Abstract
Energy consumption and thermal comfort in residential buildings are highly influenced by occupant behavior, which exhibits a high level of day-to-day and dwelling-to-dwelling variance. Although occupant behavior stochastic models have been developed in the past, the analysis or selection of a building design parameter is typically based on simulations that use a single “average” occupant behavior schedule which does not account for all possible profiles. The objective of this study is to enhance the understanding of how window-to-wall ratio (WWR) of a residential unit affects heating demand and thermal comfort when considering occupant behavior diversity through a parametric analysis. To do so, a stochastic occupant behavior model generates a high number of possible profiles, which are then used as input in an energy simulation of the dwelling. As a result, one obtains probability distributions of energy consumption and comfort for different WWR values. The paper shows that the shape of the probability distributions is affected by WWR and dwelling orientation, and that the influence of different occupant behavior aspects on performance also varies with WWR. This work could help designers to better assess the impact of WWR for a large spectrum of possible occupant behavior profiles.
Highlights
In order to reduce building energy consumption, many studies explored improvements of the envelope, fenestration, mechanical systems and heat recovery technologies
Would design and decision-making be different if one attempted to include many occupant behavior profiles? This question is important, given that in the design process, one usually does not really know the behavior of the future building users. In line with this challenge, the objective of the present study is to evaluate how the window-to-wall ratio (WWR) of a residential unit affects performance when considering a high number of possible occupant behavior profiles with a Monte Carlo approach
The impact of window-to-wall ratio will first be demonstrated in Section Impact of Window-to-Wall Ratio, before analyzing how each component of the occupant behavior model affects the performance of the building considering different WWR (Section Analysis of OB Factor Affecting Performance)
Summary
In order to reduce building energy consumption, many studies explored improvements of the envelope, fenestration, mechanical systems and heat recovery technologies. Thanks to these efforts to improve building performance, the efficiency of modern equipment and systems tend to get closer and closer to their theoretical physical limits. Nguyen and Aiello (2013) reviewed different intelligent buildings in which the attention was focused on energy saving and user activity recognition. They have concluded that proper occupant-oriented strategies could lead to up to 40% saving in both HVAC and lighting systems.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
