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Probability of occupant operation of windows during transition seasons in office buildings

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  • Li, Nan
  • Li, Juncheng
  • Fan, Ruijuan
  • Jia, Hongyuan

Abstract

Window operation is not only an important method for improving the indoor thermal environment and air quality, but also a significant way to reduce energy consumption of air-conditioned rooms during off-running periods in transition seasons. The occupants' window-operation behavior is influenced by both objective factors, such as thermal comfort and indoor air quality; and objective sensation, such as psychology and physiology, introducing considerable randomness and uncertainty. A two-month field observation of occupant window-opening behaviors for natural ventilation in an office building during the transition seasons was carried out in Chongqing, China. Multi-factor analysis of variance was conducted in data analysis using SPSS statistical software. The results showed that outdoor air temperature significantly affected window opening among other factors such as outdoor relative humidity, indoor air temperature, indoor relative humidity, and indoor CO2 concentration, which have much less effect. The main trigger point for opening windows in the transition seasons is from occupants' desire to improve the indoor thermal and air quality environment. A probability model of occupants' window operation was proposed based on logistic regression analysis. Meanwhile, the Monte Carlo simulation results indicate that during transition seasons (when outdoor temperature varied from 15 to 30 °C), the probability of window opening in office buildings follows a normal distribution and increases linearly along with the outdoor temperature growth.

Suggested Citation

  • Li, Nan & Li, Juncheng & Fan, Ruijuan & Jia, Hongyuan, 2015. "Probability of occupant operation of windows during transition seasons in office buildings," Renewable Energy, Elsevier, vol. 73(C), pages 84-91.
    • Handle: RePEc:eee:renene:v:73:y:2015:i:c:p:84-91
    DOI: 10.1016/j.renene.2014.05.065
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    Citations

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    Cited by:

    1. Hong, Juwon & Kang, Hyuna & Hong, Taehoon, 2020. "Oversampling-based prediction of environmental complaints related to construction projects with imbalanced empirical-data learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    2. Halil Alibaba, 2016. "Determination of Optimum Window to External Wall Ratio for Offices in a Hot and Humid Climate," Sustainability, MDPI, vol. 8(2), pages 1-21, February.
    3. Małgorzata Fedorczak-Cisak & Katarzyna Nowak & Marcin Furtak, 2019. "Analysis of the Effect of Using External Venetian Blinds on the Thermal Comfort of Users of Highly Glazed Office Rooms in a Transition Season of Temperate Climate—Case Study," Energies, MDPI, vol. 13(1), pages 1-18, December.
    4. Reihaneh Aram & Halil Zafer Alibaba, 2019. "Thermal Comfort and Energy Performance of Atrium in Mediterranean Climate," Sustainability, MDPI, vol. 11(4), pages 1-29, February.
    5. Anand, Prashant & Cheong, David & Sekhar, Chandra & Santamouris, Mattheos & Kondepudi, Sekhar, 2019. "Energy saving estimation for plug and lighting load using occupancy analysis," Renewable Energy, Elsevier, vol. 143(C), pages 1143-1161.
    6. Wang, Qinpeng & Augenbroe, Godfried & Kim, Ji-Hyun & Gu, Li, 2016. "Meta-modeling of occupancy variables and analysis of their impact on energy outcomes of office buildings," Applied Energy, Elsevier, vol. 174(C), pages 166-180.
    7. Zhuo Jia & Song Pan & Haowei Yu & Yiqiao Liu & Shen Wei & Mingyuan Qin & Li Chang & Ying Cui, 2023. "Modeling Occupant Window Behavior in Hospitals—A Case Study in a Maternity Hospital in Beijing, China," Sustainability, MDPI, vol. 15(11), pages 1-29, May.
    8. Jia, Mengda & Srinivasan, Ravi S. & Raheem, Adeeba A., 2017. "From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 525-540.
    9. Rouleau, Jean & Gosselin, Louis, 2020. "Probabilistic window opening model considering occupant behavior diversity: A data-driven case study of Canadian residential buildings," Energy, Elsevier, vol. 195(C).

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