Robust Energy Management for Multi-Microgrids Based on Distributed Dynamic Tube Model Predictive Control

Multi-microgrids (MMGs) provide an effective modality to integrate high-penetration renewable energy as well as other distributed sources. However, the inherent uncertainties from nature and load demand significantly impact the secure operation of the MMGs system. Considering these challenges, this paper proposes a novel intraday robust energy management framework based on the distributed dynamic tube model predictive control (DD-TMPC) method for autonomous multi-microgrids, which has less conservativeness and more economic efficiency. The proposed strategy can dynamically capture the security operation range of the microgrid system based on the set theory and utilize two cooperative MPC controllers to decompose the original uncertainty optimal problem into two different time scale deterministic uncertainty-free scheduling problems, which have lower computation complexity. Furthermore, in order to better balance the robustness and economy of system operation, a game theory-based intraday distributed energy trading mechanism is designed which considers both the transaction expectations of the market participants and the efficiency of the equilibrium solution. Comprehensive simulation studies demonstrate the feasibility of the proposed DD-TMPC strategy.