Multi-Time Scale Economic Scheduling Method Based on Day-Ahead Robust Optimization and Intraday MPC Rolling Optimization for Microgrid
Jing Zhang, Dian Qin, Yongchun Ye, Yu He, Xiaofan Fu, Jing Yang, Guoyi Shi, Heng Zhang
Abstract
Due to the source and load prediction errors and uncertainties, the real operation state of microgrid may deviate significantly from the expected state, which leads to prevent the system from reaching its expected economic effects. In order to obtain the optimal economic effects for microgrid scheduling, an optimal microgrid scheduling model considered the demand responses is built in this paper firstly, and then a multi-time scale economic scheduling method based on day-ahead robust optimization and intraday model predictive control (MPC), is developed as well. Moreover, in the day-ahead stage, the long-time scale interval is set as 1 h and robust optimization is used to address the low-frequency component issues in prediction errors and uncertainties. Meanwhile, the robust optimization enables to gain the day-head optimal economic scheduling plan for the microgrid and to keep the system operating effectively even when large-scale fluctuations happen. Furthermore, in the intraday stage, the short-time scale interval is set as 15 mins and MPC is adopted to track and roll-correct the day-ahead economic scheduling plan, which enables to address the high-frequency component issues in prediction errors and uncertainties. Finally, simulation results demonstrate the feasibility of the proposed optimal microgrid scheduling model and the validity of the proposed multi-time scale economic scheduling method.