Model Development and Identification for Fast Demand Response in Commercial HVAC Systems

Abstract

Large commercial HVAC systems are attractive targets for fast demand response (DR) applications, e.g., integrating time-intermittent renewable generation. By leveraging the communications in the building automation system (BAS) already present in most buildings, large commercial HVAC systems provide easier access to a large controllable resource than aggregating a large number of small residential loads. However, large commercial HVAC systems are complex with many variables, many end point controllers, and several internal control loops that interact with each other. In addition, the existing fleet of large commercial buildings is diverse with many different HVAC configurations and BAS architectures. Capturing these buildings as DR resources requires a method to greatly reduce the complexity of the HVAC DR control and is general and flexible enough that it can be easily deployed across the diverse fleet of existing buildings. We create such a DR control by developing a system model that uses a single state variable instead of the several hundred variables in a commercial HVAC system. The model includes a small number of system parameters, and we demonstrate how their values can be determined via system identification measurements. Finally, we test our model on a large commercial HVAC system to investigate its control performance.