Open AccessDevelopment of Stochastic Models of Window State Changes in Educational Buildings
Author(s) -
Jing Liu,
Runming Yao,
Rechel McCloy
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/304/3/032065
Subject(s) - occupancy , window (computing) , thermal comfort , computer science , environmental science , simulation , architectural engineering , engineering , meteorology , geography , operating system
How people would like to interact with surrounding environment will subsequently influence indoor thermal conditions and further impact building energy performance. In order to understand occupants’ adaptive behaviours in terms of environmental control utilization from the point of view of quantification, an investigation on windows operation was carried out in non-air-conditioned educational buildings in the UK during summer time considering the effects of occupant type (active and passive) and the time of a day. Outdoor air temperature was a better predictor or window operation than indoor air temperature. Window operation was found to be time-evolving event. The purpose or criteria of adjusting window states were different at different occupancy stages. Active occupants were more willing to change windows states in response to outdoor air temperature variations. Sub-models predicting transition probabilities of window state for different occupant type and occupancy stages were developed. The results derived from this field study are helpful with improving building simulation accuracy by integrating sub-models into simulation software and further providing guideline on building energy reduction without sacrificing indoor thermal comfort.