Optimal Partitioning of Multithermal Zone Buildings for Decentralized Control

In this article, we used an optimization-based systematic methodology for the challenging, less studied, and important problem of optimal partitioning of multithermal zone buildings for decentralized control. The proposed methodology consists of: i) construction of a graph-based network to quantitatively characterize the thermal interaction levels between neighboring zones and ii) the application of two different approaches for optimal clustering of the resulting network graph: 1) stochastic optimization and 2) robust optimization. The proposed optimization methods were tested and compared with each other on two case studies: 1) a five-zone building (a small-scale example) which allows one to consider all possible partitions to assess the success rate of the developed methods and 2) a 20-zone building (a large-scale example) for which the developed methods were used to predict the optimal partitioning of the thermal zones. Compared to the existing literature, our approach provides a systematic and potentially optimal solution for the considered problem.