Optimal Energy Management in Multi-Microgrids. A Scenario-Based MPC Approach

In view of the advancements in microgrids technology, energy management plays an important role in optimizing energy resources and minimizing operational costs, however including distributed energy resources in the microgrids makes the system variability increase, then, an adequate control strategy is necessary for exploiting these resources appropriately. This study presents an intraday Energy Management System employing a Scenario-Based Model Predictive Controller in a multi-microgrid configuration. A hierarchical controller is proposed to minimize the economic cost of the deviations with respect to the day-ahead scheduling, in front of the uncertainty in renewable generation. The formulation guarantees a preset constraint violation probability, while simplifying the treatment of uncertainty. The results demonstrate that the approach outperforms the behavior of a deterministic Model Predictive Controller, reducing the economic costs by 16%. Moreover, it significantly reduces power deviations by up to 49%. This work highlights the potential of Scenario-Based Model Predictive Control as a promising tool for real-time multi-microgrid management, offering effective management of the uncertainty and guaranteeing probabilistic constraint satisfaction.