An adaptive distributed Model Predictive Control for buildings temperature regulation
In recent years, Model Based Predictive Control (MPC) constitutes an important research trend in the control of advanced heating, ventilation and air conditioning (HVAC) systems in order to find a compromise between the energy savings and the occupant thermal comfort. An adaptive MPC law for the regulation of the indoor temperature of a three-zones building was carried out. Two different strategies of adaptive MPC (dynamic temperature set-points and dynamic weighting coefficients of the cost function) were proposed to achieve even higher performances and energy savings ensuring temperature regulation on the basis of the occupancy level of each building zone. The experimentation was carried out considering the thermal coupling between the zones, thus comparing two possible MPC architectures (distributed and decentralized) to demonstrate the effectiveness of MPC distributed approach in terms of computational costs and control results (consumed energy and comfort).
For more information see:
Lauro, Fiorella; Longobardi, Luca; Panzieri, Stefano, “An adaptive distributed predictive control strategy for temperature regulation in a multizone office building,” Intelligent Energy Systems (IWIES), 2014 IEEE International Workshop on , vol., no., pp.32,37, 8-8 Oct. 2014