TY - GEN
T1 - Introducing thermal comfort attitudes, psychological, social and contextual drivers in occupant behaviour modelling with Bayesian Networks
AU - Barthelmes, Verena M.
AU - Andersen, Rune K.
AU - Heo, Yeonsook
AU - Knudsen, Henrik
AU - Fabi, Valentina
AU - Corgnati, Stefano P.
N1 - Funding Information:
This research was part of the UserTEC project (User Practices, Technologies and Residential Energy Consumption) (www.sbi.dk/usertec), which was financed by Innovation Fond Denmark.
Publisher Copyright:
© 2018 Proceedings of 10th Windsor Conference: Rethinking Comfort.
PY - 2018
Y1 - 2018
N2 - The acknowledgment of occupant behaviour as a key driver of uncertainty in building energy analysis is today well established. Existing literature highlights the need of carefully addressing human-related interactions with the building envelope and systems. In response to this need, researchers have proposed a number of stochastic models that aim at reflecting occupant behaviour patterns in building energy simulation to bridge the gap between simulated and real energy consumptions in buildings. However, most proposed approaches for modelling occupant behaviour consider time-related factors and physical parameters such as indoor or outdoor environmental variables while less attention is paid to other influential factors such as psychological, social and contextual drivers or individual thermal comfort attitudes and preferences of the occupants. To understand occupant behaviour in a comprehensive manner, these factors should be carefully addressed in upcoming occupant behaviour models. The Bayesian Network framework presents a promising environment for hierarchically and flexibly structuring a large number of explanatory variables that drive the occupant to perform a certain action. This paper describes the development of a theoretical model of occupant's window control behaviour with an extensive set of drivers and highlights the capability and usability of Bayesian Networks to develop such models based on field measurements and information collected through surveys compiled by the building occupants.
AB - The acknowledgment of occupant behaviour as a key driver of uncertainty in building energy analysis is today well established. Existing literature highlights the need of carefully addressing human-related interactions with the building envelope and systems. In response to this need, researchers have proposed a number of stochastic models that aim at reflecting occupant behaviour patterns in building energy simulation to bridge the gap between simulated and real energy consumptions in buildings. However, most proposed approaches for modelling occupant behaviour consider time-related factors and physical parameters such as indoor or outdoor environmental variables while less attention is paid to other influential factors such as psychological, social and contextual drivers or individual thermal comfort attitudes and preferences of the occupants. To understand occupant behaviour in a comprehensive manner, these factors should be carefully addressed in upcoming occupant behaviour models. The Bayesian Network framework presents a promising environment for hierarchically and flexibly structuring a large number of explanatory variables that drive the occupant to perform a certain action. This paper describes the development of a theoretical model of occupant's window control behaviour with an extensive set of drivers and highlights the capability and usability of Bayesian Networks to develop such models based on field measurements and information collected through surveys compiled by the building occupants.
KW - Bayesian Networks
KW - Occupant behaviour
KW - Residential buildings
KW - Window control behaviour
UR - http://www.scopus.com/inward/record.url?scp=85085842137&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85085842137
T3 - Proceedings of 10th Windsor Conference: Rethinking Comfort
SP - 972
EP - 988
BT - Proceedings of 10th Windsor Conference
A2 - Nicol, Fergus
A2 - Roaf, Susan
A2 - Brotas, Luisa
A2 - Humphreys, Michael A.
PB - NCEUB 2018
T2 - 10th International Windsor Conference 2018: Rethinking Comfort
Y2 - 12 April 2018 through 15 April 2018
ER -