A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modelling of occupant behaviour in non-residential mixed-mode buildings: The distinctive features of tropical climates
Abstract This paper focuses on the modelling of occupant behaviour in the case of a non-residential mixed-mode building on the tropical island of La Réunion. For such areas and types of buildings, occupants can operate passive solutions to achieve comfort while energy-consuming ones can offer alternatives during the hottest months. Yet, compared to other climatic zones, specific knowledge on occupant comfort and behaviour is limited, making the work of engineers difficult during the design phase. In this work, occupants’ operations on hygrothermal comfort controls, such as windows and fans, were first measured and analysed. Secondly, these behaviours were modelled using two deterministic methods based on machine learning techniques and a probabilistic graphical model. A model was also implemented to estimate the number of people, using the power demand of the electrical outlets. The estimation ability of the behavioural models was evaluated and led to F1 scores greater than 0.7. A two-classifier model was proposed to estimate the level of ceiling fan use. This combined model slightly improves the F1 scores by more that 2%, which demonstrates the necessity of taking into account the links between the different controls.
Modelling of occupant behaviour in non-residential mixed-mode buildings: The distinctive features of tropical climates
Abstract This paper focuses on the modelling of occupant behaviour in the case of a non-residential mixed-mode building on the tropical island of La Réunion. For such areas and types of buildings, occupants can operate passive solutions to achieve comfort while energy-consuming ones can offer alternatives during the hottest months. Yet, compared to other climatic zones, specific knowledge on occupant comfort and behaviour is limited, making the work of engineers difficult during the design phase. In this work, occupants’ operations on hygrothermal comfort controls, such as windows and fans, were first measured and analysed. Secondly, these behaviours were modelled using two deterministic methods based on machine learning techniques and a probabilistic graphical model. A model was also implemented to estimate the number of people, using the power demand of the electrical outlets. The estimation ability of the behavioural models was evaluated and led to F1 scores greater than 0.7. A two-classifier model was proposed to estimate the level of ceiling fan use. This combined model slightly improves the F1 scores by more that 2%, which demonstrates the necessity of taking into account the links between the different controls.
Modelling of occupant behaviour in non-residential mixed-mode buildings: The distinctive features of tropical climates
Payet, Maareva (author) / David, Mathieu (author) / Lauret, Philippe (author) / Amayri, Manar (author) / Ploix, Stéphane (author) / Garde, François (author)
Energy and Buildings ; 259
2022-01-20
Article (Journal)
Electronic Resource
English
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