Analysis of the occupants’ behavior related to natural ventilation

Davide Calì, Rune Korsholm Andersen, Tanja Osterhage, Mark Wesseling, Dirk Müller, Bjarne W. Olesen

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The real energy performance of buildings depends both upon deterministic aspects (building'sphysics and engineering systems) and probabilistic aspects such as weather and occupantbehavior. Occupant behavior is usually not directly considered when calculating the expected energy performance of buildings. In fact, field test studies all over the world have shown discrepancies between expectation and real energy performances of buildings. This gap could be bridged, by embedding stochastic occupants’ behavior models within buildings’ energy performances simulation software. Within this work, an established method to analyze the probability of a state change of the windows, based on logistic regression, was applied to monitored data (measured each minute) from two refurbished residential buildings. The weather as well as the five rooms of each of the 60 apartments located in the buildings were monitored in terms of indoor environmental quality and window operation for four years. The aim of this work is the investigation of the drivers leading occupants to open and close windows.The evaluation of the 300 windows showed: the two most common drivers leading to the opening action were the time of the day and the carbon dioxide concentration in the room. The two most common drivers leading to the closing action were: the daily average outdoor temperature, and the time of the day.
Original languageEnglish
Title of host publicationCLIMA 2016 - Proceedings of the 12th REHVA World Congress
EditorsPer Kvols Heiselberg
Number of pages9
Publication date2016
Article number383
ISBN (Print)87-91606-36-5, 87-91606-30-6
Publication statusPublished - 2016
Event12th REHVA World Congress - Aalborg, Denmark
Duration: 22 May 201625 May 2016


Conference12th REHVA World Congress
Internet address


  • Occupant behavior
  • Logistic regression
  • Natural ventilation
  • Buildings’ energy performance
  • Case study

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