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An uncertainty-based design optimization method for district cooling systems

Author

Listed:
  • Gang, Wenjie
  • Augenbroe, Godfried
  • Wang, Shengwei
  • Fan, Cheng
  • Xiao, Fu

Abstract

Uncertainties exist widely at the planning and design stages of district cooling systems, which have significant impacts on the design optimization. This paper therefore proposes a design method for district cooling systems by quantifying the uncertainties, which is so-called uncertainty-based design optimization method. Uncertainties in the outdoor weather, building design/construction and indoor conditions are considered. The application of the uncertainty-based design optimization method is examined in several aspects: the performance assessment, system sizing, configuration selection and technology integration. With the performance distribution at different risk levels, the design of district cooling systems can be determined by the stakeholders based on the compromise between quantified risk and benefit. Sensitivity analysis is conducted to identify influential variables with uncertainties for the cooling loads of district cooling systems. Results show that the uncertainties in the indoor condition are the most important and the uncertainties in building design/construction have the least impact.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:102:y:2016:i:c:p:516-527
    DOI: 10.1016/j.energy.2016.02.107
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    References listed on IDEAS

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    1. 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.
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    5. Shu, Haiwen & Duanmu, Lin & Zhang, Chaohui & Zhu, Yingxin, 2010. "Study on the decision-making of district cooling and heating systems by means of value engineering," Renewable Energy, Elsevier, vol. 35(9), pages 1929-1939.
    6. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
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