TY - GEN
T1 - Exploring agent-based modeling for human-centered energy consumption prediction
AU - Abraham, Yewande S.
AU - Zhao, Zhidan
AU - Anumba, Chimay J.
AU - Asadi, Somayeh
N1 - Funding Information:
The authors acknowledge the support of Qatar National Research Fund (QNRF), a member of Qatar Foundation (Grant No. 6-1370-2-552).
Publisher Copyright:
© 2017 by Canadian Society for Civil Engineering. All rights reserved.
PY - 2017
Y1 - 2017
N2 - People interact with buildings to make the indoor environment more comfortable thereby impacting energy consumption. However, these occupants' energy-related actions in buildings are not well accounted for using traditional simulation programs and normally are represented in a simplistic manner. Agent-based modeling (ABM) is widely used to predict real world situations and this approach has been used to model human behavior in different contexts. ABM has also been used in relation to energy consumption prediction. This study explores how ABM can be used to better model not only human behavior but also look into how occupant values (for instance thermal comfort, visual comfort, indoor air quality, perceived health and personal productivity) and indoor environmental preferences can be maintained while ensuring energy savings. The human behavior considered in this paper include occupants adjusting layers of clothing, using portable heating and cooling devices, adjusting thermostats, adjusting lighting levels, and using shading devices. Following a review of the available literature, the authors highlight the gaps and present recommendations to better address occupant preferences and behavior.
AB - People interact with buildings to make the indoor environment more comfortable thereby impacting energy consumption. However, these occupants' energy-related actions in buildings are not well accounted for using traditional simulation programs and normally are represented in a simplistic manner. Agent-based modeling (ABM) is widely used to predict real world situations and this approach has been used to model human behavior in different contexts. ABM has also been used in relation to energy consumption prediction. This study explores how ABM can be used to better model not only human behavior but also look into how occupant values (for instance thermal comfort, visual comfort, indoor air quality, perceived health and personal productivity) and indoor environmental preferences can be maintained while ensuring energy savings. The human behavior considered in this paper include occupants adjusting layers of clothing, using portable heating and cooling devices, adjusting thermostats, adjusting lighting levels, and using shading devices. Following a review of the available literature, the authors highlight the gaps and present recommendations to better address occupant preferences and behavior.
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M3 - Conference contribution
AN - SCOPUS:85065080306
SN - 9781510878419
T3 - 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017
SP - 660
EP - 669
BT - 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017
PB - Canadian Society for Civil Engineering
T2 - 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017
Y2 - 31 May 2017 through 3 June 2017
ER -
