4.7 Article

A Control Framework to Enable a Commercial Building HVAC System for Energy and Regulation Market Signal Tracking

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 38, Issue 1, Pages 290-301

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2022.3156867

Keywords

HVAC; Fans; Atmospheric modeling; Buildings; Cooling; Mathematical models; Water heating; Commercial building HVAC system; two-level control; energy and regulation market signal tracking; control-oriented model; Dymola high fidelity model

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Commercial buildings are valuable resources for demand response in energy and regulation markets. However, current control methods overlook the influence of fan control on the power consumption of water loop pumps and chillers. This paper presents a complete model of a commercial building HVAC system and develops a two-level control method for tracking energy market signals and frequency regulation signals, resulting in significant improvement in tracking accuracy.
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.

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