Abstract

This paper proposes a two-level hierarchical energy management system (EMS) with demand side management (DSM) capabilities for grid-connected microgrids (MGs). The proposed strategy is based on model predictive control (MPC) with prediction intervals obtained through the fuzzy numbers method. While the Main Grid level EMS aims for auto-consumption within the MG, i.e., minimise the energy drawn for the main grid, the Microgrid level tracks power and consumption references, sent from the higher level, to manage the MG resources and the load consumption. Furthermore, fuzzy prediction intervals are used to determine the best-case and worst-case scenarios of operation and modify the load profile while the overall load during the MG operation is maintained. Operation data for generation and consumption from a real urban community is used to validate the performance of the proposed EMS. The results show that the proposed hierarchical EMS with DSM and an adequate prediction case can reduce weekly costs while maintaining overall consumption and a healthy battery usage compared to an EMS that has no way to modify the load. This concludes that a microgrid can improve its performance with the correct predictions and the commitment of the consumers.