Model reduction and nonlinear MPC for energy management in buildings

In this paper, we introduce a singular perturbations framework for the dynamic analysis and model reduction of building models. Working with a prototype building, we present a theoretical justification of the empirically acknowledged multiple time scale dynamic response of buildings, and develop a mathematically rigorous methodology for deriving reduced-order models for the dynamics in each time scale. Our analysis accounts for the potential use of Heat Recovery Ventilators (HRVs), and we show that their presence leads to the emergence of a dynamic behavior with three time scales, including an overall, system-wide component which involves both the building and the HVAC system. The second part of the paper presents a simulation case study, where we demonstrate the use of the derived reduced-order models in the synthesis of a nonlinear predictive model-based optimal energy management strategy for a single-zone test building situated on the University of Texas campus. The proposed controller exhibits excellent performance, can easily be executed in real-time and its application results in significant energy savings compared to setpoint tracking strategies.