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Diagnosis of the low temperature difference syndrome in the chilled water system of a super high-rise building: A case study

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  • Gao, Dian-ce
  • Wang, Shengwei
  • Sun, Yongjun
  • Xiao, Fu

Abstract

The low delta-T syndrome exists in many large primary–secondary chilled water systems, which results in the degradation of the system overall energy performance. This paper presents a method and a case study on diagnosing the low delta-T problem resulted from the deficit flow that frequently occurred in the chilled water system of a super high-rise building at its early operation stage. The history operation data during the days when deficit flow and low delta-T syndrome occurred are analyzed. The improper set-point of outlet water temperature on the secondary side of heat exchangers is finally diagnosed as the fault that resulted in the deficit flow and low delta-T syndrome. Diagnosis of this fault was also validated in the in situ experimental tests. The deficit flow could be eliminated if temperature set-point was reset higher. Compared with the original set-point of outlet water temperature on the secondary side of heat exchangers, 87.67kW (72.37%) of the total power of pumps on primary and secondary sides of heat exchangers could be saved in the test cases when higher set-points were used.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:98:y:2012:i:c:p:597-606
    DOI: 10.1016/j.apenergy.2012.03.057
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    1. 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.
    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. Cai, Baoping & Liu, Yonghong & Fan, Qian & Zhang, Yunwei & Liu, Zengkai & Yu, Shilin & Ji, Renjie, 2014. "Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network," Applied Energy, Elsevier, vol. 114(C), pages 1-9.
    5. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2022. "District cooling substation design and control to achieve high return temperatures," Energy, Elsevier, vol. 251(C).
    6. Ren, Haoshan & Xu, Chengliang & Lyu, Yuanli & Ma, Zhenjun & Sun, Yongjun, 2023. "A thermodynamic-law-integrated deep learning method for high-dimensional sensor fault detection in diverse complex HVAC systems," Applied Energy, Elsevier, vol. 351(C).

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