Optimal Charging Scheduling Of Electric Vehicles Based On CPSS

The establishment of the national energy strategic goal of ’ carbon peak,carbon neutrality ’ has provided unprecedented opportunities and impetus for the rapid development of electric vehicles.However,the construction of charging stations is relatively lagging behind,which seriously restricts the development of electric vehicles.Especially when the charging station fails,the charging satisfaction of the owner is further reduced.At this time,how to use the limited charging station resources to provide a reasonable charging guidance strategy for the electric vehicle waiting for charging at the fault station has become an urgent problem to improve the charging satisfaction of the owner.Therefore,it is urgent to carry out research on optimal scheduling of electric vehicle charging to provide reasonable charging guidance for electric vehicle owners affected by charging station faults.However,electric vehicle owners have obvious social attributes and bounded rationality.Therefore,they are easily affected by their social networks,resulting in a certain subjective tendency in the choice of car owners.Thus,it affects the charging scheduling effect of electric vehicles.So,this paper comprehensively considers the subjective willingness of car owners to carry out research on optimal scheduling of electric vehicle charging after charging station failure.The main contents are as follows:Firstly,the CPSS model of electric vehicle charging scheduling system is established based on Cyber-Physical-Social system(CPSS).The model includes a physical network composed of charging stations,a cyber network composed of mobile terminals and a social network composed of electric vehicle owners.This paper analyzes how the charging station fault in the physical network affects the charging choice of the car owner in the social network through the cyber network.The queuing theory model is introduced to define the charging satisfaction function of the owner as the evaluation index of the scheduling strategy,and the optimal scheduling strategy of electric vehicle charging based on local load redistribution is designed.The feasibility of CPSS model used to describe the cascading propagation process of charging station faults in physical network,cyber network and social network is verified by simulation experiments.At the same time,the superiority of local load redistribution method over traditional nearest average distribution method is verified by comparative experiments.Secondly,based on the CPSS model,the influence of objective factors such as the State of Charge(SOC)of electric vehicles,the distance between charging stations,the electricity price of charging stations and the traffic conditions between charging stations on the choice of charging stations is further considered.The weighted complex network model of charging stations is established by defining the above objective factors as weights,and the CPSS model of electric vehicle charging is optimized and improved.A local load redistribution method based on weighted complex network model is designed to guide the charging of electric vehicles affected by charging station faults,so as to further improve the charging satisfaction of vehicle owners.The effectiveness and superiority of the charging guidance strategy are verified by comparative simulation experiments.Finally,on the basis of considering the above objective factors,the subjective factors of the car owner are further considered.In the process of repairing the fault charging station by the charging station operator,the owner faces two choices: leaving and continuing to wait.Considering the subjective will of the owner,the problem of the owner ’s go / stay selection is modeled as a two-state Markov decision model,and a fuzzy inference algorithm is proposed to solve the probability transfer matrix of the Markov decision model based on the objective factors such as the SOC of the electric vehicle and the queuing order.A charging guidance strategy based on Markov decision model and weighted complex network model is designed,which further improves the charging satisfaction of electric vehicle owners.The feasibility of Markov decision model in describing the charging choice of vehicle owners is verified by simulation experiments.The superiority of the scheduling strategy to the subjective factors of vehicle owners is verified by comparative experiments.