IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i10p2627-d1659472.html
   My bibliography  Save this article

Green’s Function Approach for Simulating District Heating Networks

Author

Listed:
  • Ke Xu

    (Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China
    State Grid Smart Internet of Vehicle Co., Ltd., Beijing 100052, China)

  • Dengxin Ai

    (Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China)

  • Changlong Sun

    (Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China)

  • Yan Qi

    (Electric Power Research Institute of State Grid, Tianjin Electric Power Company, Tianjin 300010, China)

  • Jiaojiao Wang

    (Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
    Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China)

  • Fan Yang

    (Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
    Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China)

  • Hechen Ren

    (Center for Joint Quantum Studies, Department of Physics, Tianjin University, Tianjin 300350, China
    Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Department of Physics, Tianjin University, Tianjin 300350, China
    Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou 350207, China)

Abstract

In this paper, we introduce a mathematical framework for analyzing and optimizing district heating networks by leveraging the Green’s function method. Traditional numerical methods for simulating district heating networks often face computational challenges and lack transparency in revealing cause-and-effect relationships in heat propagation. By treating temperature as a scalar field, we employ Green’s function methods to derive analytical solutions that provide a more transparent and intuitive understanding of how heat propagates through the network in response to various inputs. We demonstrate the application of this framework through two numerical examples involving heating networks. Comparative results show that, under identical hardware conditions, the Green’s function method requires only about one-fifth of the computational time compared to the finite element method for the same case. This approach offers distinct advantages in terms of computational efficiency, accuracy, and interpretability, enabling more effective design, optimization, and control of sustainable district heating systems.

Suggested Citation

  • Ke Xu & Dengxin Ai & Changlong Sun & Yan Qi & Jiaojiao Wang & Fan Yang & Hechen Ren, 2025. "Green’s Function Approach for Simulating District Heating Networks," Energies, MDPI, vol. 18(10), pages 1-13, May.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2627-:d:1659472
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/10/2627/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/10/2627/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schweiger, Gerald & Larsson, Per-Ola & Magnusson, Fredrik & Lauenburg, Patrick & Velut, Stéphane, 2017. "District heating and cooling systems – Framework for Modelica-based simulation and dynamic optimization," Energy, Elsevier, vol. 137(C), pages 566-578.
    2. Zarin Pass, R. & Wetter, M. & Piette, M.A., 2018. "A thermodynamic analysis of a novel bidirectional district heating and cooling network," Energy, Elsevier, vol. 144(C), pages 20-30.
    3. Kuntuarova, Saltanat & Licklederer, Thomas & Huynh, Thanh & Zinsmeister, Daniel & Hamacher, Thomas & Perić, Vedran, 2024. "Design and simulation of district heating networks: A review of modeling approaches and tools," Energy, Elsevier, vol. 305(C).
    4. Dénarié, A. & Aprile, M. & Motta, M., 2019. "Heat transmission over long pipes: New model for fast and accurate district heating simulations," Energy, Elsevier, vol. 166(C), pages 267-276.
    5. Guelpa, Elisa & Verda, Vittorio, 2019. "Compact physical model for simulation of thermal networks," Energy, Elsevier, vol. 175(C), pages 998-1008.
    6. Shangwei Liu & Yang Guo & Fabian Wagner & Hongxun Liu & Ryna Yiyun Cui & Denise L. Mauzerall, 2024. "Diversifying heat sources in China’s urban district heating systems will reduce risk of carbon lock-in," Nature Energy, Nature, vol. 9(8), pages 1021-1031, August.
    7. Sartor, K. & Dewalef, P., 2017. "Experimental validation of heat transport modelling in district heating networks," Energy, Elsevier, vol. 137(C), pages 961-968.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kuntuarova, Saltanat & Licklederer, Thomas & Huynh, Thanh & Zinsmeister, Daniel & Hamacher, Thomas & Perić, Vedran, 2024. "Design and simulation of district heating networks: A review of modeling approaches and tools," Energy, Elsevier, vol. 305(C).
    2. De Lorenzi, Andrea & Gambarotta, Agostino & Morini, Mirko & Rossi, Michele & Saletti, Costanza, 2020. "Setup and testing of smart controllers for small-scale district heating networks: An integrated framework," Energy, Elsevier, vol. 205(C).
    3. Boghetti, Roberto & Kämpf, Jérôme H., 2024. "Verification of an open-source Python library for the simulation of district heating networks with complex topologies," Energy, Elsevier, vol. 290(C).
    4. Westphal, Jan & Brunnemann, Johannes & Speerforck, Arne, 2025. "Enabling the dynamic simulation of an unaggregated, meshed district heating network with several thousand substations," Energy, Elsevier, vol. 322(C).
    5. Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    6. Xie, Zichan & Wang, Haichao & Hua, Pengmin & Lahdelma, Risto, 2023. "Discrete event simulation for dynamic thermal modelling of district heating pipe," Energy, Elsevier, vol. 285(C).
    7. Dénarié, A. & Aprile, M. & Motta, M., 2023. "Dynamical modelling and experimental validation of a fast and accurate district heating thermo-hydraulic modular simulation tool," Energy, Elsevier, vol. 282(C).
    8. Nageler, P. & Schweiger, G. & Schranzhofer, H. & Mach, T. & Heimrath, R. & Hochenauer, C., 2018. "Novel method to simulate large-scale thermal city models," Energy, Elsevier, vol. 157(C), pages 633-646.
    9. Sommer, Tobias & Sulzer, Matthias & Wetter, Michael & Sotnikov, Artem & Mennel, Stefan & Stettler, Christoph, 2020. "The reservoir network: A new network topology for district heating and cooling," Energy, Elsevier, vol. 199(C).
    10. Licklederer, Thomas & Hamacher, Thomas & Kramer, Michael & Perić, Vedran S., 2021. "Thermohydraulic model of Smart Thermal Grids with bidirectional power flow between prosumers," Energy, Elsevier, vol. 230(C).
    11. Meibodi, Saleh S. & Rees, Simon & Loveridge, Fleur, 2024. "Modeling district heating pipelines using a hybrid dynamic thermal network approach," Energy, Elsevier, vol. 290(C).
    12. Qin, Xin & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Dibos, Sina & Pesch, Thiemo & Benigni, Andrea, 2024. "HeatNetSim: An open-source simulation tool for heating and cooling networks suitable for future energy systems," Energy, Elsevier, vol. 312(C).
    14. Zheng, Xuejing & Shi, Zhiyuan & Wang, Yaran & Zhang, Huan & Liu, Huzhen, 2023. "Thermo-hydraulic condition optimization of large-scale complex district heating network: A case study of Tianjin," Energy, Elsevier, vol. 266(C).
    15. Zheng, Xuejing & Sun, Qihang & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & You, Shijun & Zhang, Huan & Shi, Kaiyu, 2021. "Thermo-hydraulic coupled simulation and analysis of a real large-scale complex district heating network in Tianjin," Energy, Elsevier, vol. 236(C).
    16. Dancker, Jonte & Wolter, Martin, 2021. "Improved quasi-steady-state power flow calculation for district heating systems: A coupled Newton-Raphson approach," Applied Energy, Elsevier, vol. 295(C).
    17. Nageler, P. & Heimrath, R. & Mach, T. & Hochenauer, C., 2019. "Prototype of a simulation framework for georeferenced large-scale dynamic simulations of district energy systems," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    18. Steinegger, Josef & Wallner, Stefan & Greiml, Matthias & Kienberger, Thomas, 2023. "A new quasi-dynamic load flow calculation for district heating networks," Energy, Elsevier, vol. 266(C).
    19. Brown, Alastair & Foley, Aoife & Laverty, David & McLoone, Seán & Keatley, Patrick, 2022. "Heating and cooling networks: A comprehensive review of modelling approaches to map future directions," Energy, Elsevier, vol. 261(PB).
    20. Edtmayer, Hermann & Nageler, Peter & Heimrath, Richard & Mach, Thomas & Hochenauer, Christoph, 2021. "Investigation on sector coupling potentials of a 5th generation district heating and cooling network," Energy, Elsevier, vol. 230(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2627-:d:1659472. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.