Research On Charge And Discharge Control Strategy Of Electric Vehicle In V2G Mode

Electric vehicles utilize clean electricity as power source, which can effectively decrease the use of fossil fuels and reduce carbon emissions. As the continuous improvement of battery manufacturing technology and the charge and discharge facilities, electric vehicles will enter a new era of widespread application around the world. However the charging behavior of customers have randomness in time and space, thus the disorderly charging of large-scale electric vehicles will greatly impact on the load, operation and planning of the power grid. As an energy storage element, the electric vehicle battery can not only absorb energy from the system, but also transfer energy to the system through V2G technology at the peak load of power grid. Therefore, in V2G mode, it is of vital significance to improve the reliability of power supply and to adopt renewable energy by guiding users to charge and discharge in good order by reasonable charging and discharging control strategy.This paper focuses on the research of charging and discharging control strategy of electric vehicles in V2G mode and the main work is summarized as follows:(1)The charging load model of large-scale EVs based on the probability sampling in Monte Carlo method is established in this paper. Simulation results show that the disorderly charging load of the EVs aggravates the "peak plus peak" phenomenon of grid load and increases the pressure of peak-shaving and operating of power grid.(2)The orderly charging and discharging model based on spatial-temporal bi-level optimization is established in consideration of spatial and temporal distribution characteristics of EVs. The simulation examples realize the charging and discharging power optimization of EVs on the time dimension and assign the charging and discharging dispatch plan of EVs on each V2G node at different times reasonably.(3)The micro-grid economic dispatch model containing EVs and distributed generations is proposed with the objectives of the minimum equivalent load fluctuations of system, the minimum cost of power generation system and the maximum charging and discharging benefits of user. NSGA-â…¡ algorithm is used to solve the model. Through the comparative analysis of different scenarios, it can be concluded that V2G scheduling of EVs not only matches the power fluctuations of load and DGs as the storage backup, but also helps to improve the quality of power supply and the economic operational level of micro-grid.