eCOMBINE

“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.

Background

  • 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

Methodology

  • 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

Goals

  • 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

 

Results

  • 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

 

Publications