Distributed model predictive control for building temperature regulation

This paper presents a predictive control structure for thermal regulation in buildings. The proposed method considers a dynamic cost function trying to exploit the intermittently operating mode of almost all types of buildings. One of the key idea is to use the knowledge about the occupation profile. For that purpose, the predictive control strategy is first presented for a single zone building then extended to a multizone building example. Two opposite control strategies commonly exists. The decentralized control structure, which does not offer good performances especially when the thermal coupling among adjacent rooms is not negligible, and on the other hand, the centralized control for which the computational demand grows exponentially with the size of the system, being very expensive for large scale buildings. Our solution is based on a distributed approach which takes the advantages of the both methods mentioned above. A distributed MPC algorithm with one information exchange per time step is proposed with good control performances and low computational requirements.