A Control Framework to Enable a Commercial Building HVAC System for Energy and Regulation Market Signal Tracking
IEEE Transactions on Power Systems
Commercial buildings are great demand response resources in the energy and regulation markets. Many commercial building heating, ventilation and air conditioning (HVAC) systems are composed of a chiller producing chilled water, and multiple Air-Handling Units (AHUs) distributing cooled air to thermal zones. Demand response of such systems has the potential to closely track energy and regulation market signals. However, existing control methods are mostly focused on fan control, neglecting the impact of the air loop fan control on the power consumption of water loop pumps and chillers. This paper presents a complete modeling of a commercial building HVAC system consisting of chiller, water pump and multiple AHUs, and develops a two-level control to follow five-minute energy market signals and four-second frequency regulation signals. The first-level coarse control provides commands for both water and air loop variables, the second-level fine control adjusts the fan commands while maintaining the water loop inputs within the five-minute control period. As a result, the water-loop power serves as a basis to track energy market signals and the air-loop fan control can be adjusted flexibly for frequency regulation. A high-fidelity model in Dymola is built to validate the model and control. The validation is conducted through co-simulation between Matlab and Dymola model via the Building Controls Virtual Test Bed (BCVTB). The simulation results show significant tracking improvement with the proposed two-level control framework.
U.S. Department of Energy
Commercial building HVAC system, control-oriented model, Dymola high fidelity model, energy and regulation market signal tracking, two-level control
Industrial and Systems Engineering
Wenyi Wang, Guanyu Tian, Qun Zhou Sun, and Hongrui Liu. "A Control Framework to Enable a Commercial Building HVAC System for Energy and Regulation Market Signal Tracking" IEEE Transactions on Power Systems (2023): 290-301. https://doi.org/10.1109/TPWRS.2022.3156867