Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102985
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Title: An uncertainty-based design optimization method for district cooling systems
Authors: Gang, W 
Augenbroe, G
Wang, S 
Fan, C 
Xiao, F 
Issue Date: 1-May-2016
Source: Energy, 1 May 2016, v. 102, p. 516-527
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.
Keywords: Cooling load
District cooling system
Sensitivity analysis
Uncertainty quantification
Uncertainty-based design method
Publisher: Pergamon Press
Journal: Energy 
ISSN: 0360-5442
EISSN: 1873-6785
DOI: 10.1016/j.energy.2016.02.107
Rights: © 2016 Elsevier Ltd. All rights reserved.
© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Gang, W., Augenbroe, G., Wang, S., Fan, C., & Xiao, F. (2016). An uncertainty-based design optimization method for district cooling systems. Energy, 102, 516-527 is available at https://doi.org/10.1016/j.energy.2016.02.107.
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