Optimal Scheduling Method for Battery Energy Storage Based on Adaptive Time Granularity

With the integration of many intermittent and distributed new energy sources into the power grid, the safe and stable operation of the power system is facing huge challenges. HVAC (Heating, Ventilation and Air Conditioning, HVAC), electric vehicles (EV), and battery energy storage (BESS) can be a solution to this problem due to high flexibility and strong controllability. Aiming at the problem of power imbalance caused by large-scale wind power integration, this paper proposed an optimal scheduling method of HVAC and BESS based on adaptive time granularity. Time granularity is critical to the optimization of scheduling methods, which is decided by the load fluctuation in this paper. The simulation results showed that reducing the time granularity can smooth the fluctuation of the tie-line but would increase the scheduling cost and the amount of calculation.