IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i11p1151-d82449.html
   My bibliography  Save this article

Development and Evaluation of Applicable Optimal Terminal Box Control Algorithms for Energy Management Control Systems

Author

Listed:
  • Yoon-Bok Seong

    (Senior Research Engineer, Construction & Energy Business Division, Korea Conformity Laboratories, 199, Gasandigital 1-ro, Geumcheon-gu, Seoul 08503, Korea)

  • Young-Hum Cho

    (School of Architecture, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Korea)

Abstract

Common energy management control systems (EMCS) in building HVAC systems could be made much more energy efficient without sacrificing comfort. Most researchers have focused on implementing optimal control algorithms in Variable Air Volume (VAV) systems with EMC functions. Previous studies have paid little attention to using terminal box EMC functions integrated with main AHU (Air Handling Unit) systems. Terminal boxes with EMCS may cause occupant discomfort and waste excessive energy if they do not have the proper operation control functions. The objective of this study is to evaluate the impact of energy consumption and estimate building energy savings on the optimal minimum air flow of single duct VAV terminal boxes and develop applicable optimal terminal box control algorithms for EMCS. This paper presents a dynamic model of a VAV terminal box with hydronic reheat, develops optimal terminal box control algorithms and applies the developed EMCS algorithms to an actual building. The results of this study show that optimal terminal box control algorithms can stably maintain the set room air temperature and reduce energy consumption for varying heating loads compared to conventional control algorithms.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:11:p:1151-:d:82449
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/11/1151/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/8/11/1151/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    3. 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.
    4. 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.
    5. Kusiak, Andrew & Li, Mingyang, 2009. "Optimal decision making in ventilation control," Energy, Elsevier, vol. 34(11), pages 1835-1845.
    6. 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.
    7. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:8:y:2016:i:11:p:1151-:d:82449. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.