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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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
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    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. 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).
    4. 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).
    5. 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.
    6. 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.
    7. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2022. "District cooling substation design and control to achieve high return temperatures," Energy, Elsevier, vol. 251(C).
    8. 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.

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