Stochastic Simulation of Occupant Presence and Behaviour in Buildings

While most current building simulation tools consider occupants as predictable robots the true nature of human behaviour is more complex. This article describes a set of stochastic models aimed at capturing this complexity by decoupling occupant presence from occupant behaviour, then considering separately each means of occupant interaction (use of appliances, of windows, of lighting, etc.) with the building and finally modeling each of these appropriately. The model of occupant presence is unique in that it generates time series that have proven themselves to be realistic at both hourly and daily time scales. That of window opening assigns personal levels of tolerance to each occupant who thereafter reacts to indoor stimuli. The appliance model attributes devices to a zone, then reproduces the typical use of these by the occupants present, thereby generating a realistic variety in values of energy consumption and peak loads.

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

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

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

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

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

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

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

[8]  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 .

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

[10]  Francis Rubinstein,et al.  Modeling occupancy in single person offices , 2005 .

[11]  Y. Yamaguchi,et al.  DEVELOPMENT OF DISTRICT ENERGY SYSTEM SIMULATION MODEL BASED ON DETAILED ENERGY DEMAND MODEL , 2003 .

[12]  A. Hwang [Thermal comfort]. , 1990, Taehan kanho. The Korean nurse.

[13]  Aya Hagishima,et al.  State transition probability for the Markov Model dealing with on/off cooling schedule in dwellings , 2005 .

[14]  David E. Claridge,et al.  Compilation of Diversity Factors and Schedules for Energy and Cooling Load Calculations, ASHRAE Research Project 1093-RP, Final Report , 1999 .

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

[16]  K Kabele,et al.  INTEGRATED RESOURCE FLOW MODELLING OF URBAN NEIGHBOURHOODS : PROJECT SUNTOOL , 2003 .