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.
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Acknowledgements
This work was supported in part by the National Key Research and Development Program of China (2016YFB0901900 and 2017YFC0704100).
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Zhuang, L., Chen, X., Guan, X. (2019). Regression Model of Wet-Bulb Temperature in an HVAC System. In: Fang, Q., Zhu, Q., Qiao, F. (eds) Advancements in Smart City and Intelligent Building. ICSCIB 2018. Advances in Intelligent Systems and Computing, vol 890 . Springer, Singapore. https://doi.org/10.1007/978-981-13-6733-5_18
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DOI: https://doi.org/10.1007/978-981-13-6733-5_18
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