IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v171y2016icp541-554.html
   My bibliography  Save this article

In-situ implementation and evaluation of an online robust pump speed control strategy for avoiding low delta-T syndrome in complex chilled water systems of high-rise buildings

Author

Listed:
  • Gao, Dian-ce
  • Wang, Shengwei
  • Shan, Kui

Abstract

The low delta-T syndrome is one of the major faults that affect the operation and energy performance of the chilled water systems in practice, particularly for the complex chilled water systems. Low delta-T syndrome refers to the situation where the measured mean temperature difference of the overall terminal air-handling units is much lower than the expected normal value. The conventional pump speed control strategies lack the ability to handle the low delta-T syndrome. This paper presents an online robust control strategy for practical applications to avoid the low delta-T syndrome for chilled water systems including complex systems. On top of the conventional control strategies, a temperature set-point reset scheme is developed aiming at providing the reliable temperature set-point for enhancing the operation reliability of chilled water pumps. In addition, a flow-limiting control scheme is employed to perform the function of actively eliminating the deficit flow in the bypass line by a feedback mechanism. This robust pump speed control strategy has been implemented and evaluated on a real complex chilled water system in a high-rise building. The site test results show that the temperature set-point given by the proposed strategy is reliable and the system temperature difference is significantly raised by eliminating the deficit flow problem. When compared to the conventional control strategies, 78% of the total chilled water pump energy was saved in the test period. The actual pump energy saving percentage could be 39% in a year after implementing the robust control strategy in the studied system.

Suggested Citation

  • Gao, Dian-ce & Wang, Shengwei & Shan, Kui, 2016. "In-situ implementation and evaluation of an online robust pump speed control strategy for avoiding low delta-T syndrome in complex chilled water systems of high-rise buildings," Applied Energy, Elsevier, vol. 171(C), pages 541-554.
  • Handle: RePEc:eee:appene:v:171:y:2016:i:c:p:541-554
    DOI: 10.1016/j.apenergy.2016.03.077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191630397X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2016.03.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
    2. Goyal, Siddharth & Ingley, Herbert A. & Barooah, Prabir, 2013. "Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance," Applied Energy, Elsevier, vol. 106(C), pages 209-221.
    3. Ma, Zhenjun & Wang, Shengwei, 2011. "Enhancing the performance of large primary-secondary chilled water systems by using bypass check valve," Energy, Elsevier, vol. 36(1), pages 268-276.
    4. Lam, Joseph C. & Wan, Kevin K.W. & Cheung, K.L., 2009. "An analysis of climatic influences on chiller plant electricity consumption," Applied Energy, Elsevier, vol. 86(6), pages 933-940, June.
    5. Gao, Dian-ce & Wang, Shengwei & Shan, Kui & Yan, Chengchu, 2016. "A system-level fault detection and diagnosis method for low delta-T syndrome in the complex HVAC systems," Applied Energy, Elsevier, vol. 164(C), pages 1028-1038.
    6. Gao, Dian-ce & Wang, Shengwei & Sun, Yongjun & Xiao, Fu, 2012. "Diagnosis of the low temperature difference syndrome in the chilled water system of a super high-rise building: A case study," Applied Energy, Elsevier, vol. 98(C), pages 597-606.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Mingzhe & Ooka, Ryozo & Choi, Wonjun & Ikeda, Shintaro, 2019. "Experimental and numerical investigation of energy saving potential of centralized and decentralized pumping systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu, 2023. "Globally optimal control of hybrid chilled water plants integrated with small-scale thermal energy storage for energy-efficient operation," Energy, Elsevier, vol. 262(PA).
    3. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2020. "Analysis of operational data from a district cooling system and its connected buildings," Energy, Elsevier, vol. 203(C).
    4. Olszewski, Pawel & Arafeh, Jamal, 2018. "Parametric analysis of pumping station with parallel-configured centrifugal pumps towards self-learning applications," Applied Energy, Elsevier, vol. 231(C), pages 1146-1158.
    5. Sui, Quan & Wei, Fanrong & Zhang, Rui & Lin, Xiangning & Tong, Ning & Wang, Zhixun & Li, Zhengtian, 2019. "Optimal use of electric energy oriented water-electricity combined supply system for the building-integrated-photovoltaics community," Applied Energy, Elsevier, vol. 247(C), pages 549-558.
    6. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Cui, Zhitao & You, Zhiqiang & Ma, Xiaowen, 2023. "Robust enhancement of chiller sequencing control for tolerating sensor measurement uncertainties through controlling small-scale thermal energy storage," Energy, Elsevier, vol. 280(C).
    7. Shunian Qiu & Zhenhai Li & Delong Wang & Zhengwei Li & Yinying Tao, 2022. "Active Optimization of Chilled Water Pump Running Number: Engineering Practice Validation," Sustainability, MDPI, vol. 15(1), pages 1-12, December.
    8. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2022. "District cooling substation design and control to achieve high return temperatures," Energy, Elsevier, vol. 251(C).

    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. Ruparathna, Rajeev & Hewage, Kasun & Sadiq, Rehan, 2016. "Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1032-1045.
    2. Gao, Dian-ce & Wang, Shengwei & Shan, Kui & Yan, Chengchu, 2016. "A system-level fault detection and diagnosis method for low delta-T syndrome in the complex HVAC systems," Applied Energy, Elsevier, vol. 164(C), pages 1028-1038.
    3. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2020. "Analysis of operational data from a district cooling system and its connected buildings," Energy, Elsevier, vol. 203(C).
    4. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2022. "District cooling substation design and control to achieve high return temperatures," Energy, Elsevier, vol. 251(C).
    5. Wang, Wei & Chen, Jiayu & Huang, Gongsheng & Lu, Yujie, 2017. "Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution," Applied Energy, Elsevier, vol. 207(C), pages 305-323.
    6. Baldi, Simone & Yuan, Shuai & Endel, Petr & Holub, Ondrej, 2016. "Dual estimation: Constructing building energy models from data sampled at low rate," Applied Energy, Elsevier, vol. 169(C), pages 81-92.
    7. Wang, Huilong & Xu, Peng & Lu, Xing & Yuan, Dengkuo, 2016. "Methodology of comprehensive building energy performance diagnosis for large commercial buildings at multiple levels," Applied Energy, Elsevier, vol. 169(C), pages 14-27.
    8. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    9. Rachael Sherman & Hariharan Naganathan & Kristen Parrish, 2021. "Energy Savings Results from Small Commercial Building Retrofits in the US," Energies, MDPI, vol. 14(19), pages 1-16, September.
    10. Ju-wan Ha & Yu-jin Kim & Kyung-soon Park & Young-hak Song, 2022. "Energy Saving Evaluation with Low Liquid to Gas Ratio Operation in HVAC&R System," Energies, MDPI, vol. 15(19), pages 1-29, October.
    11. Fan, Cheng & Sun, Yongjun & Zhao, Yang & Song, Mengjie & Wang, Jiayuan, 2019. "Deep learning-based feature engineering methods for improved building energy prediction," Applied Energy, Elsevier, vol. 240(C), pages 35-45.
    12. Ferreira, Ana & Pinheiro, Manuel Duarte & de Brito, Jorge & Mateus, Ricardo, 2018. "Combined carbon and energy intensity benchmarks for sustainable retail stores," Energy, Elsevier, vol. 165(PB), pages 877-889.
    13. Lee, Wen-Shing & Kung, Chung-Kuan, 2011. "Using climate classification to evaluate building energy performance," Energy, Elsevier, vol. 36(3), pages 1797-1801.
    14. Cui, Can & Zhang, Xin & Cai, Wenjian, 2020. "An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model," Applied Energy, Elsevier, vol. 264(C).
    15. Abou-Ziyan, Hosny Z. & Alajmi, Ali F., 2014. "Effect of load-sharing operation strategy on the aggregate performance of existed multiple-chiller systems," Applied Energy, Elsevier, vol. 135(C), pages 329-338.
    16. Zhou, Yuren & Lork, Clement & Li, Wen-Tai & Yuen, Chau & Keow, Yeong Ming, 2019. "Benchmarking air-conditioning energy performance of residential rooms based on regression and clustering techniques," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    18. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    19. Li, Xinyi & Yao, Runming & Li, Qin & Ding, Yong & Li, Baizhan, 2018. "An object-oriented energy benchmark for the evaluation of the office building stock," Utilities Policy, Elsevier, vol. 51(C), pages 1-11.
    20. Antonio Attanasio & Marco Savino Piscitelli & Silvia Chiusano & Alfonso Capozzoli & Tania Cerquitelli, 2019. "Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates," Energies, MDPI, vol. 12(7), pages 1-25, April.

    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:eee:appene:v:171:y:2016:i:c:p:541-554. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.