Abstract
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.
| Original language | English (US) |
|---|---|
| Pages | 660-669 |
| Number of pages | 10 |
| State | Published - Jan 1 2017 |
| Event | 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017 - Vancouver, Canada Duration: May 31 2017 → Jun 3 2017 |
Conference
| Conference | 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017 |
|---|---|
| Country | Canada |
| City | Vancouver |
| Period | 5/31/17 → 6/3/17 |
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All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
Cite this
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Exploring agent-based modeling for human-centered energy consumption prediction. / Abraham, Yewande S.; Zhao, Zhidan; Anumba, Chimay J.; Asadi, Somayeh.
2017. 660-669 Paper presented at 6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017, Vancouver, Canada.Research output: Contribution to conference › Paper
TY - CONF
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
PY - 2017/1/1
Y1 - 2017/1/1
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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