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Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis

Author

Listed:
  • Sun-Hye Mun

    (Green Building Research Center, Department of Living and Built Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang-Si, Gyeonggi-Do 10223, Korea)

  • Younghoon Kwak

    (Department of Architecture, University of Seoul, Seoul 02504, Korea)

  • Jung-Ho Huh

    (Department of Architecture, University of Seoul, Seoul 02504, Korea)

Abstract

The behavior of building occupants has been studied by researchers for building control as well as for predicting energy use. In this study, we analyzed the effect of the application of single and complex behavior models on the simulation results of residential buildings. Two occupant behaviors—window opening and closing and air conditioner (AC) usage—were simulated, which are known to be interconnected. This study had two purposes: The first was to integrate data analysis tools (R in this study) and building simulation tools (EnergyPlus in this study) so that two behaviors with interconnectivity could be reflected in building simulation analysis. The second purpose was to apply the behavior models in residential buildings to an integrated simulation environment in stages to analyze their relative influence on the building energy and indoor environment. The results of the study prove that the application of complex behavior is important for research regarding the prediction of actual energy consumption. The results help identify the gap between reality and the existing simulation methods; thereby, they can help improve methods related to energy consumption analysis. We hope that this study and its results will serve as a guide for researchers looking to study occupants’ behavior in the future.

Suggested Citation

  • Sun-Hye Mun & Younghoon Kwak & Jung-Ho Huh, 2021. "Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:3:p:1243-:d:486607
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    References listed on IDEAS

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    1. Pisello, Anna Laura & Asdrubali, Francesco, 2014. "Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies," Applied Energy, Elsevier, vol. 133(C), pages 224-235.
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    3. Cellura, Maurizio & Guarino, Francesco & Longo, Sonia & Mistretta, Marina, 2017. "Modeling the energy and environmental life cycle of buildings: A co-simulation approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 733-742.
    4. Ma, Jun & Cheng, Jack C.P., 2016. "Identifying the influential features on the regional energy use intensity of residential buildings based on Random Forests," Applied Energy, Elsevier, vol. 183(C), pages 193-201.
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