Inter-Layer Interactions in Hierarchical MPC for Building Energy Management Systems
Résumé
In this paper, we consider a two-layer hierarchical Model Predictive Control (MPC) for building energy management systems. The upper layer implements a long term economical optimization that takes into account the energy price and the requirements of the occupants. The lower layer is used to ensure the tracking of the optimal scheduling plan predicted by the upper layer with a shorter prediction horizon and a higher sampling rate. The proposed work focuses on the interactions between the two levels, and investigates different strategies to project the results of the upper layer at the lower one. Comparisons of these strategies are provided, highlighting their impact on the closed-loop behaviour.