A literature review on driving factors and contextual events influencing occupants' behaviours in buildings

Abstract The present paper illustrates the results of a literature review on occupants' behaviours, assessing the actions' drivers. There is no general agreement about the reasons people interact with building systems or the driving factors that trigger their decisions. Even if lot of researchers focus on this target, they usually analyse one or two actions, while no survey makes a comprehensive investigation. Windows, lights, blinds, air-conditioning, thermostat, fans and doors patterns are investigated in different building uses (offices, houses and schools). The analysis is split in three parts: 1) evaluating the influence of environmental parameters 2) and time-related events (e.g. arrivals and departures) and 3) describing the variables adopted in behavioural models. The results suggest that not only environmental factors play a key role in the use of building systems but also contextual factors, as well as routine and habits, largely affect occupants' behaviours. Behavioural models are becoming more and more complex and comprehensive to better reproduce the human component. Considering the principal driving factors inside the behavioural models would bring a double benefit: improving the results of building simulation programs and assisting designers during the project of energy-saving and comfortable buildings.

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

[2]  Peter Barrett,et al.  Factors influencing occupants’ blind-control behaviour in a naturally ventilated office building , 2012 .

[3]  Tianzhen Hong,et al.  Advances in research and applications of energy-related occupant behavior in buildings ☆ , 2016 .

[4]  Tianzhen Hong,et al.  A simulation approach to estimate energy savings potential of occupant behavior measures , 2017 .

[5]  Jian Yao,et al.  Occupants’ impact on indoor thermal comfort: a co-simulation study on stochastic control of solar shades , 2016 .

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

[7]  Astrid Roetzel,et al.  A review of occupant control on natural ventilation , 2010 .

[8]  M. Shukuya,et al.  Comparison of theoretical and statistical models of air-conditioning-unit usage behaviour in a residential setting under Japanese climatic conditions , 2009 .

[9]  Christoph F. Reinhart,et al.  Monitoring manual control of electric lighting and blinds , 2003 .

[10]  Ravi S. Srinivasan,et al.  From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency , 2017 .

[11]  Rui Neves-Silva,et al.  Stochastic models for building energy prediction based on occupant behavior assessment , 2012 .

[12]  Stefano Paolo Corgnati,et al.  Accounting for the uncertainty related to building occupants with regards to visual comfort: A literature survey on drivers and models , 2016 .

[13]  Kevin Van Den Wymelenberg,et al.  Patterns of occupant interaction with window blinds: A literature review , 2012 .

[14]  H. Burak Gunay,et al.  The contextual factors contributing to occupants' adaptive comfort behaviors in offices – A review and proposed modeling framework , 2014 .

[15]  Hongsan Sun,et al.  An occupant behavior modeling tool for co-simulation , 2016 .

[16]  Arno Schlueter,et al.  Occupant centered lighting control for comfort and energy efficient building operation , 2015 .

[17]  M. Togeby,et al.  Demand for space heating in apartment blocks: measuring effects of policy measures aiming at reducing energy consumption , 2001 .

[18]  Young-Jun Son,et al.  Modeling human operator decision-making in manufacturing systems using BDI agent paradigm , 2005 .

[19]  Willett Kempton,et al.  «I always turn it on super» : user decisions about when and how to operate room air conditioners , 1992 .

[20]  Birgit Müller,et al.  Simple or complicated agent-based models? A complicated issue , 2016, Environ. Model. Softw..

[21]  P. Gurian,et al.  Tracking the human-building interaction: A longitudinal field study of occupant behavior in air-conditioned offices , 2015 .

[22]  Yoshiyuki Shimoda,et al.  Survey On The Occupant Behavior Relating To Window And Air Conditioner Operation In The Residential Buildings , 2013, Building Simulation Conference Proceedings.

[23]  Stefano Paolo Corgnati,et al.  On modelling and simulation of occupant models , 2015 .

[24]  Francesca Stazi,et al.  Indoor air quality and thermal comfort optimization in classrooms developing an automatic system for windows opening and closing , 2017 .

[25]  Valentina Fabi,et al.  Effect of thermostat and window opening occupant behavior models on energy use in homes , 2014 .

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

[27]  Weiming Shen,et al.  Leveraging existing occupancy-related data for optimal control of commercial office buildings: A review , 2017, Adv. Eng. Informatics.

[28]  Gregor P. Henze,et al.  Building occupancy detection through sensor belief networks , 2006 .

[29]  Vítor Leal,et al.  Influence of shading control patterns on the energy assessment of office spaces , 2012 .

[30]  David Infield,et al.  Domestic lighting: A high-resolution energy demand model , 2009 .

[31]  Jeong Tai Kim,et al.  Effects of occupancy and lighting use patterns on lighting energy consumption , 2012 .

[32]  D.R.G. Hunt,et al.  The use of artificial lighting in relation to daylight levels and occupancy , 1979 .

[33]  Darren Robinson,et al.  Adaptive actions on shading devices in response to local visual stimuli , 2010 .

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

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

[36]  Paul Torcellini,et al.  Simulation of Energy Management Systems in EnergyPlus , 2008 .

[37]  Rui Zhang,et al.  An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network , 2010 .

[38]  P. R. Warren,et al.  Window-opening behaviour in office buildings , 1984 .

[39]  L. Wallace,et al.  Continuous measurements of air change rates in an occupied house for 1 year: The effect of temperature, wind, fans, and windows* , 2002, Journal of Exposure Analysis and Environmental Epidemiology.

[40]  Andreas Wagner,et al.  Does the occupant behavior match the energy concept of the building? - Analysis of a German naturally ventilated office building , 2015 .

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

[42]  T. Inoue,et al.  The development of an optimal control system for window shading devices based on investigations in office buildings , 1988 .

[43]  Jae-Weon Jeong,et al.  Occupant behavior regarding the manual control of windows in residential buildings , 2016 .

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

[45]  Nan Li,et al.  Probability of occupant operation of windows during transition seasons in office buildings , 2015 .

[46]  Darren Robinson,et al.  Interactions with window openings by office occupants , 2009 .

[47]  Ian Beausoleil-Morrison,et al.  Development and implementation of an adaptive lighting and blinds control algorithm , 2017 .

[48]  A. Carlsson-kanyama,et al.  Efficient and inefficient aspects of residential energy behaviour: What are the policy instruments for change? , 2006 .

[49]  Zhenghua Chen,et al.  Comparing occupancy models and data mining approaches for regular occupancy prediction in commercial buildings , 2017 .

[50]  Jin Wen,et al.  Quantifying the human–building interaction: Considering the active, adaptive occupant in building performance simulation , 2016 .

[51]  Francesco Asdrubali,et al.  Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies , 2014 .

[52]  Siew Eang Lee,et al.  Review of occupancy sensing systems and occupancy modeling methodologies for the application in institutional buildings , 2016 .

[53]  Darren Robinson,et al.  A comprehensive stochastic model of blind usage: Theory and validation , 2009 .

[54]  Tianzhen Hong,et al.  Occupant behavior modeling for building performance simulation: Current state and future challenges , 2015 .

[55]  Chuang Wang,et al.  A generalized probabilistic formula relating occupant behavior to environmental conditions , 2016 .

[56]  Xuemei Guo,et al.  Compressive classification of human motion using pyroelectric infrared sensors , 2014, Pattern Recognit. Lett..

[57]  Dennis L. Loveday,et al.  Factors affecting ‘end-of-day’ window position in a non-air-conditioned office building , 2013 .

[58]  Dj Carter,et al.  Long-term patterns of use of occupant controlled office lighting , 2003 .

[59]  Anna Laura Pisello,et al.  How peers’ personal attitudes affect indoor microclimate and energy need in an institutional building: Results from a continuous monitoring campaign in summer and winter conditions , 2016 .

[60]  Sanae Chraibi,et al.  Lighting preference profiles of users in an open office environment , 2017 .

[61]  Tianzhen Hong,et al.  Statistical analysis and modeling of occupancy patterns in open-plan offices using measured lighting-switch data , 2013 .

[62]  Stuart Barlow,et al.  Occupant comfort in UK offices—How adaptive comfort theories might influence future low energy office refurbishment strategies , 2007 .

[63]  Giuliano Dall'O',et al.  Comparison between predicted and actual energy performance for summer cooling in high-performance residential buildings in the Lombardy region (Italy) , 2012 .

[64]  Marc Fontoynont,et al.  The use of shading systems in VDU task offices: A pilot study , 2006 .

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

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

[67]  K. Pavlou,et al.  Experimental investigation of the air flow and indoor carbon dioxide concentration in classrooms with intermittent natural ventilation , 2008 .

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

[69]  Clinton J. Andrews,et al.  Designing Buildings for Real Occupants: An Agent-Based Approach , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[70]  Yi Jiang,et al.  Influence of household air-conditioning use modes on the energy performance of residential district cooling systems , 2016 .

[71]  Yixing Chen,et al.  EnergyPlus and CHAMPS-Multizone co-simulation for energy and indoor air quality analysis , 2015 .

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

[73]  Sheikh Tahir Bakhsh,et al.  Indoor positioning in Bluetooth networks using fingerprinting and lateration approach , 2011, 2011 International Conference on Information Science and Applications.

[74]  Emile H. L. Aarts,et al.  Impact of Blinds Usage on Energy Consumption: Automatic Versus Manual Control , 2014, AmI.

[75]  James A. Love.  Manual switching patterns in private offices , 1998 .

[76]  Dirk Müller,et al.  Analysis of occupants' behavior related to the use of windows in German households , 2016 .

[77]  Therese Peffer,et al.  How people use thermostats in homes: A review , 2011, Building and Environment.

[78]  Aris Tsangrassoulis,et al.  Dynamic operation of daylighting and shading systems: A literature review , 2016 .

[79]  Nicolas Morel,et al.  A field investigation of the intermediate light switching by users , 2006 .

[80]  Tom Long,et al.  Determining the frequency of open windows in residences: a pilot study in Durham, North Carolina during varying temperature conditions , 2005, Journal of Exposure Analysis and Environmental Epidemiology.

[81]  Zhenghua Chen,et al.  A fusion framework for occupancy estimation in office buildings based on environmental sensor data , 2016 .

[82]  Xuan Luo,et al.  Performance evaluation of an agent-based occupancy simulation model , 2017 .

[83]  Kristian Fabbri,et al.  Energy performance building evaluation in Mediterranean countries: Comparison between software simulations and operating rating simulation , 2008 .

[84]  Ardeshir Mahdavi,et al.  An inquiry into the reliability of window operation models in building performance simulation , 2016 .

[85]  Tianzhen Hong,et al.  Ten questions concerning occupant behavior in buildings: The big picture , 2017 .

[86]  Halina Koczyk,et al.  „IEA EBC Annex 66: definition and simulation of occupant behavior in buildings” – aktualne metody modelowania zachowania użytkowników budynku , 2015 .

[87]  Lin Fu,et al.  Field investigation on consumer behavior and hydraulic performance of a district heating system in Tianjin, China , 2009 .

[88]  Da Yan,et al.  Quantitative description and simulation of human behavior in residential buildings , 2012 .

[89]  Li Shao,et al.  Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning , 2017 .

[90]  Andreas K. Athienitis,et al.  Manually-operated window shade patterns in office buildings: A critical review , 2013 .

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

[92]  Henk Visscher,et al.  Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications , 2013 .

[93]  Françoise Thellier,et al.  Impact of occupant's actions on energy building performance and thermal sensation , 2014 .

[94]  Steve Greenberg,et al.  Window operation and impacts on building energy consumption , 2015 .

[95]  Tianzhen Hong,et al.  An ontology to represent energy-related occupant behavior in buildings. Part II: Implementation of the DNAS framework using an XML schema , 2015 .

[96]  P Pieter-Jan Hoes,et al.  Occupant behavior in building energy simulation: towards a fit-for-purpose modeling strategy , 2016 .

[97]  Ardeshir Mahdavi,et al.  Predicting people's presence in buildings: An empirically based model performance analysis , 2015 .

[98]  Robert Clear,et al.  Office Worker Response to an Automated Venetian Blind and Electric Lighting System: A Pilot Study , 1998 .

[99]  Anca D. Galasiu,et al.  Occupant preferences and satisfaction with the luminous environment and control systems in daylit offices: a literature review , 2006 .

[100]  Hom B. Rijal,et al.  An algorithm to represent occupant use of windows and fans including situation-specific motivations and constraints , 2011 .

[101]  Ardeshir Mahdavi,et al.  IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings , 2017 .

[102]  Jeong Tai Kim,et al.  A field survey of visual comfort and lighting energy consumption in open plan offices , 2012 .

[103]  G. R. Newsham.  Manual Control of Window Blinds and Electric Lighting: Implications for Comfort and Energy Consumption , 1994 .

[104]  Pieter de Wilde,et al.  The gap between predicted and measured energy performance of buildings: A framework for investigation , 2014 .

[105]  Peter Boyce,et al.  Occupant use of switching and dimming controls in offices , 2006 .

[106]  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 .

[107]  Mark Rylatt,et al.  A simple model of domestic lighting demand , 2004 .

[108]  W. T. Powers.  Behavior, the control of perception , 1973 .

[109]  Hiroshi Yoshino,et al.  Definition of occupant behavior in residential buildings and its application to behavior analysis in case studies , 2015 .

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

[111]  Luis de la Ossa,et al.  Design and simulation of a thermal comfort adaptive system based on fuzzy logic and on-line learning , 2012 .

[112]  Borong Lin,et al.  Investigation of winter indoor thermal environment and heating demand of urban residential buildings in China's hot summer – Cold winter climate region , 2016 .

[113]  Chuang Wang,et al.  Air-conditioning usage conditional probability model for residential buildings , 2014 .

[114]  Tadj Oreszczyn,et al.  Occupant control of passive systems: the use of Venetian blinds , 2001 .

[115]  Tianzhen Hong,et al.  A data-mining approach to discover patterns of window opening and closing behavior in offices , 2014 .

[116]  Belinda L Collins,et al.  Window blinds as a potential energy saver: a case study. Building science series (final). [Effects of building orientation] , 1978 .

[117]  Jian Yao,et al.  Determining the energy performance of manually controlled solar shades: A stochastic model based co-simulation analysis , 2014 .

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

[119]  Chungyoon Chun,et al.  Research on seasonal indoor thermal environment and residents' control behavior of cooling and heating systems in Korea , 2009 .

[120]  Chuang Wang,et al.  Modeling Individual's Light Switching Behavior to Understand Lighting Energy Use of Office Building , 2016 .

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

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

[123]  Bjarne W. Olesen,et al.  Window opening behaviour modelled from measurements in Danish dwellings , 2013 .

[124]  Francesca Stazi,et al.  Modelling window status in school classrooms. Results from a case study in Italy , 2017 .

[125]  D.R.G. Hunt,et al.  Predicting artificial lighting use - a method based upon observed patterns of behaviour , 1980 .

[126]  Yufan Zhang,et al.  Factors influencing the occupants’ window opening behaviour in a naturally ventilated office building , 2012 .

[127]  Vorpat Inkarojrit,et al.  Balancing comfort: occupants' control of window blinds in private offices , 2005 .

[128]  Ardeshir Mahdavi,et al.  Prediction of plug loads in office buildings: Simplified and probabilistic methods , 2016 .

[129]  F. Nicol,et al.  Using field measurements of desktop illuminance in european offices to investigate its dependence on outdoor conditions and its effect on occupant satisfaction, and the use of lights and blinds , 2006 .

[130]  M S. Rea,et al.  Window blind occlusion: a pilot study , 1984 .

[131]  Ewa Wäckelgård,et al.  A combined Markov-chain and bottom-up approach to modelling of domestic lighting demand , 2009 .

[132]  Thierry S. Nouidui,et al.  Functional Mock-up Unit Import In Energyplus For Co-simulation , 2013, Building Simulation Conference Proceedings.

[133]  Tianzhen Hong,et al.  Introduction to an occupant behavior motivation survey framework , 2016 .

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

[135]  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 .

[136]  Mark S. Rea,et al.  Occupant Use of Manual Lighting Controls in Private Offices , 1999 .

[137]  Darren Robinson,et al.  Verification of stochastic models of window opening behaviour for residential buildings , 2012 .

[138]  Tianzhen Hong,et al.  Occupancy schedules learning process through a data mining framework , 2015 .

[139]  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 .

[140]  P. O. Fanger,et al.  Thermal comfort: analysis and applications in environmental engineering, , 1972 .

[141]  Athanasios Tzempelikos.  The impact of manual light switching on lighting energy consumption for a typical office building , 2010 .

[142]  Rune Vinther Andersen,et al.  Window opening behaviour: simulations of occupant behaviour in residential buildings using models based on a field survey , 2012 .

[143]  Bjarne W. Olesen,et al.  Occupants' window opening behaviour: A literature review of factors influencing occupant behaviour and models , 2012 .

[144]  Dino Bouchlaghem,et al.  Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap , 2012 .

[145]  Vítor Leal,et al.  Occupants interaction with electric lighting and shading systems in real single-occupied offices: Results from a monitoring campaign , 2013 .

[146]  Yi Jiang,et al.  A novel approach for building occupancy simulation , 2011 .

[147]  Tianzhen Hong,et al.  Simulation of occupancy in buildings , 2015 .

[148]  Jin Wen,et al.  Simulating the human-building interaction: Development and validation of an agent-based model of office occupant behaviors , 2015 .