optimization method based on charging station interaction is verified by simulation.In the fourth chapter,in the light of the time-varying characteristics of charging benefits in the process of electric vehicles going to charging stations after being dispatched,the dynamic model of electric vehicles driving is established according to the change of vehicle owner’s real-time charging benefit.In addition,the optimization method of electric vehicles dynamic driving charging scheduling is proposed.In order to realize the goal of adjusting the charging strategy according to the charging benefit of electric vehicles,the guidance strategy is simulated and analyzed by concrete examples.