Investigating the probability of behavioural responses to cold thermal discomfort
Investigating the probability of behavioural responses to cold thermal discomfort
In buildings, occupant behaviour is recognised as a major contributing factor to energy demand and in particular to heating consumption. To achieve thermal comfort within the heating season, people report to use heat in very different ways; for example behaviours include switching on the heating system, putting on warm clothes, drawing curtains, changing rooms, making a hot drink and using a hot water bottle. While research has focused on subjective accounts using interviews, diaries and questionnaires, little is known about the frequency and probability of these behaviours. Using a mixed-method approach, this paper reports on the results of a field study in dwellings using wearable and environmental sensors. The analysis investigates the probability of these behavioural responses as a function of seven independent variables; (1) external and (2) internal monitored temperature, (3) probability of heating being on or off, (4) time of the week, (5) time of the day, (6) the three categories of the predictive thermal comfort model, and (7) the three categories of the adaptive thermal comfort model. Results show that participants were more likely to increase their clothing and activity level as internal temperature decreased, although there was no significant change in activity level throughout the course of a day. Methodologically, this paper demonstrates the effectiveness of different statistical tools in analysing occupants' behaviours. Substantively, this paper emphasises the need for future research to gather objective data on what people do.
adaptive behaviours, occupant surveys, ubiquitous sensors, behaviour analysis, thermal comfort
1-31
Gauthier, Stephanie
4e7702f7-e1a9-4732-8430-fabbed0f56ed
Gauthier, Stephanie
4e7702f7-e1a9-4732-8430-fabbed0f56ed
Gauthier, Stephanie
(2016)
Investigating the probability of behavioural responses to cold thermal discomfort.
Energy and Buildings, .
(doi:10.1016/j.enbuild.2016.04.036).
Abstract
In buildings, occupant behaviour is recognised as a major contributing factor to energy demand and in particular to heating consumption. To achieve thermal comfort within the heating season, people report to use heat in very different ways; for example behaviours include switching on the heating system, putting on warm clothes, drawing curtains, changing rooms, making a hot drink and using a hot water bottle. While research has focused on subjective accounts using interviews, diaries and questionnaires, little is known about the frequency and probability of these behaviours. Using a mixed-method approach, this paper reports on the results of a field study in dwellings using wearable and environmental sensors. The analysis investigates the probability of these behavioural responses as a function of seven independent variables; (1) external and (2) internal monitored temperature, (3) probability of heating being on or off, (4) time of the week, (5) time of the day, (6) the three categories of the predictive thermal comfort model, and (7) the three categories of the adaptive thermal comfort model. Results show that participants were more likely to increase their clothing and activity level as internal temperature decreased, although there was no significant change in activity level throughout the course of a day. Methodologically, this paper demonstrates the effectiveness of different statistical tools in analysing occupants' behaviours. Substantively, this paper emphasises the need for future research to gather objective data on what people do.
Text
elsarticle_Gauthier_Manuscript.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 14 April 2016
e-pub ahead of print date: 23 April 2016
Keywords:
adaptive behaviours, occupant surveys, ubiquitous sensors, behaviour analysis, thermal comfort
Organisations:
Energy & Climate Change Group
Identifiers
Local EPrints ID: 392780
URI: http://eprints.soton.ac.uk/id/eprint/392780
ISSN: 0378-7788
PURE UUID: 936c523c-f0fe-43a5-b4e4-84a5a10e4bab
Catalogue record
Date deposited: 18 Apr 2016 13:06
Last modified: 15 Mar 2024 05:29
Export record
Altmetrics
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics