IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v267y2023ics0360544222033461.html
   My bibliography  Save this article

Mathematical modelling and model validation of the heat losses in district heating networks

Author

Listed:
  • Jakubek, Dariusz
  • Ocłoń, Paweł
  • Nowak-Ocłoń, Marzena
  • Sułowicz, Maciej
  • Varbanov, Petar Sabev
  • Klemeš, Jiří Jaromír

Abstract

Today the most popular system of district heating systems is based on pre-insulated pipes arranged in parallel or twin-pipe configuration. One of the greatest difficulties with heat distribution through pipelines is thermal loss from the distribution. The most efficient solution to that problem is optimising the insulation wall thickness layer according to the pipe diameter. Heat losses should be minimised at a relatively low investment cost to find the most suitable insulation thickness economically. Numerous studies focus on analytical (1D model) calculations and numerical simulations. However, there is a research gap related to laboratory devices that allow measuring the operation parameters (fluid flow, the temperature of the fluid in the supply pipe and the return pipe). This paper presents an analysis of the heat losses from pre-insulated pipes and twin pipes in the heating system network. This study compares the heat losses in the ground calculated by analytical solution (1D model) with the measurements on the dedicated experimental setup. The calculations have been made for several heating network pipe variants: twin pipes: DN40, DN50, DN65, and their counterparts in a single parallel pre-insulated system. The insulation thickness used in all cases is 30.85 mm for DN40 and 32.00 mm for DN50 and DN65. The insulation is made of rigid polyurethane foam that meets the requirements of the PN-EN 253 standard. During the investigation, the thermal conductivity of insulation material is examined. The obtained thermal conductivity results are used in the calculations. The results from laboratory devices and analytical models have been compared, demonstrating good agreement – with a low error level in the range of approximately 8%, depending on the type of district heating pipe. The validated mathematical model of the heating network is then used to calculate the heat losses in a heating network connecting an underground storage tank with a ground source heat pump. The economic analysis shows that after 5 y, a return on investment is expected when comparing twin-pipe systems and single-pipe pre-insulated heating networks.

Suggested Citation

  • Jakubek, Dariusz & Ocłoń, Paweł & Nowak-Ocłoń, Marzena & Sułowicz, Maciej & Varbanov, Petar Sabev & Klemeš, Jiří Jaromír, 2023. "Mathematical modelling and model validation of the heat losses in district heating networks," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222033461
    DOI: 10.1016/j.energy.2022.126460
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222033461
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.126460?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stanislav Chicherin & Vladislav Mašatin & Andres Siirde & Anna Volkova, 2020. "Method for Assessing Heat Loss in A District Heating Network with A Focus on the State of Insulation and Actual Demand for Useful Energy," Energies, MDPI, vol. 13(17), pages 1-15, September.
    2. Wang, Jiangjiang & Huo, Shuojie & Yan, Rujing & Cui, Zhiheng, 2022. "Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties," Energy, Elsevier, vol. 252(C).
    3. Niesr, 2022. "Forecast tables," National Institute UK Economic Outlook, National Institute of Economic and Social Research, vol. 0(7), pages 61-69.
    4. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    5. Jebamalai, Joseph Maria & Marlein, Kurt & Laverge, Jelle, 2022. "Design and cost comparison of district heating and cooling (DHC) network configurations using ring topology – A case study," Energy, Elsevier, vol. 258(C).
    6. Ocłoń, Paweł & Nowak-Ocłoń, Marzena & Vallati, Andrea & Quintino, Alessandro & Corcione, Massimo, 2019. "Numerical determination of temperature distribution in heating network," Energy, Elsevier, vol. 183(C), pages 880-891.
    7. Niesr, 2022. "Forecast tables," National Institute UK Economic Outlook, National Institute of Economic and Social Research, vol. 0(8), pages 76-84.
    8. Lund, Henrik & Østergaard, Poul Alberg & Chang, Miguel & Werner, Sven & Svendsen, Svend & Sorknæs, Peter & Thorsen, Jan Eric & Hvelplund, Frede & Mortensen, Bent Ole Gram & Mathiesen, Brian Vad & Boje, 2018. "The status of 4th generation district heating: Research and results," Energy, Elsevier, vol. 164(C), pages 147-159.
    9. Chen, Dongwen & Li, Yong & Abbas, Zulkarnain & Li, Dehong & Wang, Ruzhu, 2022. "Network flow calculation based on the directional nodal potential method for meshed heating networks," Energy, Elsevier, vol. 243(C).
    10. Tomasz Janusz Teleszewski & Dorota Anna Krawczyk & Antonio Rodero, 2019. "Reduction of Heat Losses Using Quadruple Heating Pre-Insulated Networks: A Case Study," Energies, MDPI, vol. 12(24), pages 1-12, December.
    11. Zhu, Tingting & Ommen, Torben & Meesenburg, Wiebke & Thorsen, Jan Eric & Elmegaard, Brian, 2021. "Steady state behavior of a booster heat pump for hot water supply in ultra-low temperature district heating network," Energy, Elsevier, vol. 237(C).
    12. Dalla Rosa, A. & Li, H. & Svendsen, S., 2011. "Method for optimal design of pipes for low-energy district heating, with focus on heat losses," Energy, Elsevier, vol. 36(5), pages 2407-2418.
    13. Lund, Henrik & Duic, Neven & Østergaard, Poul Alberg & Mathiesen, Brian Vad, 2018. "Future district heating systems and technologies: On the role of smart energy systems and 4th generation district heating," Energy, Elsevier, vol. 165(PA), pages 614-619.
    14. Wirtz, Marco & Kivilip, Lukas & Remmen, Peter & Müller, Dirk, 2020. "5th Generation District Heating: A novel design approach based on mathematical optimization," Applied Energy, Elsevier, vol. 260(C).
    15. Liu, Yanfeng & Tang, Huanlong & Chen, Yaowen & Wang, Dengjia & Song, Cong, 2022. "Optimization of layout and diameter for distributed solar heating network with multi-source and multi-sink," Energy, Elsevier, vol. 258(C).
    16. Vallati, A. & Ocłoń, P. & Colucci, C. & Mauri, L. & de Lieto Vollaro, R. & Taler, J., 2019. "Energy analysis of a thermal system composed by a heat pump coupled with a PVT solar collector," Energy, Elsevier, vol. 174(C), pages 91-96.
    17. 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).
    18. Werner, Sven, 2022. "Network configurations for implemented low-temperature district heating," Energy, Elsevier, vol. 254(PB).
    19. Dorota Anna Krawczyk & Tomasz Janusz Teleszewski, 2019. "Reduction of Heat Losses in a Pre-Insulated Network Located in Central Poland by Lowering the Operating Temperature of the Water and the Use of Egg-shaped Thermal Insulation: A Case Study," Energies, MDPI, vol. 12(11), pages 1-12, June.
    20. Niesr, 2022. "Forecast tables," National Institute UK Economic Outlook, National Institute of Economic and Social Research, vol. 0(5), pages 45-53.
    21. Ioannidis, John P.A. & Cripps, Sally & Tanner, Martin A., 2022. "Forecasting for COVID-19 has failed," International Journal of Forecasting, Elsevier, vol. 38(2), pages 423-438.
    22. Zhang, Zhaoyan & Wang, Peiguang & Jiang, Ping & Liu, Zhiheng & Fu, Lei, 2022. "Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network," Energy, Elsevier, vol. 240(C).
    23. Pirouti, Marouf & Bagdanavicius, Audrius & Ekanayake, Janaka & Wu, Jianzhong & Jenkins, Nick, 2013. "Energy consumption and economic analyses of a district heating network," Energy, Elsevier, vol. 57(C), pages 149-159.
    24. Reiners, Tobias & Gross, Michel & Altieri, Lisa & Wagner, Hermann-Josef & Bertsch, Valentin, 2021. "Heat pump efficiency in fifth generation ultra-low temperature district heating networks using a wastewater heat source," Energy, Elsevier, vol. 236(C).
    25. Buffa, Simone & Cozzini, Marco & D’Antoni, Matteo & Baratieri, Marco & Fedrizzi, Roberto, 2019. "5th generation district heating and cooling systems: A review of existing cases in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 504-522.
    26. 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).
    27. Hering, Dominik & Faller, Michael R. & Xhonneux, André & Müller, Dirk, 2022. "Operational optimization of a 4th generation district heating network with mixed integer quadratically constrained programming," Energy, Elsevier, vol. 250(C).
    28. Niesr, 2022. "Forecast tables," National Institute UK Economic Outlook, National Institute of Economic and Social Research, vol. 0(6), pages 58-66.
    29. Houjian Li & Xinya Huang & Deheng Zhou & Andi Cao & Mengying Su & Yufeng Wang & Lili Guo, 2022. "Forecasting Carbon Price in China: A Multimodel Comparison," IJERPH, MDPI, vol. 19(10), pages 1-16, May.
    30. Alexandra L’Heureux & Katarina Grolinger & Miriam A. M. Capretz, 2022. "Transformer-Based Model for Electrical Load Forecasting," Energies, MDPI, vol. 15(14), pages 1-23, July.
    31. Barco-Burgos, J. & Bruno, J.C. & Eicker, U. & Saldaña-Robles, A.L. & Alcántar-Camarena, V., 2022. "Review on the integration of high-temperature heat pumps in district heating and cooling networks," Energy, Elsevier, vol. 239(PE).
    32. Manservigi, Lucrezia & Bahlawan, Hilal & Losi, Enzo & Morini, Mirko & Spina, Pier Ruggero & Venturini, Mauro, 2022. "A diagnostic approach for fault detection and identification in district heating networks," Energy, Elsevier, vol. 251(C).
    33. Mathiesen, Brian Vad & Lund, Henrik & Connolly, David, 2012. "Limiting biomass consumption for heating in 100% renewable energy systems," Energy, Elsevier, vol. 48(1), pages 160-168.
    34. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Hiris, Daniel P. & Pop, Octavian G. & Dobrovicescu, Alexandru & Dudescu, Mircea C. & Balan, Mugur C., 2023. "Modelling of solar assisted district heating system with seasonal storage tank by two mathematical methods and with two climatic data as input," Energy, Elsevier, vol. 284(C).
    3. Liu, Zhikai & Zhang, Huan & Wang, Yaran & Fan, Xianwang & You, Shijun & Jiang, Yan & Gao, Xinlei, 2023. "Optimization of hydraulic distribution using loop adjustment method in meshed district heating system with multiple heat sources," Energy, Elsevier, vol. 284(C).

    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. Stanislav Chicherin & Vladislav Mašatin & Andres Siirde & Anna Volkova, 2020. "Method for Assessing Heat Loss in A District Heating Network with A Focus on the State of Insulation and Actual Demand for Useful Energy," Energies, MDPI, vol. 13(17), pages 1-15, September.
    2. 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).
    3. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    4. Mengting Jiang & Camilo Rindt & David M. J. Smeulders, 2022. "Optimal Planning of Future District Heating Systems—A Review," Energies, MDPI, vol. 15(19), pages 1-38, September.
    5. Calise, Francesco & Cappiello, Francesco Liberato & Cimmino, Luca & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2023. "A comparative thermoeconomic analysis of fourth generation and fifth generation district heating and cooling networks," Energy, Elsevier, vol. 284(C).
    6. Chicherin, Stanislav & Zhuikov, Andrey & Junussova, Lyazzat, 2022. "The new method for hydraulic calculations of a district heating (DH) network," Energy, Elsevier, vol. 260(C).
    7. 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).
    8. Quirosa, Gonzalo & Torres, Miguel & Chacartegui, Ricardo, 2022. "Analysis of the integration of photovoltaic excess into a 5th generation district heating and cooling system for network energy storage," Energy, Elsevier, vol. 239(PC).
    9. Chicherin, Stanislav & Anvari-Moghaddam, Amjad, 2021. "Adjusting heat demands using the operational data of district heating systems," Energy, Elsevier, vol. 235(C).
    10. Belliardi, Marco & Caputo, Paola & Ferla, Giulio & Cereghetti, Nerio & Antonioli Mantegazzini, Barbara, 2023. "An innovative application of 5GDHC: A techno-economic assessment of shallow geothermal systems potential in different European climates," Energy, Elsevier, vol. 280(C).
    11. Fester, Jakob & Østergaard, Peter Friis & Bentsen, Fredrik & Nielsen, Brian Kongsgaard, 2023. "A data-driven method for heat loss estimation from district heating service pipes using heat meter- and GIS data," Energy, Elsevier, vol. 277(C).
    12. Jie, Pengfei & Zhao, Wanyue & Li, Fating & Wei, Fengjun & Li, Jing, 2020. "Optimizing the pressure drop per unit length of district heating piping networks from an environmental perspective," Energy, Elsevier, vol. 202(C).
    13. Chicherin, Stanislav & Starikov, Aleksander & Zhuikov, Andrey, 2022. "Justifying network reconstruction when switching to low temperature district heating," Energy, Elsevier, vol. 248(C).
    14. Quirosa, Gonzalo & Torres, Miguel & Becerra, José A. & Jiménez-Espadafor, Francisco J. & Chacartegui, Ricardo, 2023. "Energy analysis of an ultra-low temperature district heating and cooling system with coaxial borehole heat exchangers," Energy, Elsevier, vol. 278(PA).
    15. Tomasz Janusz Teleszewski & Dorota Anna Krawczyk & Antonio Rodero, 2019. "Reduction of Heat Losses Using Quadruple Heating Pre-Insulated Networks: A Case Study," Energies, MDPI, vol. 12(24), pages 1-12, December.
    16. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    17. Østergaard, Poul Alberg & Werner, Sven & Dyrelund, Anders & Lund, Henrik & Arabkoohsar, Ahmad & Sorknæs, Peter & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Mathiesen, Brian Vad, 2022. "The four generations of district cooling - A categorization of the development in district cooling from origin to future prospect," Energy, Elsevier, vol. 253(C).
    18. Grzegorz Kinelski & Jakub Stęchły & Piotr Bartkowiak, 2022. "Various Facets of Sustainable Smart City Management: Selected Examples from Polish Metropolitan Areas," Energies, MDPI, vol. 15(9), pages 1-23, April.
    19. Yang, Weijia & Huang, Yuping & Zhao, Daiqing, 2023. "A coupled hydraulic–thermal dynamic model for the steam network in a heat–electricity integrated energy system," Energy, Elsevier, vol. 263(PC).
    20. 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.

    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:eee:energy:v:267:y:2023:i:c:s0360544222033461. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.