A distributed MPC strategy based on Benders' decomposition applied to multi-source multi-zone temperature regulation

This paper presents a distributed model predictive control (DMPC) algorithm based on Benders' decomposition for temperature regulation in buildings using multiple heating sources. It is well known that the main objective of this control problem is to minimize the heating energy bills while maintaining a certain indoor thermal comfort. To reduce the heating costs, many buildings are equipped with different heating sources. An example is the use of a hot water based central heating system and local electric convectors as complementary heating sources. Using a linear system model of the controlled process, the MPC optimization problem can be solved by linear programming. In order to reduce the computational demand required to solve the minimization problem, the authors propose a DMPC algorithm based on the Benders' decomposition. The effectiveness of the proposed approach compared to the currently used PI-based control is illustrated in a simulation study.