The influence of sleeping habits on cooling energy use in residential sector in Hong Kong

• Published in: Building and environment 2018-03, Vol.132, p.205-213
• Main Authors: Bao, Yani, Liu, Tianqi, Lee, W.L.
• Format: Article
• Language: English
• Subjects: Comfort analysis; Computer simulation; Cooling; Cooling effects; Cooling energy use; Energy; Energy consumption; Habits; Prediction model; Prediction models; Residential areas; Residential energy; Simulation; Sleep; Sleep quality; Sleeping habits; Thermal energy
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2018.01.036

Sleep is a dominant part of our daily lives. People often have sleeping habits. Sleeping habit is referred as the preferred bedding system (type of bedding and sleepwear) and thermal environment. Thermal environment and cooling energy use are closely related. Many works have been done on sleep quality, sleeping habits, and the associated cooling energy use. However, it is noted that they are either separately or pairwise investigated. No investigations to date have been done to investigate their interactive effect. This study serves as a pilot study to fill the research gaps in investigating the interactive effect of sleep quality, sleeping habits and cooling energy use. Based on the use of three bedding systems and four temperature settings, 12 sleeping tests, each refers to one sleeping habit, were performed simultaneously in eight subjects. Sleepbot was employed to quantity sleep quality. Upon ascertaining the best sleep quality for different bedding systems, hour-by-hour energy simulations using EnergyPlus were conducted. It was found that for the use of light bedding systems, the associated drop in energy use would be 78.3% and 37.8% for female and male subjects respectively. Two prediction models, one relating energy use with thermal environment, and the other relating sleep quality with sleeping habit, have been established. The models can help quickly determine the tradeoff amongst sleep quality, sleeping habit and energy use. •Twelve simultaneous sleeping tests were conducted on eight subjects.•Each sleeping test adopted different bedding system and temperature setting.•Sleep quality measured by “toss and turn” and energy use simulated by EnergyPlus.•Interactive effect of sleep quality, sleeping habit and energy use were determined.•Prediction models were developed to enable trade-off decisions.