IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v280y2020ics0306261920314653.html
   My bibliography  Save this article

An adjoint optimization approach for the topological design of large-scale district heating networks based on nonlinear models

Author

Listed:
  • Blommaert, Maarten
  • Wack, Y.
  • Baelmans, M.

Abstract

This article deals with the problem of finding the best topology, pipe diameter choices, and operation parameters for realistic district heating networks. Present design tools that employ non-linear flow and heat transport models for topological design are limited to small heating networks with up to 20 potential consumers. We introduce an alternative adjoint-based numerical optimization strategy to enable large-scale nonlinear thermal network optimization. In order to avoid a strong computational cost scaling with the network size, we aggregate consumer constraints with a constraint aggregation strategy. Moreover, to align this continuous optimization strategy with the discrete nature of topology optimization and pipe size choices, we present a numerical continuation strategy that gradually forces the design variables towards discrete design choices. As such, optimal network topology and pipe sizes are determined simultaneously. Finally, we demonstrate the scalability of the algorithm by designing a fictitious district heating network with 160 consumers. As a proof-of-concept, the network is optimized for minimal investment cost and pumping power, while keeping the heat supplied to the consumers within a thermal comfort range of 5%. Starting from a uniform distribution of 15 cm wide piping throughout the network, the novel algorithm finds a network lay-out that reduces piping investment by 23% and pump-related costs by a factor of 14 in less than an hour on a standard laptop. Moreover, the importance of embedding the non-linear transport model is clear from a temperature-induced variation in the consumer flow rates of 72%.

Suggested Citation

  • Blommaert, Maarten & Wack, Y. & Baelmans, M., 2020. "An adjoint optimization approach for the topological design of large-scale district heating networks based on nonlinear models," Applied Energy, Elsevier, vol. 280(C).
  • Handle: RePEc:eee:appene:v:280:y:2020:i:c:s0306261920314653
    DOI: 10.1016/j.apenergy.2020.116025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920314653
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2020.116025?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. Weinand, Jann Michael & Kleinebrahm, Max & McKenna, Russell & Mainzer, Kai & Fichtner, Wolf, 2019. "Developing a combinatorial optimisation approach to design district heating networks based on deep geothermal energy," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    3. 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.
    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. Bordin, Chiara & Gordini, Angelo & Vigo, Daniele, 2016. "An optimization approach for district heating strategic network design," European Journal of Operational Research, Elsevier, vol. 252(1), pages 296-307.
    6. Deng, Na & Cai, Rongchang & Gao, Yuan & Zhou, Zhihua & He, Guansong & Liu, Dongyi & Zhang, Awen, 2017. "A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin," Energy, Elsevier, vol. 141(C), pages 1750-1763.
    7. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    8. Werner, Sven, 2017. "International review of district heating and cooling," Energy, Elsevier, vol. 137(C), pages 617-631.
    9. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    10. Marty, Fabien & Serra, Sylvain & Sochard, Sabine & Reneaume, Jean-Michel, 2018. "Simultaneous optimization of the district heating network topology and the Organic Rankine Cycle sizing of a geothermal plant," Energy, Elsevier, vol. 159(C), pages 1060-1074.
    11. Persson, U. & Möller, B. & Werner, S., 2014. "Heat Roadmap Europe: Identifying strategic heat synergy regions," Energy Policy, Elsevier, vol. 74(C), pages 663-681.
    12. Mertz, Théophile & Serra, Sylvain & Henon, Aurélien & Reneaume, Jean-Michel, 2016. "A MINLP optimization of the configuration and the design of a district heating network: Academic study cases," Energy, Elsevier, vol. 117(P2), pages 450-464.
    13. Merkert, Lennart & Listmann, Kim & Hohmann, Sören, 2019. "Optimization of thermo-hydraulic systems using multiparametric delay modeling," Energy, Elsevier, vol. 189(C).
    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. Wack, Yannick & Baelmans, Martine & Salenbien, Robbe & Blommaert, Maarten, 2023. "Economic topology optimization of District Heating Networks using a pipe penalization approach," Energy, Elsevier, vol. 264(C).
    2. Merlet, Yannis & Baviere, Roland & Vasset, Nicolas, 2022. "Formulation and assessment of multi-objective optimal sizing of district heating network," Energy, Elsevier, vol. 252(C).
    3. Wack, Yannick & Serra, Sylvain & Baelmans, Martine & Reneaume, Jean-Michel & Blommaert, Maarten, 2023. "Nonlinear topology optimization of District Heating Networks: A benchmark of a mixed-integer and a density-based approach," Energy, Elsevier, vol. 278(PB).
    4. Piotr Pałka & Marcin Malec & Przemysław Kaszyński & Jacek Kamiński & Piotr Saługa, 2023. "District Heating System Optimisation: A Three-Phase Thermo-Hydraulic Linear Model," Energies, MDPI, vol. 16(8), pages 1-18, April.
    5. 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).
    6. Merlet, Yannis & Baviere, Roland & Vasset, Nicolas, 2023. "Optimal retrofit of district heating network to lower temperature levels," Energy, Elsevier, vol. 282(C).
    7. 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.
    8. 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).
    9. 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).

    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. 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).
    2. Kazagic, Anes & Merzic, Ajla & Redzic, Elma & Tresnjo, Dino, 2019. "Optimization of modular district heating solution based on CHP and RES - Demonstration case of the Municipality of Visoko," Energy, Elsevier, vol. 181(C), pages 56-65.
    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. Simeoni, Patrizia & Ciotti, Gellio & Cottes, Mattia & Meneghetti, Antonella, 2019. "Integrating industrial waste heat recovery into sustainable smart energy systems," Energy, Elsevier, vol. 175(C), pages 941-951.
    5. 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).
    6. Wack, Yannick & Baelmans, Martine & Salenbien, Robbe & Blommaert, Maarten, 2023. "Economic topology optimization of District Heating Networks using a pipe penalization approach," Energy, Elsevier, vol. 264(C).
    7. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    8. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
    9. 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.
    10. Wack, Yannick & Serra, Sylvain & Baelmans, Martine & Reneaume, Jean-Michel & Blommaert, Maarten, 2023. "Nonlinear topology optimization of District Heating Networks: A benchmark of a mixed-integer and a density-based approach," Energy, Elsevier, vol. 278(PB).
    11. Régis Delubac & Sylvain Serra & Sabine Sochard & Jean-Michel Reneaume, 2021. "A Dynamic Optimization Tool to Size and Operate Solar Thermal District Heating Networks Production Plants," Energies, MDPI, vol. 14(23), pages 1-27, November.
    12. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    13. Persson, Urban & Wiechers, Eva & Möller, Bernd & Werner, Sven, 2019. "Heat Roadmap Europe: Heat distribution costs," Energy, Elsevier, vol. 176(C), pages 604-622.
    14. Rämä, Miika & Wahlroos, Mikko, 2018. "Introduction of new decentralised renewable heat supply in an existing district heating system," Energy, Elsevier, vol. 154(C), pages 68-79.
    15. Chambers, Jonathan & Narula, Kapil & Sulzer, Matthias & Patel, Martin K., 2019. "Mapping district heating potential under evolving thermal demand scenarios and technologies: A case study for Switzerland," Energy, Elsevier, vol. 176(C), pages 682-692.
    16. Fritz, M. & Plötz, P. & Schebek, L., 2022. "A technical and economical comparison of excess heat transport technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    17. Østergaard, Poul Alberg & Andersen, Anders N., 2018. "Economic feasibility of booster heat pumps in heat pump-based district heating systems," Energy, Elsevier, vol. 155(C), pages 921-929.
    18. Lumbreras, Mikel & Garay-Martinez, Roberto & Arregi, Beñat & Martin-Escudero, Koldobika & Diarce, Gonzalo & Raud, Margus & Hagu, Indrek, 2022. "Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters," Energy, Elsevier, vol. 239(PD).
    19. Badami, Marco & Fonti, Antonio & Carpignano, Andrea & Grosso, Daniele, 2018. "Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach," Energy, Elsevier, vol. 144(C), pages 826-838.
    20. Im, Yong-Hoon & Liu, Jie, 2018. "Feasibility study on the low temperature district heating and cooling system with bi-lateral heat trades model," Energy, Elsevier, vol. 153(C), pages 988-999.

    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:appene:v:280:y:2020:i:c:s0306261920314653. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.