A deep understanding of energy use behavior by occupants in buildings is crucial to the design and operation of buildings to achieve low- or zero-net energy goals. Currently, occupant behavior is under-recognized, compared with the conventional technological solutions, and over-simplified in the design, construction, operation, and retrofit of buildings. Occupant behavior in buildings includes:
- The presence of people in spaces and movement between spaces
- Occupant interactions with building systems
- Occupant adaptations (e.g., changing clothing, having hot/cold drinks).
Occupant actions such as adjusting a thermostat for comfort, switching lights on/off, using appliances, opening/closing windows, pulling window blinds up/down, and moving between spaces can have a significant impact on energy use and occupant comfort in buildings. Depending on the building type, climate, and degree of automation in operation and controls, occupants could increase or decrease energy use by a factor of up to three for residential buildings [Andersen 2012], and increase by up to 80% or reduce by up to 50% for single-occupancy offices [Lin and Hong 2012]. One simulation study [Sun and Hong 2017] also estimated occupant behavior measures have a 41% energy savings potential for office buildings.
Occupant behavior is inherently uncertain and requires an interdisciplinary approach — across the building, social, behavioral, data and computer sciences — to be understood. On one hand, behavior is influenced by external factors such as culture, economy, and climate, as well as internal factors such as individual comfort preference, physiology, and psychology. On the other hand, occupants' interactions with building systems strongly influence building operations and associated energy use and operating costs; in turn, building operations influence occupant behavior, thus forming a closed loop.
Past studies of occupant behavior have lacked in-depth quantitative analysis. Available models of occupant behavior have been developed across different researchers and have shown inconsistencies, lacking consensus on how to approach experimental design and modeling methodologies. A strong need has recently emerged for researchers to work together on devising a consistent research framework for occupant behavior definition and simulation.
Annex 66: Definition and simulation of occupant behavior in buildings [Yan and Hong 2017] is a recently completed international collaborative project that laid the groundwork for this occupant behavior research framework. Annex 66 was co-led by the United States (sponsored by Department of Energy's Building Technologies Office) and China, and included more than 100 researchers from 20 countries working together from November 2013 to May 2018 under the International Energy Agency's (IEA) Energy in Buildings and Communities (EBC) Programme.
Annex 66's research contributions included:
- Identifying quantitative representation and classification of occupant behavior
- Developing methods for occupant behavior measurement, modeling, evaluation, and application
- Implementing occupant behavior models in building performance simulation tools
- Demonstrating applications of occupant behavior models in design, evaluation and operational optimization of buildings through 32 case studies covering various building types across several countries.
The major deliverable from the Annex 66 research is a scientific methodological framework that will guide occupant behavior research in the areas of data collection; model building and evaluation; simulation tool development, integration, and application; and interdisciplinary issues. Outcomes from Annex 66 were presented in four topical issues [Hong 2015, Wagner and Dong 2015, O'Brien et al. 2017, Andrews and Dong 2018], a Springer book [Wagner et al. 2018], and 27 international workshops, seminars and forums.
The outcomes of this research benefit building energy modelers, building designers and engineers, energy software developers, technology vendors, and policymakers. Energy policy makers can use occupant behavior modeling to improve decision-making. The availability of quantitative behavior models can facilitate the development of more effective policies for reducing energy consumption in buildings that leverage knowledge of likely occupant actions and their influence on building performance — for example, by enabling estimation of the energy and occupant comfort consequences of using particular policy levers (e.g., regulation, information campaigns, incentives) and/or supporting the development of new technologies (e.g., occupant-centric sensing and control packages).
The Annex 66 final report, deliverables, and occupant behavior modeling tools are available at annex66.org. Going forward, several ongoing research efforts will continue to tackle some of the open challenges left by Annex 66 and further integrate the human dimensions in the building life cycle to improve performance, including: IEA EBC Annex 79 - Occupant behavior-centric building design and operation, and the ASHRAE Multidisciplinary Task Group on Occupant Behavior in Buildings (MTG.OBB).
Andersen, R. K. (2012). The influence of occupants' behaviour on energy consumption investigated in 290 identical dwellings and in 35 apartments. 10th International Conference on Healthy Buildings, Brisbane, Australia.
Andrews C. and Dong B. (Eds.) (2018). Applications of occupant behavior modeling. A special issue, Building Simulation. Building Simulation. https://link.springer.com/journal/12273/10/6/page/1
Hong T. and Lin H.W. (2012). Occupant behavior: impact on energy use of private offices, ASim:Asian Building Simulation Conference, Shanghai, China.
Hong T. (Ed.) (2015). Advances in Building Energy Modeling and Simulation. A special issue, Energy and Buildings. https://www.sciencedirect.com/journal/energy-and-buildings/special-issue/10K0F4HG0ND?sdc=1
O'Brien W., Mahdavi A. et al. (Eds.) (2017). Fundamentals of occupant behavior research. A special issue, Building Performance Simulation. https://www.tandfonline.com/toc/tbps20/10/5-6?nav=tocList
Sun K. and Hong T. (2017). A simulation approach to estimate energy savings potential of occupant behavior measures, Energy and Buildings, 136:43-62.
Wagner A. and Dong B. (Eds.) (2015). Occupancy behavior in buildings: modeling, simulation, and applications. A special issue, Energy and Buildings. https://www.sciencedirect.com/journal/energy-and-buildings/special-issue/10R14N5DN35?sdc=1
Wagner, A., O'Brien W., Dong B. (Eds.) (2018). Exploring Occupant Behavior in Buildings: Methods and Challenges. Springer, ISBN 978-3-319-61464-9.
Yan D., Hong T., Dong B., et al. (2017). IEA EBC Annex 66: Definition and Simulation of occupant behavior in buildings, Energy and Buildings, 156:258-270.