A Chance Constrained MPC-Based Microgrid Central Controller for Building-Sized Hybrid Microgrids

Abstract

This work presents a microgrid central controller (MGCC) based on a Model Predictive Control (MPC) strategy that aims to optimize the operational cost for single building hybrid microgrids, considering the existence of renewable generation and an energy storage system. The formulation is done in terms of active and apparent power, leading to a Mixed Integer Linear Programming (MILP) problem, and take into account power factor rules. The uncertainties on the load prediction are addressed by using a chance constrained approach. In order to verify the proposed technique, its performance was evaluated on a study case microgrid through simulation, where the MGCC commands the power delivered by the converter linking the DC and AC buses and managing the energy storage.