Abstract
The multi-energy microgrid (MEMG) plays a significant role in improving energy utilization and flexibility of energy supply. However, the uncertainties of wind turbine (WT) and load demand in MEMG are inevitable, which brings challenges to MEMG scheduling. To deal with the uncertainties of MEMG with minimum operational cost, this paper proposes a tube model predictive control (TMPC)-based optimal scheduling strategy for MEMG coupled with electricity, heat, and natural gas. The proposed TMPC consists of two MPCs, namely the nominal MPC and the ancillary MPC. Firstly, without considering the uncertainties, the nominal MPC generates reference trajectories with the goal of economy on tightened constraints. Further, considering the multiple uncertainties, the ancillary MPC makes scheduling decisions for the actual system via steering the ancillary trajectories to those provided by the nominal MPC. In this way, the proposed TMPC-based strategy has robustness against uncertainties of MEMG. Simulations on a grid-connected MEMG are carried out to show the effectiveness and the computational efficiency of the proposed TMPC-based optimal scheduling strategy.
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