A Study on the Impact of Household Occupants’ Behavior on Energy Consumption Using an Integrated Computer Model

In this paper, several models are integrated into a thermal model to study the impact of occupants’ behaviors on the building energy consumption. An air flow model is developed to simulate ventilation related to the occupant’s patterns of window opening and closing. An electric consumption model is developed to simulate the usage pattern and the electricity input to household electric appliances. The thermostat setpoint temperature and window shading schemes are varied with different occupants’ behavior norms and are included in the model. The simulation was applied to a typical household located in the city of Oshawa in Ontario, Canada. The results show that the window opening has the greatest impact on the energy consumption during the heating season, and the shading scheme has the greatest impact on the A/C energy consumption during the cooling season. The electricity consumption of the A/C can be significantly reduced by appropriately applying the shading and opening schemes and resetting the thermostat setpoint temperature to a slightly higher degree. Keeping the windows closed and allowing the solar radiation to be transmitted through the window in winter help reduce the energy usage to heat the house.

[1]  Yiwen Jian,et al.  Case study of window opening behavior using field measurement results , 2011 .

[2]  Vice President,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATION AND AIR CONDITIONING ENGINEERS INC. , 2007 .

[3]  Jukka Paatero,et al.  A model for generating household electricity load profiles , 2006 .

[4]  Jerald D. Parker,et al.  Heating, Ventilating, and Air Conditioning: Analysis and Design , 1977 .

[5]  Christoph F. Reinhart,et al.  Lightswitch-2002: a model for manual and automated control of electric lighting and blinds , 2004 .

[6]  G. Iwashita,et al.  The effects of human behavior on natural ventilation rate and indoor air environment in summer − a field study in southern Japan , 1997 .

[7]  Edyta Dudkiewicz,et al.  Inherent variability of heat consumption in residential buildings , 2009 .

[8]  Jeffrey D. Spitler,et al.  Cooling and heating load calculation manual , 1992 .

[9]  Jacek Tejchman,et al.  Comparison of physical performances of the ventilation systems in low-energy residential houses , 2009 .

[10]  Ian Beausoleil-Morrison,et al.  A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices , 2013 .

[11]  Madhavi Indraganti,et al.  Adaptive use of natural ventilation for thermal comfort in Indian apartments , 2010 .

[12]  Christoph F. Reinhart,et al.  Adding advanced behavioural models in whole building energy simulation: A study on the total energy impact of manual and automated lighting control , 2006 .

[13]  Mohamed B. Gadi,et al.  A comparison between CFD and Network models for predicting wind-driven ventilation in buildings , 2007 .

[14]  Joseph Andrew Clarke,et al.  Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings , 2007 .

[15]  Omar Khattab,et al.  Occupants’ behavior and activity patterns influencing the energy consumption in the Kuwaiti residences , 2003 .

[16]  K. K. Andersen,et al.  Survey of occupant behaviour and control of indoor environment in Danish dwellings , 2007 .

[17]  Claude Brezinski,et al.  Numerical recipes in Fortran (The art of scientific computing) : W.H. Press, S.A. Teukolsky, W.T. Vetterling and B.P. Flannery, Cambridge Univ. Press, Cambridge, 2nd ed., 1992. 963 pp., US$49.95, ISBN 0-521-43064-X.☆ , 1993 .

[18]  Darren Robinson,et al.  A generalised stochastic model for the simulation of occupant presence , 2008 .

[19]  Guy R. Newsham,et al.  Clothing as a thermal comfort moderator and the effect on energy consumption , 1997 .

[20]  Konstantinos Papakostas,et al.  Occupational and energy behaviour patterns in Greek residences , 1997 .

[21]  Ali Malkawi,et al.  Simulating multiple occupant behaviors in buildings: An agent-based modeling approach , 2014 .

[22]  Yaolin Lin,et al.  Three-dimensional thermal and airflow (3D-TAF) model of a dome-covered house in Canada , 2008 .

[23]  A. Emery,et al.  A long term study of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards , 2006 .

[24]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[25]  Aya Hagishima,et al.  A methodology for peak energy requirement considering actual variation of occupants' behavior schedules , 2008 .

[26]  Tianzhen Hong,et al.  An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework , 2015 .

[27]  Y. Shimoda,et al.  Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model , 2007 .

[28]  Sebastian Herkel,et al.  Towards a model of user behaviour regarding the manual control of windows in office buildings , 2008 .