The Prediction Of Electric Vehicles Charge And Discharge Capacity And The Study On The Control Strategy Of V2G

Vehicle-to-Grid technology is a new type of technology, which can accomplish the bidirectional exchange of the information and the energy under control. It emphasizes that EVs are not only electric power consumer, but also they can supply electric power to the grid as distributing power supply when they are available. With V2G technology, electric energy can be bidirectional exchanged effectively between EVs and the grid. And the process is real-time and under control. Power electronics, communications, dispatch and metering, load demand management and many other advanced technologies are integrated in V2G system, which is a superior comprehensive application.First, the concept of EVs is introduced. Then an idea that distributed connection and concentrated control for the amount of vehicles is presented for the limitation of VEs’ storage and wide distribution. An EVs control center as the third party is established between grid dispatching center and EVs, which works as the band of communication and coordination.Second, use of EVs follows the statistic law. Time of charging and discharging, and daily mileage can be obtained randomly by Monte Carlo method. And it is assumed that the time follows uniform distribution, the mileage follows logarithmic normal distribution. Prediction of EVs random load is significant for the dispatching scheme of grid dispatching center. And it can supply data support for the security maintenance of the system.Finally, based on the control zone and control layer, this paper focuses on how to control the process of charging and discharging of VEs effectively by EVs control center so that a win-win strategy of customers and the grid can be designed for the use of EVs.For the advantage of power grid, charging and discharging strategy of EVs is to be designed to serve peak load regulation, the mathematical model of vehicles participating load responses and accomplishing a dispatch scheme are established, and solve it by the Particle Swarm Optimization(PSO), in which constricts of available capacity of the battery, available time and exchange power are considered. Aimed at solving PSO’s premature convergence for high-dimensional problem, an improved PSO based on sub-vector is proposed, which shows greater searching ability for the whole space and better optimizing effect.For the advantage of consumer, strategy should be designed to bring economic profit to the consumer for the participation of V2G. This strategy is based on the conduction of real-time electricity price. An objective function aimed at maximizing profit of V2G users and charging and constraint condition set by discharging characteristics of battery, available energy and available capacity, we establish a mathematic. We optimize Then Charging and discharging time of a single user or a group of users with Binary Particle Swarm Optimization Algorithm (BPSO).