基于DST模型的地埋管蓄热系统土壤参数反演方法及应用

王茜如; 冯国会; 黄凯良; 戴晓欣; 刘瞧宇; 卢伟东

doi:10.19799/j.cnki.2095-4239.2025.1167

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基于DST模型的地埋管蓄热系统土壤参数反演方法及应用

储能测试与评价 | 更新时间：2026-07-13

- 基于DST模型的地埋管蓄热系统土壤参数反演方法及应用
- Soil parameter inversion method and application of borehole thermal energy storage system based on DST model
- 储能科学与技术 2026年15卷第6期页码：2408-2417
- 作者机构：
  
  沈阳建筑大学市政与环境工程学院，辽宁沈阳 110168
- 作者简介：
  
  王茜如（1996—），女，博士研究生，主要从事地埋管跨季节储热研究，E-mail：wangxiru1129@163.com；
  冯国会，教授，主要从事相变储能、可再生能源利用研究，E-mail：fengguohui888@163.com。
- 基金信息：
  
  “十四五”国家重点研发计划资助(2022YFC3802400)
- DOI：10.19799/j.cnki.2095-4239.2025.1167
  中图分类号： TK 529
- 收稿：2025-12-29，
  
  修回：2026-01-21，
  
  纸质出版：2026-06-28
- 稿件说明：
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王茜如, 冯国会, 黄凯良, 等. 基于DST模型的地埋管蓄热系统土壤参数反演方法及应用[J]. 储能科学与技术, 2026, 15(6): 2408-2417.

WANG Xiru, FENG Guohui, HUANG Kailiang, et al. Soil parameter inversion method and application of borehole thermal energy storage system based on DST model[J]. Energy Storage Science and Technology, 2026, 15(6): 2408-2417.
王茜如, 冯国会, 黄凯良, 等. 基于DST模型的地埋管蓄热系统土壤参数反演方法及应用[J]. 储能科学与技术, 2026, 15(6): 2408-2417. DOI： 10.19799/j.cnki.2095-4239.2025.1167.

WANG Xiru, FENG Guohui, HUANG Kailiang, et al. Soil parameter inversion method and application of borehole thermal energy storage system based on DST model[J]. Energy Storage Science and Technology, 2026, 15(6): 2408-2417. DOI： 10.19799/j.cnki.2095-4239.2025.1167.

摘要

准确获取土壤热物性参数是地埋管蓄热（BTES）系统进行可靠设计与优化的基础。为解决传统热响应测试（TRT）要求输入恒定、无法准确估计体积热容等问题，提出了一种基于管道地面蓄热模型（DST模型）和实测运行数据的BTES蓄热系统实际性能反演方法，使用基于惯性权值法的粒子群优化算法（PSOIWM），将归一化综合均方根误差（RMSE）作为优化目标，反演土壤初始温度、土壤热导率和土壤体积热容。运用该反演方法，日均出水温度的预测误差从1.28%降低至0.39%；土壤平均温度的预测误差从5.16%显著降低至0.27%。综合RMSE从2.00℃降至0.80℃。对验证期的独立评估进一步证实了反演模型的优越性。相较于初始参数，反演参数预测的出水温度平均相对误差降低了54.2%，土壤平均温度的相对误差全程波动小于0.5%，平均相对误差为0.24%。反演参数预测的综合RMSE为0.58℃，其中RMSE

fluid

为0.25℃，RMSE

soil

为0.05℃，预测精度提升了71%。与采用TRT获得的初始参数工况相比，优化后的反演参数使模型对系统实际性能的预测精度显著提升。本研究为利用实测数据精准反演土壤参数并有效预测系统实际性能提供了一种高效可靠的方法。

Abstract

Borehole thermal energy storage (BTES) technology has been identified as a key solution to the mismatch between waste heat generation and utilization. Accurate determin

ation of the thermal physical parameters of soil is paramount for the reliable design and optimization of the BTES system. To address the limitations of the conventional thermal response test (TRT)

such as the requirement for constant input and the inability to accurately estimate the volumetric heat capacity

a method for inverting the actual performance of the BTES system based on the duct ground heat storage model and measured operation data is proposed. The particle swarm optimization algorithm based on the inertia weight method was employed to minimize the normalized comprehensive root mean square error (RMSE) to invert the initial soil temperature

thermal conductivity

and volumetric heat capacity. An experimental platform was established for the cross-seasonal heat storage and heating system of buried pipes. Following a three-month heat storage period

an increase in the average soil temperature was observed. The heat storage body of the buried pipes exhibited an increase from 12.81℃ to 16.09℃. The average daily heat storage capacity was determined to be 344.99 kW·h

and the total heat storage capacity was found to be 32.08 MW·h. The application of the proposed inversion method reduced the prediction error of the average daily effluent temperature from 1.28% to 0.39%. The prediction error of the average soil temperature decreased significantly from 5.16% to 0.27%. Consequently

the comprehensive RMSE decreased from 2.00℃ to 0.80℃. An independent assessment of the validation period further confirmed the superiority of the proposed inversion model. Compared with the initial parameters

the average relative error of the discharge temperature predicted by the inverted parameters decreased by 54.2%. The relative error of the average soil temperature fluctuated below 0.5% throughout the process

with an average relative error of 0.24%. The comprehensive RMSE for the inverted parameter predictions was 0.58℃

comprising RMSE

fluid

and RMSE

soil

of 0.25℃ and 0.05℃

respectively

representing a

71% improvement in prediction accuracy. A comparison of the initial parameter conditions obtained using the TRT with the optimized inverted parameters reveals a significant enhancement in the predictive accuracy of the model for the actual system performance. This study proposes an efficient and reliable method for precisely inverting soil parameters using measured data and effectively predicting the actual system performance.

关键词

Keywords

references

江亿, 胡姗. 中国城乡能源供给系统的低碳途径[J]. 科技导报, 2023, 41(16): 6-22. DOI:10.3981/j.issn.1000-7857.2023.16.001.

JIANG Y, HU S. The low carbon transition approach for China's urban and rural energy supply systems[J]. Science & Technology Review, 2023, 41(16): 6-22. DOI:10.3981/j.issn.1000-7857.2023. 16.001.

WANG X R, FENG G H, HUANG K L, et al. Experimental and numerical study on heat storage and extraction characteristics of single and double U-tube borehole heat exchangers for thermal energy storage[J]. Renewable Energy, 2026, 257: 124792. DOI:10.1016/j.renene.2025.124792.

王子逸, 徐玉杰, 周学志, 等. 跨季节复合储热系统储/释热特性[J]. 储能科学与技术, 2020, 9(6): 1837-1846. DOI:10.19799/j.cnki.2095-4239.2020.0101.

WANG Z Y, XU Y J, ZHOU X Z, et al. Storage and release characteristics of seasonal composite thermal storage system[J]. Energy Storage Science and Technology, 2020, 9(6): 1837-1846. DOI:10.19799/j.cnki.2095-4239.2020.0101.

XU J, WANG R Z, LI Y. A review of available technologies for seasonal thermal energy storage[J]. Solar Energy, 2014, 103: 610-638. DOI:10.1016/j.solener.2013.06.006.

YANG T R, LIU W, KRAMER G J, et al. Seasonal thermal energy storage: A techno-economic literature review[J]. Renewable and Sustainable Energy Reviews, 2021, 139: 110732. DOI:10.1016/j.rser.2021.110732.

YANG F, LIU M, SHEN Y, et al. Cross-seasonal storage of flue gas waste heat from power plants based on soil heat storage using buried pipes: Geotechnical thermal response experiment[J]. Energies, 2025, 18(9): 2191. DOI:10.3390/en18092191.

徐德厚, 周学志, 徐玉杰, 等. 新型地下跨季节复合储热系统性能规律[J]. 储能科学与技术, 2021, 10(5): 1768-1776.

XU D H, ZHOU X Z, XU Y J, et al. Performance law of a new composite seasonal underground thermal storage system[J]. Energy Storage Science and Technology, 2021, 10(5): 1768-1776.

冯国会, 卢伟东, 王茜如, 等. 运行参数及间歇启停策略对地埋管蓄热性能的影响[J]. 储能科学与技术, 2025, 14(10): 3785-3795.

FENG G H, LU W D, WANG X R, et al. Influence of operational parameters and intermittent start-stop strategy on thermal storage performance of ground heat exchangers[J]. Energy Storage Science and Technology, 2025, 14(10): 3785-3795.

王茜如, 冯国会, 黄凯良, 等. 季节性埋管蓄热系统长周期蓄取热特性及参数敏感性分析[J]. 工程热物理学报, 2025, 46(11): 3728-3738.

WANG X R, FENG G H, HUANG K L, et al. Long period heat storage characteristics and parameter sensitivity analysis of seasonal borehole thermal energy storage system[J]. Journal of Engineering Thermophysics, 2025, 46(11): 3728-3738.

JIA J, LEE W L, CHENG Y D. Field demonstration of a first constant-temperature thermal response test with both heat injection and extraction for ground source heat pump systems[J]. Applied Energy, 2019, 249: 79-86. DOI:10.1016/j.apenergy. 2019.04.145.

WAGNER V, BAYER P, KÜBERT M, et al. Numerical sensitivity study of thermal response tests[J]. Renewable Energy, 2012, 41: 245-253. DOI:10.1016/j.renene.2011.11.001.

HAN Z W, ZHANG S W, LI B, et al. Study on the influence of the identification model on the accuracy of the thermal response test[J]. Geothermics, 2018, 72: 316-322. DOI:10.1016/j.geothermics. 2017.11.018.

ZHANG X P, HAN Z W, JI Q, et al. Thermal response tests for the identification of soil thermal parameters: A review[J]. Renewable Energy, 2021, 173: 1123-1135. DOI:10.1016/j.renene.2020.12.028.

MCDANIEL A, TINJUM J, HART D J, et al. Distributed thermal response test to analyze thermal properties in heterogeneous lithology[J]. Geothermics, 2018, 76: 116-124. DOI:10.1016/j.geothermics.2018.07.003.

WITTE H J L. Advances in geothermal response testing[M]//Thermal Energy Storage for Sustainable Energy Consumption. Dordrecht: Springer Netherlands, 2007: 177-192. DOI:10.1007/978-1-4020-5290-3_9.

张长兴, 胡松涛, 刘玉峰, 等. 基于系统优化的岩土热物性确定方法[J]. 浙江大学学报(工学版), 2012, 46(12): 2237-2242.

ZHANG C X, HU S T, LIU Y F, et al. Determination method for rock-soil thermal properties based on system optimization[J]. Journal of Zhejiang University (Engineering Science), 2012, 46(12): 2237-2242.

ZHANG X D, JIANG Y Q, YAO Y, et al. A TRNSYS-based thermal response test parameter estimation method[J]. International Journal of Electrical Energy, 2016, 4(1): 28-31. DOI:10.18178/ijoee.4.1.28-31.

GUO F, YANG X D. Long-term performance simulation and sensitivity analysis of a large-scale seasonal borehole thermal energy storage system for industrial waste heat and solar energy[J]. Energy and Buildings, 2021, 236: 110768. DOI:10.1016/j.enbuild.2021.110768.

HELLSTROM G. Ground heat storage: thermal analyses of duct storage systems[D]. Lund: Lund University, 1991.

ZHANG L, XU P, MAO J C, et al. A low cost seasonal solar soil heat storage system for greenhouse heating: Design and pilot study[J]. Applied Energy, 2015, 156: 213-222. DOI:10.1016/j.apenergy.2015.07.036.

方修睦. 建筑环境测试技术[M]. 3版. 北京: 中国建筑工业出版社, 2016.FANG X M. Testing technology for building environment[M]. 3rd ed. Beijing: China Architecture & Building Press, 2016.

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