Research On Scheduling Strategy Of Electric Vehicle Based On V2G

Environmental pollution and energy safety have been two important problems nowadays, and the appearance of electric vehicles provide important means to solve these two problems. Traditional vehicles replaced by electric vehicles is in favor of reducing air pollution caused by automobile exhaust. Fossil energy replaced by electrical energy to drive cars is in favor of improving energy efficiency and relieving the energy crisis. While, the development of electric vehicles has inevitably impact on electric load.Large-scale electric vehicles charging in power grid can increase the power load fluctuation, affect the quality of electric energy. Therefore, solving charging problems of Large-scale electric vehicles and bring economic benefit for power grid, charging station and EV users are the most important issures in researching V2 G problems.This paper studies diferent scheduling strategies of EVs in charging mode and charging/discharging mode.In the study of scheduling strategies of EVs in charging mode. Firstly, introduce three charging mode of EV: immediately charging mode, off_peak charging mode and dispatching mode, and then simulate them with examples. The result shows that,immediately charging mode may increase the power grid load fluctuation and affect the quality of electric energy; off_peak charging mode may decrease the power load fluctuation to a certain degree, but it also may lead to another peak load at night for lots of EVs charging at the same time by night; dispatching mode can restrain load fluctuation gently, decrease the difference between peak load and valley load, and make the power grid load curve change more smoothly.To decrease the difference between peak load and valley load further, presenting scheduling strategies of EVs in V2 G technology based on EV battery's storage characteristics, and taking the minimized output fluctuation of the power load and maximized income of charging station and the users of EVs as objective function, several models were established. Results of calculation example indicate that the output fluctuation of the power load can be effectively suppressed and the income of charging station and the EV users can be increased through scheduling EVs charging/discharging in order. Then proves the advantage that coordinated scheduling in multi-objective to scheduling in single-objective.