IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4372-d839496.html
   My bibliography  Save this article

Development and Application of an Open-Source Framework for Automated Thermal Network Generation and Simulations in Modelica

Author

Listed:
  • Michael Mans

    (E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, 52056 Aachen, Germany
    These authors contributed equally to this work.)

  • Tobias Blacha

    (E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, 52056 Aachen, Germany
    These authors contributed equally to this work.)

  • Thomas Schreiber

    (E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, 52056 Aachen, Germany)

  • Dirk Müller

    (E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, 52056 Aachen, Germany)

Abstract

District heating and cooling (DHC) networks, and in particular, the fifth generation of DHC networks, offer great potential in increasing the overall system efficiency and reducing CO 2 emissions in the heating and cooling of urban districts. Due to the growing complexity of these energy systems, the use of new planning methods, such as the use of dynamic simulation models based on Modelica , becomes more important. However, especially with large, complex thermal networks, there is a high effort for manual model construction and parameterization. For this reason, we present a framework for automated model generation of DHC networks based on simulation models in Modelica written in Python . The core function of the Python framework is to transform a graph representation of a district heating network into a dynamic simulation model. The authors briefly describe the workflow and demonstrate its applicability with three different use cases. We investigate the impact of different design decisions, e.g., comparing the difference between central and decentral pumps as well as a combination of both in one network. In addition, we present the results of evaluating the impact of different network temperature levels or pipe insulation compared to the overall energy supplied to the network, leading to the conclusion that the presented framework is capable of reducing the manual effort for performing DHC network simulations with Modelica and allows to easily perform parameter studies in an early planning phases in the future.

Suggested Citation

  • Michael Mans & Tobias Blacha & Thomas Schreiber & Dirk Müller, 2022. "Development and Application of an Open-Source Framework for Automated Thermal Network Generation and Simulations in Modelica," Energies, MDPI, vol. 15(12), pages 1-25, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4372-:d:839496
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4372/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/12/4372/
    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. Byrne, John & Zhou, Aiming & Shen, Bo & Hughes, Kristen, 2007. "Evaluating the potential of small-scale renewable energy options to meet rural livelihoods needs: A GIS- and lifecycle cost-based assessment of Western China's options," Energy Policy, Elsevier, vol. 35(8), pages 4391-4401, August.
    3. 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.
    4. Gils, Hans Christian & Cofala, Janusz & Wagner, Fabian & Schöpp, Wolfgang, 2013. "GIS-based assessment of the district heating potential in the USA," Energy, Elsevier, vol. 58(C), pages 318-329.
    5. Lund, H. & Möller, B. & Mathiesen, B.V. & Dyrelund, A., 2010. "The role of district heating in future renewable energy systems," Energy, Elsevier, vol. 35(3), pages 1381-1390.
    6. 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.
    7. Gormally, A.M. & Whyatt, J.D. & Timmis, R.J. & Pooley, C.G., 2012. "A regional-scale assessment of local renewable energy resources in Cumbria, UK," Energy Policy, Elsevier, vol. 50(C), pages 283-293.
    8. Fuchs, Marcus & Teichmann, Jens & Lauster, Moritz & Remmen, Peter & Streblow, Rita & Müller, Dirk, 2016. "Workflow automation for combined modeling of buildings and district energy systems," Energy, Elsevier, vol. 117(P2), pages 478-484.
    9. Christopher Kennedy & John Cuddihy & Joshua Engel‐Yan, 2007. "The Changing Metabolism of Cities," Journal of Industrial Ecology, Yale University, vol. 11(2), pages 43-59, April.
    10. 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.
    11. 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).
    12. 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).
    13. Lund, Henrik & Østergaard, Poul Alberg & Nielsen, Tore Bach & Werner, Sven & Thorsen, Jan Eric & Gudmundsson, Oddgeir & Arabkoohsar, Ahmad & Mathiesen, Brian Vad, 2021. "Perspectives on fourth and fifth generation district heating," Energy, Elsevier, vol. 227(C).
    14. Guelpa, Elisa & Verda, Vittorio, 2021. "Demand response and other demand side management techniques for district heating: A review," Energy, Elsevier, vol. 219(C).
    15. Nis Bertelsen & Brian Vad Mathiesen, 2020. "EU-28 Residential Heat Supply and Consumption: Historical Development and Status," Energies, MDPI, vol. 13(8), pages 1-21, April.
    16. 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.
    17. Nageler, P. & Zahrer, G. & Heimrath, R. & Mach, T. & Mauthner, F. & Leusbrock, I. & Schranzhofer, H. & Hochenauer, C., 2017. "Novel validated method for GIS based automated dynamic urban building energy simulations," Energy, Elsevier, vol. 139(C), pages 142-154.
    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. Jan Stock & André Xhonneux & Dirk Müller, 2022. "Framework for the Automated Identification of Possible District Heating Separations to Utilise Present Heat Sources Based on Existing Network Topology," Energies, MDPI, vol. 15(21), pages 1-31, November.

    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. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    2. 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.
    3. 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.
    4. Meibodi, Saleh S. & Loveridge, Fleur, 2022. "The future role of energy geostructures in fifth generation district heating and cooling networks," Energy, Elsevier, vol. 240(C).
    5. 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).
    6. 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).
    7. 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.
    8. 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).
    9. Zhou, Suyang & Chen, Jinyi & Gu, Wei & Fang, Xin & Yuan, Xiaodong, 2023. "An adaptive space-step simulation approach for steam heating network considering condensate loss," Energy, Elsevier, vol. 263(PA).
    10. Sommer, Tobias & Sotnikov, Artem & Sulzer, Matthias & Scholz, Volkher & Mischler, Stefan & Rismanchi, Behzad & Gjoka, Kristian & Mennel, Stefan, 2022. "Hydrothermal challenges in low-temperature networks with distributed heat pumps," Energy, Elsevier, vol. 257(C).
    11. Petrović, Stefan & Bühler, Fabian & Radoman, Uroš & McKenna, Russell, 2022. "Power transformers as excess heat sources – a case study for Denmark," Energy, Elsevier, vol. 239(PE).
    12. Gianni Martinazzoli & Daniele Pasinelli & Adriano Maria Lezzi & Mariagrazia Pilotelli, 2023. "Design of a 5th Generation District Heating Substation Prototype for a Real Case Study," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    13. Salenbien, R. & Wack, Y. & Baelmans, M. & Blommaert, M., 2023. "Geographically informed automated non-linear topology optimization of district heating networks," Energy, Elsevier, vol. 283(C).
    14. Gjoka, Kristian & Rismanchi, Behzad & Crawford, Robert H., 2023. "Fifth-generation district heating and cooling systems: A review of recent advancements and implementation barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    15. Damir Požgaj & Branimir Pavković & Boris Delač & Vladimir Glažar, 2023. "Retrofitting of the District Heating System Based on the Application of Heat Pumps Operating with Natural Refrigerants," Energies, MDPI, vol. 16(4), pages 1-28, February.
    16. Chicherin, Stanislav & Zhuikov, Andrey & Junussova, Lyazzat, 2022. "The new method for hydraulic calculations of a district heating (DH) network," Energy, Elsevier, vol. 260(C).
    17. Manz, Pia & Billerbeck, Anna & Kök, Ali & Fallahnejad, Mostafa & Fleiter, Tobias & Kranzl, Lukas & Braungardt, Sibylle & Eichhammer, Wolfgang, 2024. "Spatial analysis of renewable and excess heat potentials for climate-neutral district heating in Europe," Renewable Energy, Elsevier, vol. 224(C).
    18. 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).
    19. Persson, Urban & Wiechers, Eva & Möller, Bernd & Werner, Sven, 2019. "Heat Roadmap Europe: Heat distribution costs," Energy, Elsevier, vol. 176(C), pages 604-622.
    20. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

    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:15:y:2022:i:12:p:4372-:d:839496. 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.