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Analysis of operational data from a district cooling system and its connected buildings

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  • Jangsten, Maria
  • Lindholm, Torbjörn
  • Dalenbäck, Jan-Olof

Abstract

District cooling systems are likely to become more common as the cooling demands in cities increase. Their performance is often challenged by low temperature differences between the supply and return water, called low delta-T. Few previous studies have investigated low delta-Ts in district cooling systems with heat exchangers separating the distribution system and the connected buildings, which therefore is the objective of this study. The study is based on an analysis of operational data from both district cooling provider and 37 of the connected buildings chilled water systems, collected from the energy transfer stations during spring and summer of 2018. The design delta-T in the district cooling system is 10 °C, while the actual delta-T varies between 6 and 8 °C. The study shows the main causes to the low delta-T are the following: operation in the saturation zone; too low building chilled water return temperature; too low temperature approach of the heat exchanger’s supply streams and non-optimized supply temperatures in the buildings. Potential solutions to resolve the low delta-T include adjusting the supply temperature setpoint on the secondary side; restricting the flow on the primary side; providing economic incentives for the district cooling customers and ensuring compliance with the design guidelines.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:203:y:2020:i:c:s0360544220309518
    DOI: 10.1016/j.energy.2020.117844
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    References listed on IDEAS

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    1. Jangsten, Maria & Filipsson, Peter & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2020. "High Temperature District Cooling: Challenges and Possibilities Based on an Existing District Cooling System and its Connected Buildings," Energy, Elsevier, vol. 199(C).
    2. Gang, Wenjie & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2016. "District cooling systems: Technology integration, system optimization, challenges and opportunities for applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 253-264.
    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. 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.
    5. 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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    Citations

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    Cited by:

    1. Stanislav Chicherin & Andrey Zhuikov & Lyazzat Junussova, 2023. "District Heating for Poorly Insulated Residential Buildings—Comparing Results of Visual Study, Thermography, and Modeling," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    2. Neri, Manfredi & Guelpa, Elisa & Verda, Vittorio, 2022. "Design and connection optimization of a district cooling network: Mixed integer programming and heuristic approach," Applied Energy, Elsevier, vol. 306(PA).
    3. Chicherin, Stanislav & Anvari-Moghaddam, Amjad, 2021. "Adjusting heat demands using the operational data of district heating systems," Energy, Elsevier, vol. 235(C).
    4. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
    5. Salah Vaisi & Saleh Mohammadi & Kyoumars Habibi, 2021. "Heat Mapping, a Method for Enhancing the Sustainability of the Smart District Heat Networks," Energies, MDPI, vol. 14(17), pages 1-17, September.
    6. Chicherin, Stanislav & Starikov, Aleksander & Zhuikov, Andrey, 2022. "Justifying network reconstruction when switching to low temperature district heating," Energy, Elsevier, vol. 248(C).
    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).

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