Distributed model predictive control based on Benders' decomposition applied to multisource multizone building temperature regulation

Daniel-Petru Morosan (1, 2) , Romain Bourdais (3) , Didier Dumur (2) , Jean Buisson (1)

1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 E3S - Supélec Sciences des Systèmes
3 IETR - Institut d'Électronique et des Technologies du numéRique

This paper presents a distributed model predic- tive control algorithm based on Benders' decomposition for temperature regulation in buildings. It is well known that the main objective of this control problem is to minimize the heating (cooling) energy bills while maintaining a certain indoor thermal comfort. In order to reduce the energy costs, many buildings are equipped with several heating sources with different dynamics, gains and energy prices, an example is the use of a hot water based central heating and local electric convectors as a complementary heating source. Using a linear system model of the controlled process, the MPC minimization problem can be solved by linear programming. The Benders' decomposition exploits a particular structure (block-angular) of the constraint matrix and distributes the computational demand among local controllers. The effectiveness of the proposed distributed control approach comparing to the currently used PI-based control is illustrated in a simulation study.

Daniel-Petru Morosan, Romain Bourdais, Didier Dumur, Jean Buisson. Distributed model predictive control based on Benders' decomposition applied to multisource multizone building temperature regulation. 49th IEEE Conference on Decision and Control, Dec 2010, Atlanta, United States. pp.3914-3919, ⟨10.1109/CDC.2010.5717092⟩. ⟨hal-00554675⟩