Volume 4: Innovative Solutions for Energy Transitions: Part III

Investigation on Occupants’ Interaction With Windows in University Building in Zunyi, China Jing Liu* , Zhangyong Li , Yi Chen1 , Ting Cai

Abstract

Adaptive action in terms of window operation has closely correlation with indoor air quality and building energy performance. Guizhou is as a traditional undeveloped area in China, even though the GDP growth rate in recent 5 years is remarkable, very few studies on adaptive behaviours in context of built environment are conducted. In this paper, an investigation on window operation considering the influence of subject type was carried out in HVAC-system-equipped university building during winter in Zunyi, China. Due to out of service of HVAC system, indoor thermal conditions are relative poor and not in the ASHRAE’s winter comfort zones. Outdoor air temperature is identified to be the only physical environmental variable driving window-opening behaviour in this study. Active occupants would like to adjust indoor thermal condition or to improve indoor air quality by means of operating windows. On contrary, passive occupants are reluctant to adjust windows during survey period. But overall, more surveyed windows are opened with the rising in outdoor air temperature. The mathematic models predicting the probabilities of window-opening occurrence are also developed based on logistic regression analysis. The predictive accuracy is 69.65%. This is the first time performing a study on interaction between occupants and window adjustments in Zunyi, China. The developed predictable models also fill in the blank the no quantitative models are available in this area. Therefore, the results concluded from the field study are helpful of providing unprecedented guidelines on improvement of indoor thermal environment and building energy efficiency in Zunyi, China. In addition, by integrating into simulation software the accuracy of dynamic simulation of building energy consumption can also be improved.

Keywords field study, window operation, predictive model, thermal environment