Abstract: With the increase of both the number of electric vehicles connected to the grid and battery capacity, the uncoordinated charging has been bringing tremendous pressure to the grid, and even affecting the stability of the operation of the grid. On the contrary, a reasonable dispatch of electric vehicles can bring additional benefits to the grid. This paper proposes a sliding window variable speed optimization charging method for achieving the real-time V2G scheduling of grid-connected electric vehicles. The real-time electricity prices are combined to minimize the economic costs; The network loss is quickly solved via the offline network loss sensitivity; The battery aging cost is quantified by using the charging power fluctuation method. By constructing a multi-objective optimization problem composed of battery aging cost, charging cost, and grid loss cost minimization, the V2G real-time scheduling strategy is obtained via a convex optimization algorithm. Finally, via the improved IEEE33 node distribution network, the comparative experiments are made about the average distribution scheme, natural charging scheme, and the proposed sliding window variable speed optimized charging scheme. It is shown from the experimental results that the proposed scheme can slow down the battery aging and effectively reduce the charging costs and network losses, and balance the loads.