A scenario-based distributed stochastic MPC for building temperature regulation

In this paper, we focus on the temperature regulation of rooms in buildings. By using the dynamic model of the thermal process, weather condition, occupancy and so on, a Stochastic Model Predictive Control (SMPC) problem is formulated to keep the temperature of rooms within a comfortable range with a predefined probability while consuming less energy. The temperature regulation problem in this paper is an optimal control problem of a linear system with additive uncertainty. To overcome the computational burden caused by the large number of rooms, a subgradient-based dual decomposition method is used to solve the SMPC problem in a distributed manner. Simulation results show the effectiveness of our results.