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A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings

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  • Hamed Nabizadeh Rafsanjani

    (The Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, 113 NH, Lincoln, NE 68588-0500, USA)

  • Changbum R. Ahn

    (The Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, 113 NH, Lincoln, NE 68588-0500, USA)

  • Mahmoud Alahmad

    (The Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, 113 NH, Lincoln, NE 68588-0500, USA)

Abstract

Buildings currently account for 30–40 percent of total global energy consumption. In particular, commercial buildings are responsible for about 12 percent of global energy use and 21 percent of the United States’ energy use, and the energy demand of this sector continues to grow faster than other sectors. This increasing rate therefore raises a critical concern about improving the energy performance of commercial buildings. Recently, researchers have investigated ways in which understanding and improving occupants’ energy-consuming behaviors could function as a cost-effective approach to decreasing commercial buildings’ energy demands. The objective of this paper is to present a detailed, up-to-date review of various algorithms, models, and techniques employed in the pursuit of understanding and improving occupants’ energy-use behaviors in commercial buildings. Previous related studies are introduced and three main approaches are identified: (1) monitoring occupant-specific energy consumption; (2) Simulating occupant energy consumption behavior; and (3) improving occupant energy consumption behavior. The first approach employs intrusive and non-intrusive load-monitoring techniques to estimate the energy use of individual occupants. The second approach models diverse characteristics related to occupants’ energy-consuming behaviors in order to assess and predict such characteristics’ impacts on the energy performance of commercial buildings; this approach mostly utilizes agent-based modeling techniques to simulate actions and interactions between occupants and their built environment. The third approach employs occupancy-focused interventions to change occupants’ energy-use characteristics. Based on the detailed review of each approach, critical issues and current gaps in knowledge in the existing literature are discussed, and directions for future research opportunities in this field are provided.

Suggested Citation

  • Hamed Nabizadeh Rafsanjani & Changbum R. Ahn & Mahmoud Alahmad, 2015. "A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings," Energies, MDPI, vol. 8(10), pages 1-34, October.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:10996-11029:d:56711
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    5. Ghahramani, Ali & Castro, Guillermo & Karvigh, Simin Ahmadi & Becerik-Gerber, Burcin, 2018. "Towards unsupervised learning of thermal comfort using infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 41-49.
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    7. Ahmed, Omar & Sezer, Nurettin & Ouf, Mohamed & Wang, Liangzhu (Leon) & Hassan, Ibrahim Galal, 2023. "State-of-the-art review of occupant behavior modeling and implementation in building performance simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    8. Shimoda, Yoshiyuki & Yamaguchi, Yohei & Iwafune, Yumiko & Hidaka, Kazuyoshi & Meier, Alan & Yagita, Yoshie & Kawamoto, Hisaki & Nishikiori, Soichi, 2020. "Energy demand science for a decarbonized society in the context of the residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    9. Ghahramani, Ali & Pantelic, Jovan & Lindberg, Casey & Mehl, Matthias & Srinivasan, Karthik & Gilligan, Brian & Arens, Edward, 2018. "Learning occupants’ workplace interactions from wearable and stationary ambient sensing systems," Applied Energy, Elsevier, vol. 230(C), pages 42-51.
    10. Rafsanjani, Hamed Nabizadeh & Ghahramani, Ali & Nabizadeh, Amir Hossein, 2020. "iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings," Applied Energy, Elsevier, vol. 266(C).

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