Occupant behavior in building energy simulation: Towards a fit-for-purpose modeling strategy

Clevenger, 2006, The impact of the building occupant on energy modeling simulations Hong, 2012, Occupant behavior: impact on energy use of private offices, Asim IBSPA Asia Conference ASHRAE, Addendum r to ANSI/ASHRAE/IESNA Standard 90. 1–2007 Energy Standard for Buildings Except Low-Rise Residential Buildings (2007). IEA-EBC Annex 66 Zeigler, 2000 Brooks, 1996, Choosing the best model: level of detail, complexity, and model performance, Math. Comput. Modell., 24, 1, 10.1016/0895-7177(96)00103-3 Robinson, 2011, Choosing the right model: conceptual modeling for simulation, 2011 Winter Simulation Conference, 1428 Astrup, 2008, Finding the appropriate level of complexity for a simulation model: an example with a forest growth model, For. Ecol. Manage., 256, 1659, 10.1016/j.foreco.2008.07.016 Pitt, 2002, When a good fit can be Bad, Trends Cogn. Sci., 6, 421, 10.1016/S1364-6613(02)01964-2 Trčka, 2010, Overview of HVAC system simulation, Autom. Constr., 19, 93, 10.1016/j.autcon.2009.11.019 Chwif, 2000, On simulation model complexity, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165), 449, 10.1109/WSC.2000.899751 Djunaedy, 2003, Toward external coupling of building energy and airflow modelling programs, ASHRAE Trans., 771 Ochoa, 2012, State of the art in lighting simulation for building science: a literature review, J. Build. Perform. Simul., 5, 209, 10.1080/19401493.2011.558211 H. Polinder, M. Schweiker, A. Van Der Aa, K. Schakib-Ekbatan, V. Fabi, R. Andersen, et al. Final Report Annex 53—Occupant behavior and modeling (Separate Document Volume II), 2013. Duarte, 2013, Revealing occupancy patterns in an office building through the use of occupancy sensor data, Energy Build., 67, 587, 10.1016/j.enbuild.2013.08.062 Mahdavi, 2015, Predicting people’s presence in buildings: an empirically based model performance analysis, Energy Build., 86, 349, 10.1016/j.enbuild.2014.10.027 Macdonald, 1999, Assessing uncertainty in building simulation, 683 Parys, 2014, Agent-based behavioural models for residential buildings in dynamic building simulation: state-of-the-art and integrated model assembly, IBPSA-FR 2014, 1 Gunay, 2013, A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices, Build. Environ., 70, 31, 10.1016/j.buildenv.2013.07.020 Parys, 2011, Coupling of dynamic building simulation with stochastic modelling of occupant behaviour in offices—a review-based integrated methodology, J. Build. Perform. Simul., 4, 339, 10.1080/19401493.2010.524711 Feng, 2015, Simulation of occupancy in buildings, Energy Build., 87, 348, 10.1016/j.enbuild.2014.11.067 Haldi, 2009, Interactions with window openings by office occupants, Build. Environ., 44, 2378, 10.1016/j.buildenv.2009.03.025 Hunt, 1979, The use of artificial lighting in relation to daylight levels and occupancy, Build. Environ., 14, 21, 10.1016/0360-1323(79)90025-8 Fritsch, 1990, A stochastic model of user behaviour regarding ventilation, Build. Environ., 25, 173, 10.1016/0360-1323(90)90030-U Capasso, 1994, Bottom-up approach to residential load modeling, IEEE Trans. Power Syst., 9, 957, 10.1109/59.317650 Newsham, 1995, Lightswitch: a stochastic model for predicting office lighting energy consumption, 59 Degelman, 1999, A model for simulation of daylighting and occupancy sensors as an energy control strategy for office buildings, 571 Nicol, 2001, Characterising occupant behavior in buildings: towards a stochastic model of occupant use of windows, lights, blinds heaters and fans, 1073 Yamaguchi, 2003, Development of district energy system simulation model based on detailed energy demand model, Proceeding of Eighth International IBPSA Conference, 1443 Reinhart, 2004, Lightswitch-2002: A model for manual and automated control of electric lighting and blinds, Sol. Energy, 77, 15, 10.1016/j.solener.2004.04.003 Stokes, 2004, A simple model of domestic lighting demand, Energy Build., 36, 103, 10.1016/j.enbuild.2003.10.007 Pfafferott, 2005, Statistical simulation of user behaviour in low-energy office buildings, International Conference Passive and Low Energy Cooling for the Built Environment, 676 Wang, 2005, Modeling occupancy in single Person offices, Energy Build., 37, 121, 10.1016/j.enbuild.2004.06.015 Bourgeois, 2006, Adding advanced behavioural models in whole building energy simulation: a study on the total energy impact of manual and automated lighting control, Energy Build., 38, 814, 10.1016/j.enbuild.2006.03.002 Zimmermann, 2007, Modeling and simulation of individual user behavior for building performance predictions, 913 Yun, 2008, Time-dependent occupant behaviour models of window control in summer, Build. Environ., 43, 1471, 10.1016/j.buildenv.2007.08.001 Tanimoto, 2008, Validation of probabilistic methodology for generating actual inhabitants’ behavior schedules for accurate prediction of maximum energy requirements, Energy Build., 40, 316, 10.1016/j.enbuild.2007.02.032 Rijal, 2008, Development of an adaptive window-opening algorithm to predict the thermal comfort, energy use and overheating in buildings, J. Build. Perform. Simul., 1, 17, 10.1080/19401490701868448 Page, 2008, A generalised stochastic model for the simulation of occupant presence, Energy Build., 40, 83, 10.1016/j.enbuild.2007.01.018 Haldi, 2008, On the behaviour and adaptation of office occupants, Build. Environ., 43, 2163, 10.1016/j.buildenv.2008.01.003 Herkel, 2008, Towards a model of user behaviour regarding the manual control of windows in office buildings, Build. Environ., 43, 588, 10.1016/j.buildenv.2006.06.031 Richardson, 2008, A high-resolution domestic building occupancy model for energy demand simulations, Energy Build., 40, 1560, 10.1016/j.enbuild.2008.02.006 Tanimoto, 2008, Validation of methodology for utility demand prediction considering actual variations in inhabitant behaviour schedules, J. Build. Perform. Simul., 1, 31, 10.1080/19401490701868471 Widén, 2009, Constructing load profiles for household electricity and hot water from time-use data-Modelling approach and validation, Energy Build., 41, 753, 10.1016/j.enbuild.2009.02.013 Widén, 2009, A combined Markov-chain and bottom-up approach to modelling of domestic lighting demand, Energy Build., 41, 1001, 10.1016/j.enbuild.2009.05.002 Erickson, 2009, Energy efficient building environment control strategies using real-time occupancy measurements, ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, 19, 10.1145/1810279.1810284 Gaceo, 2009, Comparison of standard and case-Based user profiles in building’s energy performance simulation, Eleventh International IBPSA Conference, 584 Armstrong, 2009, Synthetically derived profiles for representing occupant-driven electric loads in Canadian housing, J. Build. Perform. Simul., 2, 15, 10.1080/19401490802706653 Davis, 2010, Occupancy diversity factors for common university building types, Energy Build., 42, 1543, 10.1016/j.enbuild.2010.03.025 Haldi, 2010, Adaptive actions on shading devices in response to local visual stimuli, J. Build. Perform. Simul., 3, 135, 10.1080/19401490903580759 Tabak, 2010, Methods for the prediction of intermediate activities by office occupants, Build. Environ., 45, 1366, 10.1016/j.buildenv.2009.11.018 Widén, 2010, A high-resolution stochastic model of domestic activity patterns and electricity demand, Appl. Energ., 87, 1880, 10.1016/j.apenergy.2009.11.006 Azar, 2010, A conceptual framework to energy estimation in buildings using agent based modeling, Proceedings of the 2010 Winter Simulation Conference, 3145, 10.1109/WSC.2010.5679007 Andrews, 2011, Designing buildings for real occupants: an agent-based approach, IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 41, 1077, 10.1109/TSMCA.2011.2116116 Robinson, 2011, Multi agent simulation of occupants’ presence and behaviour, Proceedings of Building Simulation, 14 Wang, 2011, A novel approach for building occupancy simulation, Build. Simul., 4, 149, 10.1007/s12273-011-0044-5 Yamaguchi, 2012, Comparison of occupant behavior models applied to a household Schweiker, 2012, Verification of stochastic models of window opening behaviour for residential buildings, J. Build. Perform. Simul., 5, 55, 10.1080/19401493.2011.567422 Liao, 2012, Agent-based and graphical modelling of building occupancy, J. Build. Perform. Simul., 5, 5, 10.1080/19401493.2010.531143 Zhang, 2012, Factors influencing the occupants’ window opening behaviour in a naturally ventilated office building, Build. Environ., 50, 125, 10.1016/j.buildenv.2011.10.018 Wilke, 2013, A bottom-up stochastic model to predict building occupants’ time-dependent activities, Build. Environ., 60, 254, 10.1016/j.buildenv.2012.10.021 Andersen, 2013, Window opening behaviour modelled from measurements in Danish dwellings, Build. Environ., 69, 101, 10.1016/j.buildenv.2013.07.005 Chang, 2013, Statistical analysis and modeling of occupancy patterns in open-plan offices using measured lighting-switch data, Build. Simul., 6, 23, 10.1007/s12273-013-0106-y Aerts, 2014, A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison, Build. Environ., 75, 67, 10.1016/j.buildenv.2014.01.021 Lee, 2014, Simulating multiple occupant behaviors in buildings: an agent-based modeling approach, Energy Build., 69, 407, 10.1016/j.enbuild.2013.11.020 Fabi, 2014, Occupants ’ behaviour in office building: stochastic models for window, 8th Windsor Conference: Counting the Cost of Comfort in a Changing World Cumberland Lodge, Windsor, UK, 10–13 April 2014. London : Network for Comfort and Energy Use in Buildings, 10 T. Buso, S.D. Oca, S.P. Corgnati, The influence of realistic schedules for the use of appliances on the total energy performances in dwellings, (2014) 1–18. Chapman, 2014, Coupling multi-agent stochastic simulation of occupants with building simulation Rysanek, 2014, DELORES − an open-source tool for stochastic prediction of occupant services demand, J. Build. Perform. Simul., 37 Gunay, 2014, Coupling stochastic occupant models to building performance simulation using the discrete event system specification formalism, J. Build. Perform. Simul., 7, 1, 10.1080/19401493.2013.866695 D’Oca, 2014, Effect of thermostat and window opening occupant behavior models on energy use in homes, Build. Simul., 7, 683, 10.1007/s12273-014-0191-6 Langevin, 2014, Including occupants in building performance simulation: integration of an agent-based occupant behavior algorithm with Energyplus Alfakara, 2014, Using agent-based modelling to simulate occupants’ behaviours in response to summer overheating Zhou, 2015, Data analysis and stochastic modeling of lighting energy use in large office buildings in China, Energy Build., 86, 275, 10.1016/j.enbuild.2014.09.071 2014 Gunay, 2015, Implementation and comparison of existing occupant behaviour models in EnergyPlus, J. Build. Perform. Simul., 1493, 1, 10.1080/19401493.2015.1102969 Hong, 2015, An ontology to represent energy-related occupant behavior in buildings Part I: Introduction to the DNAs Framework, Build. Environ. Tahmasebi, 2015, Exploring the implications of different occupancy modelling approaches for building performance simulation results, Energy Procedia, 78, 567, 10.1016/j.egypro.2015.11.737 Tahmasebi, 2015, The sensitivity of building performance simulation results to the choice of occupants’ presence models: a case study, J. Build. Perform. Simul., 1493, 1, 10.1080/19401493.2015.1117528 Fanger, 1970 Richardson, 2010, Domestic electricity use: a high-resolution energy demand model, Energy Build., 42, 1878, 10.1016/j.enbuild.2010.05.023 Mahdavi, 2011, People in building performance simulation, 56 Mahdavi, 2015, Common fallacies in representation of occupants in building performance simulation Mahdavi, 2015, The deployment-dependence of occupancy-related models in building performance simulation, Energy Build. Yan, 2015, Occupant behavior modeling for building performance simulation: current state and future challenges, Energy Build., 107, 264, 10.1016/j.enbuild.2015.08.032 Hoes, 2009, User behavior in whole building simulation, Energy Build., 41, 295, 10.1016/j.enbuild.2008.09.008 BPIE, 2011 Correia da Silva, 2013, Occupants interaction with electric lighting and shading systems in real single-occupied offices: results from a monitoring campaign, Build. Environ., 64, 152, 10.1016/j.buildenv.2013.03.015 O’Brien, 2014, The contextual factors contributing to occupants’ adaptive comfort behaviors in offices–A review and proposed modeling framework, Build. Environ., 77, 77, 10.1016/j.buildenv.2014.03.024 U.S. DOE Lin, 2013, On variations of space-heating energy use in office buildings, Appl. Energ., 111, 515, 10.1016/j.apenergy.2013.05.040