The paper proposes a wind power consumption strategy with flexible resource coordination scheduling based on digital twin for the flexible resource aggregation and efficient consumption caused by the high proportion of new energy sources connected to the grid under low-carbon goals. Digital twin technology is used to achieve ultra-short-term forecasting of new energy generation output and load electricity consumption in response to the time-varying nature of environmental factors. Considering the energy storage characteristics and adjustable characteristics of electric vehicles(EVs), the load characteristics can be improved by optimizing the EV charging and discharging power and attributing EVs to different aggregators according to the location of charging posts. The corresponding objective functions are established in order to satisfy the demands of both grid side and users. Finally, The experimental results verify that the proposed strategy can achieve high accuracy prediction of wind turbines, reduce the level of wind power abandonment, and effectively reduce the load fluctuation.