Optimization Of Ordered Charging Strategy For Large-scale Electric Vehicles

Environmental sustainability is a common topic of the international community,and development of electric vehicles(EVs)as a new alternative means of transport has become the focus in the world.The large-scale development of electric vehicles can not only improve the problems of environmental pollution and fossil energy shortage,but also lower the cost of travel compared with high oil prices.Today,the maximum driving distance of EVs is relatively short,and the charging facilities are not perfect.A lot of electric vehicles' disorderly charging behavior in time and space not only causes users to charge hard problems,but also affects the operation efficiency of charging facilities.Therefore,it is necessary to study the orderly charging strategy of EVs.In addition,the coordinated charging is based on the information exchange between the EVs and charging station,including location information,traveling route,vehicle type and so on,which is easy to cause the leakage of user privacy.Therefore,the information security involved in the coordinated charging of electric vehicles need to be studied in depth.The optimization strategies and solutions about the information security problems are put forward.The main works and specific researchs are summarized as follows:First,a charging strategy for electric vehicles based on spatiotemporal restriction to research the impact of charging station queuing is proposed.And a model of charging selection is established by minimizing the summation of round-trip time,waiting time and charging time.Simulation examples demonstrate that compared to the nearest selection of the charging station,the proposed method is more effective and feasible and can reduce the charging time greatly.Next,an orderly charging strategy for large-scale EVs is proposed.And the hierarchical clustering and quadratic division based on K-means are used to achieve the convergence of EVs with similar properties.Furthermore,the charging scheduling model based on electric vehicle clustering is constructed based on the utilization rate of the charging station and the charging distance of the EV as the objective function,and the genetic algorithm is used to solve the problem.The results show that both methods can solve the problem of EV charging in the region,but our method has more advantages.Finally,in order to realize the fast charging of EVs and improve the utilization rate of charging facilities,it is very important to protect the information safety of electric vehicle users and ensure the safe transmission of data information.So the charging network management system is established to realize information exchange between charging network and the needs of the user.The security of communication problems among EVs,management center and the charging station are studied.