Model predictive control for optimal integration of a thermal chimney and solar shaded building

Abstract

Energy-saving devices are extensively sought in several fields, including heating, ventilation, and air-conditioning (HVAC) tasks in buildings. This paper investigates six model predictive control (MPC) strategies as a way to optimize the operation of a solar shaded, natural ventilated building located at TU Delft campus. Such building is based on an innovative combination of a thermal chimney and glazing walls for harvesting passive energy. The main challenge is dealing with the system dynamics. The predictive controllers we consider include both linear and nonlinear MPC, and four hierarchical MPC strategies. All controllers aim to minimize auxiliary power consumption and, consequently, increasing the energy savings. The six control strategies performance are evaluated using reference values for thermal comfort, while relying on simulations performed in MATLAB for calculations. The hierarchical MPC architecture which considers a hybrid structure with nonlinear tracker for ventilation and linear agents for heating purposes appears the most promising one.