TRACTABLE PREDICTIVE CONTROL STRATEGIES FOR HEATING SYSTEMS IN BUILDINGS

Model Predictive control is an advanced control tech-nique that has been used to optimize thermal comfort in buildings. Nowadays, the new buildings are char-acterized by an important inertia as well as low power heating systems. Since the thermal losses are very low, taking into account the intermittent occupancies in the control strategy is questionable. More precisely, in this paper, two model predictive controllers are devel-oped to reduce energy consumption while preserving the thermal comfort. These strategies keep using the local controllers and they are adapted for being imple-mented in embedded systems. The simulation results show lower energy consumptions and higher comfort levels in comparison with non-predictive strategies