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Achieving natural ventilation potential in practice: Control schemes and levels of automation

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  • Chen, Yujiao
  • Tong, Zheming
  • Wu, Wentao
  • Samuelson, Holly
  • Malkawi, Ali
  • Norford, Leslie

Abstract

A major challenge to fully achieve the natural ventilation (NV) potential in green buildings is the control and coordination of windows and the HVAC system. Three main types of control schemes with increasing levels of automation were examined in this study: spontaneous occupant control driven by thermal comfort, informed occupant manual control that follows instructional signals, and the fully automatic window/HVAC control system governed by either rule-based heuristic control criteria or a computational backend for model predictive control (MPC). Energy saving performance, indoor thermal comfort, and frequency of operation were used as metrics to evaluate various control schemes. We assessed the effectiveness of these control schemes using five representative climates in China that range from hot to severely cold. Our results demonstrated the advantage of fully automatic system, especially integrated with MPC, which showed energy savings of 17–80% with zero discomfort degree hours. In contrast with MPC, the fully automatic system with heuristic control showed 10–66% energy savings and the same discomfort degree hours. Neither the informed nor the spontaneous occupant control cases studied were able to maintain the indoor air temperature within the comfort range at all times. The informed occupant control in particular resulted in thousands of discomfort degree hours in the worst cases. The spontaneous occupant control showed moderate to no energy savings, whereas the informed occupant control introduced excessive energy usage in certain cases. Overall, the fully automatic NV control system exhibited the best energy saving performance and occupant satisfaction among studied control schemes despite of the additional initial investment. It is particularly true in climates where NV control has a considerable impact on building energy performance and employing improper NV control can cause energy waste and excessive thermal discomfort. In the selection of natural ventilation control system, our analysis suggests that developers and building owners should not only consider the initial system investment and maintenance cost, but also take into account the annual energy savings and occupant satisfaction to fully realize natural ventilation potential.

Suggested Citation

  • Chen, Yujiao & Tong, Zheming & Wu, Wentao & Samuelson, Holly & Malkawi, Ali & Norford, Leslie, 2019. "Achieving natural ventilation potential in practice: Control schemes and levels of automation," Applied Energy, Elsevier, vol. 235(C), pages 1141-1152.
    • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:1141-1152
    DOI: 10.1016/j.apenergy.2018.11.016
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    1. Oropeza-Perez, Ivan & Østergaard, Poul Alberg, 2014. "Potential of natural ventilation in temperate countries – A case study of Denmark," Applied Energy, Elsevier, vol. 114(C), pages 520-530.
    2. Cui, Can & Wu, Teresa & Hu, Mengqi & Weir, Jeffery D. & Li, Xiwang, 2016. "Short-term building energy model recommendation system: A meta-learning approach," Applied Energy, Elsevier, vol. 172(C), pages 251-263.
    3. Li, Xiwang & Wen, Jin & Malkawi, Ali, 2016. "An operation optimization and decision framework for a building cluster with distributed energy systems," Applied Energy, Elsevier, vol. 178(C), pages 98-109.
    4. Homod, Raad Z. & Sahari, Khairul Salleh Mohamed & Almurib, Haider A.F., 2014. "Energy saving by integrated control of natural ventilation and HVAC systems using model guide for comparison," Renewable Energy, Elsevier, vol. 71(C), pages 639-650.
    5. Artmann, N. & Manz, H. & Heiselberg, P., 2007. "Climatic potential for passive cooling of buildings by night-time ventilation in Europe," Applied Energy, Elsevier, vol. 84(2), pages 187-201, February.
    6. Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard Barry & Tong, Zheming, 2016. "Energy Saving Potential of Natural Ventilation in China: The Impact of Ambient Air Pollution," Scholarly Articles 27733689, Harvard University Department of Economics.
    7. Peng, Jinqing & Lu, Lin & Yang, Hongxing & Ma, Tao, 2015. "Comparative study of the thermal and power performances of a semi-transparent photovoltaic façade under different ventilation modes," Applied Energy, Elsevier, vol. 138(C), pages 572-583.
    8. Yao, Runming & Liu, Jing & Li, Baizhan, 2010. "Occupants' adaptive responses and perception of thermal environment in naturally conditioned university classrooms," Applied Energy, Elsevier, vol. 87(3), pages 1015-1022, March.
    9. Chen, Xi & Yang, Hongxing & Wang, Yuanhao, 2017. "Parametric study of passive design strategies for high-rise residential buildings in hot and humid climates: miscellaneous impact factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 442-460.
    10. Oropeza-Perez, Ivan & Østergaard, Poul Alberg, 2014. "Energy saving potential of utilizing natural ventilation under warm conditions – A case study of Mexico," Applied Energy, Elsevier, vol. 130(C), pages 20-32.
    11. Tong, Shuiguang & Cheng, Zhewu & Cong, Feiyun & Tong, Zheming & Zhang, Yidong, 2018. "Developing a grid-connected power optimization strategy for the integration of wind power with low-temperature adiabatic compressed air energy storage," Renewable Energy, Elsevier, vol. 125(C), pages 73-86.
    12. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    13. Li, Xiwang & Wen, Jin & Bai, Er-Wei, 2016. "Developing a whole building cooling energy forecasting model for on-line operation optimization using proactive system identification," Applied Energy, Elsevier, vol. 164(C), pages 69-88.
    14. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2016. "Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design," Applied Energy, Elsevier, vol. 182(C), pages 625-633.
    15. Hughes, Ben Richard & Calautit, John Kaiser & Ghani, Saud Abdul, 2012. "The development of commercial wind towers for natural ventilation: A review," Applied Energy, Elsevier, vol. 92(C), pages 606-627.
    16. Hiyama, Kyosuke & Glicksman, Leon, 2015. "Preliminary design method for naturally ventilated buildings using target air change rate and natural ventilation potential maps in the United States," Energy, Elsevier, vol. 89(C), pages 655-666.
    17. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2017. "Estimating natural ventilation potential for high-rise buildings considering boundary layer meteorology," Applied Energy, Elsevier, vol. 193(C), pages 276-286.
    18. Martins, Nuno R. & Carrilho da Graça, Guilherme, 2017. "Impact of outdoor PM2.5 on natural ventilation usability in California’s nondomestic buildings," Applied Energy, Elsevier, vol. 189(C), pages 711-724.
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