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Performance assessment of district cooling systems for a new development district at planning stage

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  • Gang, Wenjie
  • Wang, Shengwei
  • Gao, Diance
  • Xiao, Fu

Abstract

A district cooling system supplies cooling to a group of buildings in a district. It has been widely used for its high energy and economic performance, especially in Asian and European countries. It is supposed that a district cooling system can achieve good performance when used in the subtropical area like Hong Kong, where the cooling is required throughout the year and the building density is very high. This study aims to quantitatively assess the performance of the district cooling system in a new development area in Hong Kong. By modeling the buildings and cooling systems of the new district based on the current plan, the performance of district cooling system is compared with the conventional cooling system, which refers to individual in-building cooling systems. Three cases with different chilled water systems are simulated and analyzed. Results show that the district cooling system is more efficient than the individual cooling system, with less energy consumption and operational cost. Energy consumption of main subsystems is compared and the energy saving potential of district cooling system is analyzed. Sensitivity study of district cooling system performance at partial load is conducted and results show that the district cooling system is more efficient under different load conditions during night time.

Suggested Citation

  • Gang, Wenjie & Wang, Shengwei & Gao, Diance & Xiao, Fu, 2015. "Performance assessment of district cooling systems for a new development district at planning stage," Applied Energy, Elsevier, vol. 140(C), pages 33-43.
    • Handle: RePEc:eee:appene:v:140:y:2015:i:c:p:33-43
    DOI: 10.1016/j.apenergy.2014.11.014
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    References listed on IDEAS

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    Cited by:

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    3. An, Jingjing & Yan, Da & Hong, Tianzhen & Sun, Kaiyu, 2017. "A novel stochastic modeling method to simulate cooling loads in residential districts," Applied Energy, Elsevier, vol. 206(C), pages 134-149.
    4. Li, Sihui & Gong, Guangcai & Peng, Jinqing, 2019. "Dynamic coupling method between air-source heat pumps and buildings in China’s hot-summer/cold-winter zone," Applied Energy, Elsevier, vol. 254(C).
    5. Gang, Wenjie & Augenbroe, Godfried & Wang, Shengwei & Fan, Cheng & Xiao, Fu, 2016. "An uncertainty-based design optimization method for district cooling systems," Energy, Elsevier, vol. 102(C), pages 516-527.
    6. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    7. Rismanchi, B., 2017. "District energy network (DEN), current global status and future development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 571-579.
    8. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    9. Deng, Na & He, Guansong & Gao, Yuan & Yang, Bin & Zhao, Jun & He, Shunming & Tian, Xue, 2017. "Comparative analysis of optimal operation strategies for district heating and cooling system based on design and actual load," Applied Energy, Elsevier, vol. 205(C), pages 577-588.
    10. Rabah Ismaen & Tarek Y. ElMekkawy & Shaligram Pokharel & Adel Elomri & Mohammed Al-Salem, 2022. "Solar Technology and District Cooling System in a Hot Climate Regions: Optimal Configuration and Technology Selection," Energies, MDPI, vol. 15(7), pages 1-24, April.
    11. Ding, Yan & Wang, Qiaochu & Kong, Xiangfei & Yang, Kun, 2019. "Multi-objective optimisation approach for campus energy plant operation based on building heating load scenarios," Applied Energy, Elsevier, vol. 250(C), pages 1600-1617.
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    15. Gang, Wenjie & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "Robust optimal design of building cooling systems considering cooling load uncertainty and equipment reliability," Applied Energy, Elsevier, vol. 159(C), pages 265-275.
    16. Happle, Gabriel & Fonseca, Jimeno A. & Schlueter, Arno, 2020. "Impacts of diversity in commercial building occupancy profiles on district energy demand and supply," Applied Energy, Elsevier, vol. 277(C).
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    18. Valerie Eveloy & Dereje S. Ayou, 2019. "Sustainable District Cooling Systems: Status, Challenges, and Future Opportunities, with Emphasis on Cooling-Dominated Regions," Energies, MDPI, vol. 12(2), pages 1-64, January.
    19. Deng, Na & Cai, Rongchang & Gao, Yuan & Zhou, Zhihua & He, Guansong & Liu, Dongyi & Zhang, Awen, 2017. "A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin," Energy, Elsevier, vol. 141(C), pages 1750-1763.
    20. Gao, Cheng & Wang, Dan & Sun, Yuying & Wang, Wei & Zhang, Xiuyu, 2023. "Optimal load dispatch of multi-source looped district cooling systems based on energy and hydraulic performances," Energy, Elsevier, vol. 274(C).

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