Two-stage charging scheduling optimization of electric vehicles based on user behavior

With the continuous improvement of the penetration rate of electric vehicles, it hurts the economic and stable operation of the power grid, to reduce the power grid load fluctuation caused by random charging of electric vehicles, In this paper, a two-stage charging strategy is proposed. Firstly, the probability distribution model is calculated according to the travel characteristics of users, and then the charging model is established by the Monte Carlo method combined with the information on charging piles, battery characteristics, and automobile scale. Finally, the impact of this strategy on the power grid is described by taking valley peak value, saving rate, and travel rate as evaluation indexes. Simulation results show that this strategy can meet the driving needs of users, reduce travel anxiety information, and reduce the peak-valley load gap of the power grid. It is an orderly charging strategy integrating the power grid and user sides.