Day-ahead and intraday multi-time scale microgrid scheduling based on light robustness and MPC
Yu He, Zetao Li, Jing Zhang, Guoyi Shi, Wenping Cao
Abstract
An optimized microgrid scheduling model is established considering demand responses, forecast errors, and the effects of uncertainties in different scheduling stages. A day-ahead, intraday, multi-time scale economic scheduling method based on light robust optimization and model predictive control (MPC) is also proposed. In the day-ahead, long-time-scale scheduling stage, light robustness optimization is used to cope with low-frequency components in prediction errors and uncertainties, and mitigates the deviations between the day-ahead scheduling plan and the actual economic scheduling outcomes under source and load forecast errors and uncertainties. At the intraday, short-time-scale stages, the MPC tracks the day-ahead light robustness economic scheduling plan, considering the high frequency components of prediction errors and uncertainties, so as to achieve robust open-loop control, better tracking results, and better economy. Analytical results demonstrate the effectiveness of the method.