A simplified modeling of cooling coils for control and optimization of HVAC systems

A cooling coil unit (CCU) is nonlinear in nature. Existing CCU models for control and optimization are either linear approximations around an operating point or very complex nonlinear ones, resulting in difficulties for real time applications. Therefore, it is of practical importance to develop a si...

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Bibliographic Details
Published in:Energy conversion and management 2004-11, Vol.45 (18), p.2915-2930
Main Authors: Wang, Yao-Wen, Cai, Wen-Jian, Soh, Yeng-Chai, Li, Shu-Jiang, Lu, Lu, Xie, Lihua
Format: Article
Language:English
Subjects:
Air conditioning. Ventilation
Applied sciences
Chilled water
Cooling coil
Devices using thermal energy
Energy
Energy. Thermal use of fuels
Exact sciences and technology
Heat exchangers (included heat transformers, condensers, cooling towers)
Heat transfer
Heating, air conditioning and ventilation
HVAC systems
Modeling
Techniques, equipment. Control. Metering
Theoretical studies. Data and constants. Metering
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Summary:A cooling coil unit (CCU) is nonlinear in nature. Existing CCU models for control and optimization are either linear approximations around an operating point or very complex nonlinear ones, resulting in difficulties for real time applications. Therefore, it is of practical importance to develop a simple, yet accurate CCU engineering model that will yield better real time control and optimization of heating, ventilating and air conditioning (HVAC) systems. In this paper, a technique for developing a simple, yet accurate engineering CCU model is presented. The modeling technique is based on an energy balance and heat transfer principles. Commissioning information is then used to estimate, at most, three model parameters by either a linear or nonlinear least squares method. Experiment shows that the method is robust and gives a better match to real performance over the entire operating range when compared to existing methods in the literature. This model is expected to have wide applications in control and optimization of HVAC systems. The modeling methodology can also be extended to other heat exchangers.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2003.12.024