Abstract: A model predictive control based multiple time scale scheduling method is proposed for the microgrid system with smart buildings integrated. Firstly, the mathematical model of virtual energy storage system is developed to effectively use the flexibility of buildings due to their thermal dynamics of the envelope. The virtual energy storage system is optimized in the multiple time scale scheduling method for microgrid with smart buildings integrated. Then, a model predictive control based intraday rolling adjustment method is proposed. By using the rolling optimization in each control horizon, the operational schedules of the microgrid system can be adjusted accurately. Finally, taking refrigeration scenario in summer as an example, the effectiveness of the proposed method is verified by using the microgrid with smart buildings integrated. The results demonstrate that on the premise of guaranteeing comfort level of indoor temperature in the building, the proposed method can reduce the operating cost at the day-ahead economic optimization and dispatch stage and smooth the tie-line power fluctuations caused by day-ahead prediction error at the intra-day rolling adjustment stage.