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Optimized supply-air temperature (SAT) in variable-air-volume (VAV) systems

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  • Ke, Yu-Pei
  • Mumma, Stanley A.

Abstract

A criterion, based on optimization principles, for determining the SAT setpoint in VAV systems is presented. It is generally accepted that conventional SAT reset controls (SATRC), bounded by either space humidity or ductwork size, will save cooling and/or heating energy. How-ever, the ventilation consequences and penalty resulting from increased fan power have generally been overlooked. Ventilation is impacted since changes in the SAT setpoint change the primary airflow rate and the operation of economizer cycles, i.e. the distribution of fresh outdoor air (OA). These changes may result in extra energy demand and ventilation inefficiency if the reset criterion is not appropriate. This optimization concept simultaneously reduces energy consumption and meets ventilation requirements. Simulation results illustrate that the use of the optimized SATRC saves more energy than a conventional one.

Suggested Citation

  • Ke, Yu-Pei & Mumma, Stanley A., 1997. "Optimized supply-air temperature (SAT) in variable-air-volume (VAV) systems," Energy, Elsevier, vol. 22(6), pages 601-614.
    • Handle: RePEc:eee:energy:v:22:y:1997:i:6:p:601-614
    DOI: 10.1016/S0360-5442(96)00154-5
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    Cited by:

    1. Jing, Gang & Cai, Wenjian & Zhang, Xin & Cui, Can & Yin, Xiaohong & Xian, Huacai, 2019. "An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system," Energy, Elsevier, vol. 172(C), pages 1053-1065.
    2. Okochi, Godwine Swere & Yao, Ye, 2016. "A review of recent developments and technological advancements of variable-air-volume (VAV) air-conditioning systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 784-817.
    3. Kusiak, Andrew & Tang, Fan & Xu, Guanglin, 2011. "Multi-objective optimization of HVAC system with an evolutionary computation algorithm," Energy, Elsevier, vol. 36(5), pages 2440-2449.
    4. Mossolly, M. & Ghali, K. & Ghaddar, N., 2009. "Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm," Energy, Elsevier, vol. 34(1), pages 58-66.
    5. Kusiak, Andrew & Li, Mingyang, 2009. "Optimal decision making in ventilation control," Energy, Elsevier, vol. 34(11), pages 1835-1845.
    6. Javier Diaz-Valdivia & Flávio A. S. Fiorelli, 2023. "Computational Analysis of the Automation Strategies of Temperatures of Supplied Air, Chilled and Condensation Water in Commercial Buildings," Energies, MDPI, vol. 16(8), pages 1-13, April.
    7. Yoon-Bok Seong & Young-Hum Cho, 2016. "Development and Evaluation of Applicable Optimal Terminal Box Control Algorithms for Energy Management Control Systems," Sustainability, MDPI, vol. 8(11), pages 1-22, November.
    8. Yaolin Lin & Wei Yang, 2018. "Comments to Paper Entitled: Development of a Data-Driven Predictive Model of Supply Air Temperature in an Air-Handling Unit for Conserving Energy. Energies 2018, 11 , 407," Energies, MDPI, vol. 11(6), pages 1-2, June.

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