1. Definition and Simulation of Occupant Behavior in Buildings Da Yan Tsinghua University, China Tianzhen Hong Lawrence Berkeley Lab, USA Nov 14, 2013 Dublin, Ireland

2. Page 2 Background Large gaps between field data and simulation result Source: NBI report 2008 Energy Performance of LEED For New Construction Buildings

3. Page 3 Background building energy is not only affected by climate and system Ref.: SBI/Aalborg University Energy Use in Danish Single Family Houses – By year of construction

4. Page 4 Background Courtesy: Danny Parker, FSEC

5. Page 5 Background OB has significant influence on building energy use The statistics energy consumption of cooling system in different apartments of one residential building in Beijing,2006 Significant discrepancy between each apartment

6. Page 6 Occupant behavior is a key factor

7. Page 7 Importance and Urgency OB is a Key factor for design optimization, energy diagnosis and performance evaluation, and also building energy simulation Limited understanding or inadequate over-simplification on OB; In-depth quantitative analysis urgently needed; Over 20 groups all over the world studying OB individually Lack of consensus in common language, in good experimental design, and in modeling methodologies. An international cooperation is extremely important for both knowledge gaining and data sharing

8. Page 8 Importance and Urgency Simulated Result Measured Data ? OCCUPANT BEHAVIOR Building Energy Use estimation Building Technology evaluation

9. Page 9 Challenges Focus on how OB physically and quantitatively affect on building performance

10. Page 10 Challenges Stochastic and uncertainty Family A Family B Turn off 8 ： 00 Turn on 0 ： 00 ON OFF

11. Page 11 Challenges Diversity of OB Other responses include: complain, contact facilities department, keep blankets and sweaters within reach, and open windows. IFMA 2009 HVAC Survey of IFMA members in US and Canada with 452 responses from 3357 samples

12. Page 12 Challenges Complexity of OB

13. Page 13 Challenges Typical OB Category and Distribution X 10 X 7 X 9 X 12 X 6

14. Page 14 Research Target Identify quantitative definition, description and classification of OB Develop effective simulation methodologies of OB Integrated OB models with building energy simulation tools Demonstrate the OB models in design, evaluation, operation management and policy making by case studies

15. Page 15 Research Target Develop a scientific framework for OB quantitative definition and simulation methodologies

16. Page 16 Research Target Description Questionnaire Interview Measurement Measured action data & environmental parameters Validation Statistical comparison, frequency, times, mean value Model Simulate action data Real Actions

17. Page 17 Research Target Set up Common Description and Definition for OB Common Description & Definition Design Research Policy Labelling Representation Data CollectionModelling

18. Page 18 Technical Approach Targeting Building types: Residential buildings & Office buildings Occupant movement and presence Action Model in residential buildings Action Model in commercial buildings Integration of OB model with simulation tools Demonstration of the applications of OB models Sub-Task A Sub-Task BSub-Task C Sub-Task D Sub-Task E Fundamental Research Practical Application

19. Page 19 ST-A ST-A Personnel presence and movement model Occupant’s presence and movement is strongly connected with Space, Time and Events Personal Presence & Movement

20. Page 20 ST-A ST-A Personnel presence and movement model Building level – # of occupants Q: How many occupants are there in a building at a time? Space level – occupied status Q: whether or not a space (room) is occupied? Space level – # of occupants Q: How many occupants are there in a space at a time? Occupant level - individual tracking Q: In which space an occupant is at a particular time? A set of coherent personnel presence models are demanded for different application purposes

21. Page 21 ST-B ST-B Action model in residential buildings Occupant’s actions are influenced by environmental and physical parameters in a stochastic way

22. Page 22 ST-B ST-B Action model in residential buildings Action Model Object State OB Characteristic Parameter Object State Change State based  Action Based Action based models has more advantage to exhibit the relationship between OB phenomenon and physical driven force

23. Page 23 ST-C ST-C Action model in commercial buildings Higher possibility of interaction and negotiation among occupants in commercial buildings

24. Page 24 ST-C ST-C Action model in commercial buildings Occupants Operation Manager Assignment of the Control Authority between Occupants and Operation Managers affects performance significantly Centralized Control Decentralized Control

25. Page 25 ST-D ST-D Integration with simulation software OB XML schema Software module EnergyPlusDeST Designbuilder ESP-rTRNSYS DOE-2 …… BEM Porgrams Tools to be developed Integration Essential to integrate the OB models with BEMs to exhibit the influence of OB on building energy and performance

26. Page 26 ST-D ST-D Integration with simulation software Develop flexible, sustainable, robust module for simulation

27. Page 27 ST-E ST-E Applications of OB models To exhibit OB’s influence on comfort, environment, energy usage and technology adaptability, improve applications by case studies & guidelines

28. Page 28 Outcomes & Audience OutcomesTarget Audience A Standard definition, description and classification of occupant behaviour in building Building Energy Researchers Energy Modellers Simulation Software Developers B Systematic measurement approach, simulation modelling and validation methodology C Occupant Behavior Database with data of different temporal and spatial resolution D Software to simulate OB, integrated with a building thermal and energy model Building Designers Energy Saving Evaluators HVAC Engineers System Operators Energy Policy Makers E Case studies and guidelines to demonstrate applications of the new OB definitions and models

29. Page 29 International Workshop for New ANNEX August 23 rd, 2013 at IEA HQ in Paris 24 participants from 13 countries One day’s presentation and discussion about the scope of work, technical approach and next steps

30. Page 30 Forum in ISHVAC 2013 Oct 21st, 2013 Xi’an, China Half day with 10 presentations 40 participants from 6 countries

31. Page 31 Participants 24 Countries and Regions AustraliaAustriaBelgiumBrazilCanadaChina DenmarkFinlandFranceGermanyHongKongHungary ItalyJapanKoreaNetherlandNorwayPoland SpainSwedenSwissUKUSASingapore

32. Page 32 Participants 24 Nations or Regions, 57 institutions 73 participants, plus 14 participants want to be kept informed University, research institute, software company, design consultant company, operation manager, system control company ASHRAE has confirmed to join this project, CIBSE is considering participation

33. Page 33 TRA (10 countries) Technology 1: Methods to describe and model occupant behavior in buildings (TRL 3) Technology 2: Integration of the definition and models of occupant behavior with current building energy modelling programs (TRL 2) Technology 3: Application of the definition and models of occupant behavior in residential and commercial buildings to improve design, operation, and retrofit of buildings (TRL 3)

34. Page 34 WORK PLAN Preparation phase –Half a year (2013.11 — 2014.6) Working phase –Two and a half years (2014.7 — 2016.12) Reporting phase –Half a year (2017.1 — 2017.6) 2013.11 2014.6 2015.6 2016.12 2017.6 Preparation phase Working phase Reporting phase

35. Page 35 Summary OB has great influence on building energy usage and also technology evaluation There are still lack of quantitative methods and common language for OB description and simulation This proposal is focused on setting up a scientific framework for OB definition, description, simulation and applications

36. Page 36 Thank you for your attention!