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Regression Model of Wet-Bulb Temperature in an HVAC System

  • Luping Zhuang
  • Xi ChenEmail author
  • Xiaohong Guan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 890)

Abstract

It can result in substantial energy saving in heating, ventilation, and air-conditioning (HVAC) system by improving the control strategy of heating, ventilation, and air-conditioning system. However, it is challenging to obtain the optimal control strategy of an HVAC system due to its model’s complexity. In this paper, a regression model is proposed for the wet-bulb temperature which is a key variable in cooling tower and fan coil unit. The proposed model avoids the iterative computing process of obtaining the value of the wet-bulb temperature and reduces the complexity of an HVAC system’s model. Numerical results show that the proposed model takes less than 7% computing time to get the value of wet-bulb temperature, and the relative deviations are less than 0.4%, compared to the original model.

Keywords

Wet-bulb temperature Regression model HVAC system 

Notes

Acknowledgements

This work was supported in part by the National Key Research and Development Program of China (2016YFB0901900 and 2017YFC0704100).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Center for Intelligent and Networked System, Department of AutomationTsinghua UniversityBeijingChina
  2. 2.MOE KLINNS LabXi’an Jiaotong UniversityXi’anChina

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