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Effect of disturbance on thermal response test, part 2: Numerical study of applicability and limitation of infinite line source model for interpretation under disturbance from outdoor environment

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  • Choi, Wonjun
  • Ooka, Ryozo

Abstract

The approximated infinite line source (ILS) model is widely used to interpret thermal response tests (TRTs). It assumes a constant heat flux from the source. However, this assumption is violated in real field conditions by the heat exchange between the circulating fluid and the outdoor environment in an above-ground TRT setup. This results in a fluctuating behavior of sequential estimation and estimation error. In this study, we quantitatively examined the effect of disturbance from outdoor environment on TRTs, especially when TRTs are interpreted by the ILS model, using numerical methods. An analytical model that takes disturbance into account was incorporated as the boundary condition of a numerical model. Using typical synthetic weather data of different seasons and 36 cases of measured weather data, numerical TRTs were conducted and interpreted. Some characteristic behavior of interpretation related to weather conditions was explained and changes in error range with testing duration were analyzed to clarify the applicability and limitation of the interpretation using the ILS model. The results showed that at least 60 h of TRT is required to obtain results within the error range of ±5% compared with the reference case. Additionally, some practical suggestions regarding conducting and interpreting TRTs are provided.

Suggested Citation

  • Choi, Wonjun & Ooka, Ryozo, 2016. "Effect of disturbance on thermal response test, part 2: Numerical study of applicability and limitation of infinite line source model for interpretation under disturbance from outdoor environment," Renewable Energy, Elsevier, vol. 85(C), pages 1090-1105.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:1090-1105
    DOI: 10.1016/j.renene.2015.07.049
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    1. Zhang, Changxing & Song, Wei & Liu, Yufeng & Kong, Xiangqiang & Wang, Qing, 2019. "Effect of vertical ground temperature distribution on parameter estimation of in-situ thermal response test with unstable heat rate," Renewable Energy, Elsevier, vol. 136(C), pages 264-274.
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    3. Zhang, Xueping & Han, Zongwei & Ji, Qiang & Zhang, Hongzhi & Li, Xiuming, 2021. "Thermal response tests for the identification of soil thermal parameters: A review," Renewable Energy, Elsevier, vol. 173(C), pages 1123-1135.
    4. Tang, Fujiao & Nowamooz, Hossein, 2019. "Sensitive analysis on the effective soil thermal conductivity of the Thermal Response Test considering various testing times, field conditions and U-pipe lengths," Renewable Energy, Elsevier, vol. 143(C), pages 1732-1743.
    5. Tang, Fujiao & Nowamooz, Hossein, 2020. "Outlet temperatures of a slinky-type Horizontal Ground Heat Exchanger with the atmosphere-soil interaction," Renewable Energy, Elsevier, vol. 146(C), pages 705-718.
    6. Tang, F. & Lahoori, M. & Nowamooz, H. & Rosin-Paumier, S. & Masrouri, F., 2021. "A numerical study into effects of soil compaction and heat storage on thermal performance of a Horizontal Ground Heat Exchanger," Renewable Energy, Elsevier, vol. 172(C), pages 740-752.
    7. Choi, Wonjun & Kikumoto, Hideki & Choudhary, Ruchi & Ooka, Ryozo, 2018. "Bayesian inference for thermal response test parameter estimation and uncertainty assessment," Applied Energy, Elsevier, vol. 209(C), pages 306-321.
    8. Li, Biao & Han, Zongwei & Bai, Chenguang & Hu, Honghao, 2019. "The influence of soil thermal properties on the operation performance on ground source heat pump system," Renewable Energy, Elsevier, vol. 141(C), pages 903-913.
    9. Choi, Wonjun & Menberg, Kathrin & Kikumoto, Hideki & Heo, Yeonsook & Choudhary, Ruchi & Ooka, Ryozo, 2018. "Bayesian inference of structural error in inverse models of thermal response tests," Applied Energy, Elsevier, vol. 228(C), pages 1473-1485.
    10. Zhang, Xueping & Han, Zongwei & Meng, Xinwei & Li, Gui & Ji, Qiang & Li, Xiuming & Yang, Lingyan, 2021. "Study on high-precision identification method of ground thermal properties based on neural network model," Renewable Energy, Elsevier, vol. 163(C), pages 1838-1848.
    11. Zhang, Xueping & Han, Zongwei & Li, Gui & Li, Xiuming, 2022. "Effect of temperature measurement error on parameters estimation accuracy for thermal response tests," Renewable Energy, Elsevier, vol. 185(C), pages 230-240.
    12. Choi, Wonjun & Ooka, Ryozo, 2016. "Effect of natural convection on thermal response test conducted in saturated porous formation: Comparison of gravel-backfilled and cement-grouted borehole heat exchangers," Renewable Energy, Elsevier, vol. 96(PA), pages 891-903.
    13. Wołoszyn, Jerzy, 2020. "Global sensitivity analysis of borehole thermal energy storage efficiency for seventeen material, design and operating parameters," Renewable Energy, Elsevier, vol. 157(C), pages 545-559.
    14. Yongjie Ma & Yanjun Zhang & Yuxiang Cheng & Yu Zhang & Xuefeng Gao & Hao Deng & Xin Zhang, 2022. "Influence of Different Heat Loads and Durations on the Field Thermal Response Test," Energies, MDPI, vol. 15(22), pages 1-17, November.

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