Abstract
Significant diversity between occupants and their presence and actions results in major uncertainty with regard to predicting building performance. However, many current occupant modelling approaches – even stochastic ones – suppress occupant diversity by focusing on developing representative occupants. Accordingly, existing approaches tend to limit the ability of stochastic occupant models to provide probabilistic building performance distributions. Using occupancy data from 16 private offices, this paper evaluated three hypotheses: (1) occupant parameters have a continuous distribution rather than discrete; (2) modelling occupants from aggregated data suppresses diversity; and (3) randomly selecting occupant traits exaggerates synthetic population diversity. The paper indicates that samples sizes for the studied occupants would have more appropriately been an order of magnitude higher: hundreds. This introductory paper shows that there are many future research needs with regard to modelling occupants.
Acknowledgements
The financial support from the Natural Sciences and Engineering Research Council (NSERC) Canada is gratefully acknowledged. This paper benefited greatly from discussion with members of IEA EBC Annex 66.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
William O’Brien http://orcid.org/0000-0002-0236-5383
Farhang Tahmasebi http://orcid.org/0000-0001-5727-2646