“Interaction between energy use, COMfort, Behaviour, and INdoor Environment in Office Buildings”


Project Description

The project aims at overcoming uncertainties in predicting energy consumption of HVAC (Heating, Ventilation and Air-Conditioning) and lighting services in open plan offices by developing an integrated approach to study the cause-effect relationship between occupants and combined in-door environmental factors (thermal, visual, air quality and

 noise). The impulse behind dynamic and multivariable behaviour of occupants are identified through the field study with the implementation of point-in-time mobile questionnaires coupled with multi-dimensional (indoor and out-door) environmental measurements. Building occupants, whenever they perform a certain (dis)comfort-related action

 (e.g. window opening or closing), are asked to indicate the motivation behind the control behaviour on our developed mobile application OBdrive. This holistic approach allows to gain a more comprehensive understanding of occupant behaviour towards bridging the gap between real and predicted energy use in office buildings.


  • Occupant behaviour is one of the key factors of uncertainty when predicting energy use in Building Energy Simulation Tools (BEST)
  • A more holistic understanding of the human-building interaction is needed to overcome the energy performance gap


  • Point-in-time surveying on behaviours (windows, blinds, lights)
  • Long-term surveying (individual characteristics/preferences, group dynamics)
  • Global comfort evaluation through field measurements and subjective responses


  • Gain insights on the multivariable-driven human-building interaction in open plan offices (Fig. 1)
  • Development of an integrated approach to explore the dynamic cause-effect relationships between occupants, combined environmental factors, and energy use
Conceptual illustration: Multi-variable-driven stimuli



  • Exploration of an extensive set of drivers at work including individual characteristics and preferred adaptive opportunities
  • Investigation of group behaviours
  • Development of a comprehensive and multidimensional OB model for implementation in building energy simulation
Mobile app OBdrive: Investigation of drivers behind actions