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Novel demand-controlled optimization of constant-air-volume mechanical ventilation for indoor air quality, durability and energy saving

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  • Zhang, Sheng
  • Ai, Zhengtao
  • Lin, Zhang

Abstract

Demand-controlled ventilation (DCV) is widely used for the energy-efficient provision of indoor air quality. However, existing DCV requires a continuously variable airflow rate, and is not applicable to the constant-air-volume mechanical ventilation (generally in buildings with room air conditioners and free-running buildings). This study proposes a novel DCV for constant-air-volume mechanical ventilation. To achieve high ventilation efficiency, the proposed DCV operates the constant-air-volume mechanical ventilation continuously and intermittently at full-load/quasi-full-load and partial-load conditions respectively, which is controlled by the upper and lower concentration limits of indoor airborne pollutants (indicated by indoor CO2 concentration). The larger upper and lower concentration limits are preferred for energy saving, but could deteriorate indoor air quality, and cause durability problems due to frequent on-off operations. A genetic algorithm-based optimization is developed to determine the upper and lower concentration limits to maximize energy efficiency while satisfying the demand on indoor air quality and avoiding excessively frequent on-off operations. Case studies verify that the ventilation performance of the proposed DCV optimization is more sensitive to the lower concentration limit than the upper concentration limit. The conventional methods (the continuous ventilation and the intermittent ventilation) for the constant-air-volume mechanical ventilation risk low energy efficiency and deteriorated durability. The proposed DCV optimization improves energy efficiency by up to 88% while meeting demanded indoor air quality and durability.

Suggested Citation

  • Zhang, Sheng & Ai, Zhengtao & Lin, Zhang, 2021. "Novel demand-controlled optimization of constant-air-volume mechanical ventilation for indoor air quality, durability and energy saving," Applied Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:appene:v:293:y:2021:i:c:s0306261921004311
    DOI: 10.1016/j.apenergy.2021.116954
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    Cited by:

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    3. Li, Chunxiao & Cui, Can & Li, Ming, 2023. "A proactive 2-stage indoor CO2-based demand-controlled ventilation method considering control performance and energy efficiency," Applied Energy, Elsevier, vol. 329(C).
    4. Simon Li, 2023. "Review of Engineering Controls for Indoor Air Quality: A Systems Design Perspective," Sustainability, MDPI, vol. 15(19), pages 1-46, September.
    5. Sinha, Anshuman & Thakkar, Harshul & Rezaei, Fateme & Kawajiri, Yoshiaki & Realff, Matthew J., 2022. "Reduced building energy consumption by combined indoor CO2 and H2O composition control," Applied Energy, Elsevier, vol. 322(C).
    6. Su, Wei & Ai, Zhengtao & Liu, Jing & Yang, Bin & Wang, Faming, 2023. "Maintaining an acceptable indoor air quality of spaces by intentional natural ventilation or intermittent mechanical ventilation with minimum energy use," Applied Energy, Elsevier, vol. 348(C).
    7. Pouranian, Fatemeh & Akbari, Habibollah & Hosseinalipour, S.M., 2021. "Performance assessment of solar chimney coupled with earth-to-air heat exchanger: A passive alternative for an indoor swimming pool ventilation in hot-arid climate," Applied Energy, Elsevier, vol. 299(C).
    8. Moghadam, Talie T. & Ochoa Morales, Carlos E. & Lopez Zambrano, Maria J. & Bruton, Ken & O'Sullivan, Dominic T.J., 2023. "Energy efficient ventilation and indoor air quality in the context of COVID-19 - A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).

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