Optimal Control Method of Variable Air Volume Terminal Unit System

Hyo-Jun Kim and Young-Hum Cho
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Hyo-Jun Kim: School of Architecture, Yeungnam University, Gyeongsan 38541, Korea
Young-Hum Cho: School of Architecture, Yeungnam University, Gyeongsan 38541, Korea

Energies, 2021, vol. 14, issue 22, 1-15

Abstract: This study reviewed the existing studies on the types of variable air volume (VAV) terminal units, control and operation methods, prediction models, and sensor calibration methods. As a result of analyzing the existing research trends on the system type, characteristics, and control method of VAV terminal units studies such as theoretical verification and energy simulation were conducted to improve the existing control methods, reset the set value using a mathematical model, and add a monitoring sensor for the application of control methods. The mathematical model used in the study of VAV terminal unit control methods was used to derive set values for minimum air volume, supply temperature, ventilation requirements, and indoor comfort. The mathematical model has a limitation in collecting input information for professional knowledge and model development, and development of a building environment prediction model using a black box model is being studied. The VAV terminal unit system uses a sensor to control the device, and when an error occurs in the sensor, indoor comfort problems and energy waste occur. To solve this problem, sensor calibration techniques have been developed using statistical models, mathematical models, and Bayesian statistical models. The possibility of developing a method for calibrating the variable air volume terminal unit sensor using the prediction model was confirmed. In conclusion, the VAV terminal unit system is one of the most energy efficient systems. The energy saving potential of current VAV systems can still be improved through control methods, the use of predictive models, and sensor calibration methods.

Keywords: variable air volume system; terminal unit; optimal control; prediction model; sensor calibration (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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