Global sensitivity analysis and uncertainty quantification for design parameters of shallow geothermal systems

被引:0
作者
Simon Richter
Katrin Lubashevsky
Jakob Randow
Steve Henker
Jörg Buchwald
Anke Bucher
机构
[1] Leipzig University of Applied Sciences,Faculty of Engineering
[2] HTWK,Department of Environmental Informatics
[3] Helmholtz Centre for Environmental Research,Faculty of Environmental Sciences
[4] UFZ,Center for Information Services and High Performance Computing (ZIH)
[5] geoENERGIE Konzept GmbH,undefined
[6] TUD Dresden University of Technology,undefined
[7] TUD Dresden University of Technology,undefined
来源
Geothermal Energy | / 12卷
关键词
Shallow geothermal exploitation; Borehole heat exchanger; Ground source heat pump; Numerical simulation; OpenGeoSys; Sensitivity analysis; Uncertainty quantification; Sobol’ indices; Monte Carlo simulation; Machine learning;
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学科分类号
摘要
To improve the design process of geothermal systems, it is important to know which design parameters particularly affect the performance of the system. This article presents investigations on design parameters for borehole heat exchangers in the shallow subsurface. The study is based on numerical simulations with one double U-tube borehole heat exchanger and approximated models obtained using machine learning. As a result of the global sensitivity analysis, relevant parameters are identified and their respective influence on the performance of a borehole heat exchanger is compared. For example, according to this analysis, the three parameters with the highest sensitivity are the initial temperature, the heat demand and the share of the borehole heat exchanger that is surrounded by groundwater flow. Finally, the effects of uncertainties in the parameters identified as relevant for the design of a borehole heat exchanger are considered in an uncertainty quantification for a fictitious site. Uncertainties for regulatory compliance with respect to temperature limits as well as a large probability of oversizing the system were identified for the considered example. The results of the exemplary uncertainty quantification indicate that it has the potential to be a useful tool for planning practice.
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