Utilizing flexibility in microgrids using model predictive control

We derive a control strategy for the operation of Microgrids (MGs) with high shares of Renewable Energy Sources involving Model Predictive Control (MPC). By combining the MPC with an Energy Management System (EMS) utilizing stochastic programming techniques and a sufficiently large temporal optimization window we improve the point of operation of the system regarding both short and long-term operational aspects. We aim for a system operation that allows for the utilization of the MG as a Virtual Power Plant. In this work we focus on the predictive controller design and the incorporation of information derived in the EMS layer.