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Thermal transient prediction of district heating pipeline: Optimal selection of the time and spatial steps for fast and accurate calculation

Author

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  • Wang, Yaran
  • You, Shijun
  • Zhang, Huan
  • Zheng, Xuejing
  • Zheng, Wandong
  • Miao, Qingwei
  • Lu, Gang

Abstract

Predicting the thermal transients of district heating (DH) network is the key to simulation analysis and operation optimization of DH system. Numerical methods can provide accurate prediction and sufficient information of thermal transients. But the high computation burden restricts the application of numerical methods, especially when applied to operation optimization of large DH networks. This dilemma can be relieved by suitably increasing the scales of time and spatial steps, but do not obviously affect the precision of the numerical models. However, there are few researches concerning such topics. In this paper, the optimal scales of time and spatial steps of a newly proposed implicit upwind model and the characteristic line model were studied for fast and accurate calculation. Results show that both models can ensure the prediction errors of the pipeline outlet temperature within ±0.5°C. For characteristic line model, the recommended time step and spatial step are 60s and 170m<Δx<520m. And for implicit upwind method, the recommended time step and spatial step are 20s and 30m. Besides, the implicit upwind model is unconditionally stable and provides more information on temperature distribution along the pipeline, especially when small and fast propagation occurs.

Suggested Citation

  • Wang, Yaran & You, Shijun & Zhang, Huan & Zheng, Xuejing & Zheng, Wandong & Miao, Qingwei & Lu, Gang, 2017. "Thermal transient prediction of district heating pipeline: Optimal selection of the time and spatial steps for fast and accurate calculation," Applied Energy, Elsevier, vol. 206(C), pages 900-910.
    • Handle: RePEc:eee:appene:v:206:y:2017:i:c:p:900-910
    DOI: 10.1016/j.apenergy.2017.08.061
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Dobos, László & Abonyi, János, 2011. "Controller tuning of district heating networks using experiment design techniques," Energy, Elsevier, vol. 36(8), pages 4633-4639.
    4. Guelpa, Elisa & Toro, Claudia & Sciacovelli, Adriano & Melli, Roberto & Sciubba, Enrico & Verda, Vittorio, 2016. "Optimal operation of large district heating networks through fast fluid-dynamic simulation," Energy, Elsevier, vol. 102(C), pages 586-595.
    5. Duquette, Jean & Rowe, Andrew & Wild, Peter, 2016. "Thermal performance of a steady state physical pipe model for simulating district heating grids with variable flow," Applied Energy, Elsevier, vol. 178(C), pages 383-393.
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