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Soil temperature gradient as a useful tool for small water leakage detection from district heating pipes in buried channels

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  • Perpar, Matjaž
  • Rek, Zlatko

Abstract

A methodology for detecting small leakages from pipelines placed in buried concrete channels is presented. This methodology is based on determining soil temperature gradient using appropriate numerical and experimental processes. An equivalent thermal conductivity (λeq) was defined based on the known heat flux and temperature gradient through the insulation subjected to the leakage. Two dimensional (2D) transient–steady-state–combined simulations were conducted for evaluating the channel cross-section heat loss. To mimic the leakage, λeq values in the range 0.5–10 W/(m·K) were used. The computation exhibited a large increase in the soil temperature gradient above the channel in case of leakage, from approximately 25 °C/m for dry insulation to approximately 50 °C/m at λeq = 0.5 W/(m·K). The procedure including the evaluation of the soil thermal conductivity λs, developed in our previous work, and further soil temperature gradient monitoring through computation and measurements enabled the detection of minor leakages in a pipeline section. Applying the proposed methodology to an entire network could contribute to comprehensive leakage control in district heating systems.

Suggested Citation

  • Perpar, Matjaž & Rek, Zlatko, 2020. "Soil temperature gradient as a useful tool for small water leakage detection from district heating pipes in buried channels," Energy, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:energy:v:201:y:2020:i:c:s036054422030791x
    DOI: 10.1016/j.energy.2020.117684
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    1. Ziemele, Jelena & Gravelsins, Armands & Blumberga, Andra & Blumberga, Dagnija, 2017. "Combining energy efficiency at source and at consumer to reach 4th generation district heating: Economic and system dynamics analysis," Energy, Elsevier, vol. 137(C), pages 595-606.
    2. Sartor, K. & Quoilin, S. & Dewallef, P., 2014. "Simulation and optimization of a CHP biomass plant and district heating network," Applied Energy, Elsevier, vol. 130(C), pages 474-483.
    3. Volkova, Anna & Mašatin, Vladislav & Siirde, Andres, 2018. "Methodology for evaluating the transition process dynamics towards 4th generation district heating networks," Energy, Elsevier, vol. 150(C), pages 253-261.
    4. Lund, Henrik & Werner, Sven & Wiltshire, Robin & Svendsen, Svend & Thorsen, Jan Eric & Hvelplund, Frede & Mathiesen, Brian Vad, 2014. "4th Generation District Heating (4GDH)," Energy, Elsevier, vol. 68(C), pages 1-11.
    5. Perpar, Matjaz & Rek, Zlatko & Bajric, Suvad & Zun, Iztok, 2012. "Soil thermal conductivity prediction for district heating pre-insulated pipeline in operation," Energy, Elsevier, vol. 44(1), pages 197-210.
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    Cited by:

    1. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & You, Shijun, 2022. "Valve failure detection of the long-distance district heating pipeline by hydraulic oscillation recognition: A numerical approach," Energy, Elsevier, vol. 261(PA).
    2. Yihong Guan & Mou Lv & Shen Dong, 2023. "Pressure-driven Background Leakage Models and their Application for Leak Localization Using a Multi-population Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 359-373, January.
    3. Sun, Chunhua & Zhang, Haixiang & Cao, Shanshan & Xia, Guoqiang & Zhong, Jian & Wu, Xiangdong, 2023. "A hierarchical classifying and two-step training strategy for detection and diagnosis of anormal temperature in district heating system," Applied Energy, Elsevier, vol. 349(C).
    4. Zheng, Xuejing & Hu, Fangshu & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & Zhang, Huan & You, Shijun & Xu, Boxiao, 2021. "Leak detection of long-distance district heating pipeline: A hydraulic transient model-based approach," Energy, Elsevier, vol. 237(C).
    5. Jing, Mengke & Zhang, Shujie & Fu, Lisong & Cao, Guoquan & Wang, Rui, 2023. "Reducing heat losses from aging district heating pipes by using cured-in-place pipe liners," Energy, Elsevier, vol. 273(C).
    6. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & You, Shijun, 2024. "Pump-stopping-induced hydraulic oscillations in long-distance district heating system: Modelling and a comprehensive analysis of critical factors," Energy, Elsevier, vol. 294(C).
    7. Zhu, Jianlu & Wang, Sailei & Pan, Jun & Lv, Hao & Zhang, Yixiang & Han, Hui & Liu, Cuiwei & Duo, Zhili & Li, Yuxing, 2024. "Experimental study on leakage temperature field of hydrogen blending into natural gas buried pipeline," Applied Energy, Elsevier, vol. 359(C).
    8. Matjaž Perpar & Zlatko Rek, 2021. "The Ability of a Soil Temperature Gradient-Based Methodology to Detect Leaks from Pipelines in Buried District Heating Channels," Energies, MDPI, vol. 14(18), pages 1-13, September.

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