Interactions with window openings by office occupants

Based on almost seven years of continuous measurements, we have analysed in detail the influence of occupancy patterns, indoor temperature and outdoor climate parameters (temperature, wind speed and direction, relative humidity and rainfall) on window opening and closing behaviour. In this we have also considered the variability of behaviours between individuals. This paper begins by presenting some of the key findings from these analyses. We go on to develop and test several modelling approaches, including logistic probability distributions, Markov chains and continuous-time random processes. Based on detailed statistical analysis and cross-validation of each variant, we propose a hybrid of these techniques which models stochastic usage behaviour in a comprehensive and efficient way. We conclude by describing an algorithm for implementing this model in dynamic building simulation tools.

[1]  J. F. Nicol,et al.  Developing an adaptive control algorithm for Europe , 2002 .

[2]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[3]  W. Hauck,et al.  Wald's Test as Applied to Hypotheses in Logit Analysis , 1977 .

[4]  Joseph Andrew Clarke,et al.  Development of adaptive algorithms for the operation of windows, fans, and doors to predict thermal comfort and energy use in Pakistani buildings , 2008 .

[5]  R. Fritsch,et al.  A stochastic model of user behaviour regarding ventilation , 1990 .

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

[7]  J. F. Nicol,et al.  Thermal comfort: use of controls in naturally ventilated buildings , 2001 .

[8]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[9]  David G. Kleinbaum,et al.  Survival Analysis: A Self-Learning Text , 1997 .

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

[11]  Susan Roaf,et al.  Pioneering new indoor temperature standards: the Pakistan project , 1996 .

[12]  J. B. Dick,et al.  Ventilation Research in Occupied Houses. , 1951 .

[13]  J. F. Nicol,et al.  Climatic variations in comfortable temperatures: the Pakistan projects , 1999 .

[14]  J. F. Nicol,et al.  Development of an adaptive window-opening algorithm to predict the thermal comfort, energy use and overheating in buildings , 2008 .

[15]  G. W. Brundrett,et al.  Ventilation: A behavioural approach , 1977 .

[16]  Gail Brager,et al.  Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55 , 2002 .

[17]  P. Fanger Introduction of the olf and the decipol units to quantify air pollution perceived by humans indoors and outdoors , 1988 .

[18]  J. F. Nicol Characterising occupant behaviour in buildings : towards a stochastic model of occupant use of windows, lights, blinds, heaters and fans , 2001 .

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

[20]  Tom Fawcett,et al.  ROC graphs with instance-varying costs , 2006, Pattern Recognit. Lett..

[21]  A. Dobson An introduction to generalized linear models , 1990 .

[22]  Sebastian Herkel,et al.  A PRELIMINARY MODEL OF USER BEHAVIOUR REGARDING THE MANUAL CONTROL OF WINDOWS IN OFFICE BUILDINGS , 2005 .

[23]  K. Steemers,et al.  Time-dependent occupant behaviour models of window control in summer , 2008 .

[24]  R. Fritsch,et al.  Stochastic model of inhabitant behavior in regard to ventilation , 1991 .

[25]  Andrew Stone,et al.  SUNtool - A new modelling paradigm for simulating and optimising urban sustainability , 2007 .

[26]  J. F. Nicol,et al.  Natural ventilated buildings: Use of controls for changing indoor climate , 1998 .

[27]  Darren Robinson,et al.  Some trends and research needs in energy and comfort prediction , 2006 .

[28]  Darren Robinson,et al.  On the behaviour and adaptation of office occupants , 2008 .

[29]  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 .

[30]  Koen Steemers,et al.  Thermal performance of a naturally ventilated building using a combined algorithm of probabilistic occupant behaviour and deterministic heat and mass balance models , 2009 .