1. THERMAL INERTIA FOR SMALL SCALE RESIDENTIAL BUILDING STIJN VERBEKE UNIVERSITY OF ANTWERP UNIVERSITY COLLEGE stijn.verbeke@ua.ac.be BAUSIM 2010 CONFERENCE – Vienna University of Technology Phd Student, University of Antwerp, Belgium

2. // PROBLEM DESCRIPTION // 1 Reduce summer overheating + + Store heat gains Fast reaction + + Benefits night setback

3. // PROBLEM DESCRIPTION // 2 What is the effect of building thermal inertia in houses in Belgian climatic conditions? ?

4. // METHODS // Whole Building Simulation // 3  Conduction finite difference alghoritm  Annual simulation  Time step = 3 minutes  Weather data : IWEC Brussels Energy Plus

5. // METHODS // Model Geometry // 4

6. 5  Building thermal Mass  Orientation  Glazed surface  Level of thermal insulation: K70/K45/K35/K25 Design Variants:

7. // METHODS // Occupant behaviour // 6 deterministic  Unpredictable behaviour  Various activities  User interference

8. // METHODS // Occupant behaviour // 6 stochastic deterministic

9. // METHODS // Occupant behaviour // 7  Presence in the rooms  Artificial lighting  Electrical appliances  Heating Setpoint  Ventilation Detailed stochastic occupancy model describing:

10. // METHODS // workflow // 8 °C / kWh GEOMETRY MATERIALS HVAC  PRESENCE  INTERNAL HEAT GAIN  THERMOSTAT  WINDOW OPEN? SCHEDULES CLIMATE DATA EVALUATION THERMAL COMFORT MATLAB MATLAB SCRIPT ADJUSTS SCHEDULE FILE

11. // METHODS // discomfort indicator // 9 PPD/PMV (Fanger) Adaptive comfort models ? Custom discomfort indicator = Room thermostat: operative temperature control +

12. // RESULTS // 10 K20K35K45K70

13. // RESULTS // 11  Inertia has minor influence Heating energy demand  HW  LWHeating demand on average + 4.5%  Inertia has major influence Thermal Discomfort  HW  LWDiscomfort on average + 20.4% HW  MWHeating demand on average + 1% HW  MWDiscomfort on average + 2%

14. 10 // RESULTS // DETAILED USER BEHAVIOUR DETERMINISTIC USER BEHAVIOUR (no window opening)

15. 10 // RESULTS // DETAILED USER BEHAVIOUR With sun shading

16. // RESULTS // Influence of occupancy model // 14 DETAILED STOCHASTIC DETERMINISTICCONSTANT ENERGY +5%+1% DISCOMFORT +20%+43%+21% HW  LWHW  MW +1%+0%+1% +2%+10%+19%

17. // CONCLUSIONS //

18. 16  More detailed model of occupant behaviour may leed to different design decisions  Impact of thermal inertia: Heating demand: minor influence Thermal comfort: important influence  Insulations, glazed surface and orientation more important than building thermal mass Preferably at least some thermal mass