IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v209y2020ics0360544220315176.html
   My bibliography  Save this article

Enabling large-scale dynamic simulations and reducing model complexity of district heating and cooling systems by aggregation

Author

Listed:
  • Falay, Basak
  • Schweiger, Gerald
  • O’Donovan, Keith
  • Leusbrock, Ingo

Abstract

District heating and cooling (DHC) systems are considered cornerstones of a future heat and cold supply due to their ability to integrate renewable and waste heat sources as well as long and short-term storage technologies and their flexibility for integration of other infrastructures. Therefore, DHC systems may represent the central hub of an interlinked overall energy system. These options nevertheless lead to a more complex system if implemented as the number of technical components and potential interactions increase and as the energy demands on the network grow. The transportation of the heat supplied to the consumers through water flow involves both time and temperature-dependent changes based on the mass flow rates and the heat losses to the surrounding from the pipes. The dynamic properties of the consumers and the distribution pipes strongly influence the operation of the district heating systems. Dynamic modeling tools are required to cope with the increasing complexities and to optimize the operation of the DHC systems by using the knowledge of time delay in the heat transport, temperature distribution and flow characteristics. Nevertheless, it is computationally challenging to simulate large-scale DHC networks dynamically. One proposed method for improvement in this context is aggregation, which simplifies the topological complexities of the original network by reducing the number of pipe junctions (branches) and pipes. This paper focuses on the analysis and evaluation of the application of two aggregation methods, the Danish and the German method, in a dynamic modelling environment and comparing the aggregation to the monitoring data of a virtual district heating network with 146 consumers and an existing district heating network with 66 consumers. These evaluations are based on comparison of the simulation results of the aggregated network with fewer consumers than the original network in terms of accuracy, information loss and computational time. The results show that the CPU time in the simulation of this network can speed up approximately more than 95% by aggregating the network down to 3 consumers without significant information loss. We will highlight the current potentials and limitations of both aggregation methods in terms of integrating them in the planning, modelling and operation of DHC systems, including the 4th generation district heating systems.

Suggested Citation

  • Falay, Basak & Schweiger, Gerald & O’Donovan, Keith & Leusbrock, Ingo, 2020. "Enabling large-scale dynamic simulations and reducing model complexity of district heating and cooling systems by aggregation," Energy, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:energy:v:209:y:2020:i:c:s0360544220315176
    DOI: 10.1016/j.energy.2020.118410
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220315176
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.118410?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. Popovski, Eftim & Aydemir, Ali & Fleiter, Tobias & Bellstädt, Daniel & Büchele, Richard & Steinbach, Jan, 2019. "The role and costs of large-scale heat pumps in decarbonising existing district heating networks – A case study for the city of Herten in Germany," Energy, Elsevier, vol. 180(C), pages 918-933.
    2. Schweiger, Gerald & Heimrath, Richard & Falay, Basak & O'Donovan, Keith & Nageler, Peter & Pertschy, Reinhard & Engel, Georg & Streicher, Wolfgang & Leusbrock, Ingo, 2018. "District energy systems: Modelling paradigms and general-purpose tools," Energy, Elsevier, vol. 164(C), pages 1326-1340.
    3. 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.
    4. Gerald Schweiger & Fabian Kuttin & Alfred Posch, 2019. "District Heating Systems: An Analysis of Strengths, Weaknesses, Opportunities, and Threats of the 4GDH," Energies, MDPI, vol. 12(24), pages 1-15, December.
    5. Tunzi, Michele & Østergaard, Dorte Skaarup & Svendsen, Svend & Boukhanouf, Rabah & Cooper, Edward, 2016. "Method to investigate and plan the application of low temperature district heating to existing hydraulic radiator systems in existing buildings," Energy, Elsevier, vol. 113(C), pages 413-421.
    6. Schweiger, G. & Nilsson, H. & Schoeggl, J. & Birk, W. & Posch, A., 2020. "Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    7. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
    8. Nord, Natasa & Løve Nielsen, Elise Kristine & Kauko, Hanne & Tereshchenko, Tymofii, 2018. "Challenges and potentials for low-temperature district heating implementation in Norway," Energy, Elsevier, vol. 151(C), pages 889-902.
    9. 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.
    10. 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.
    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. Hirsch, Hauke & Nicolai, Andreas, 2022. "An efficient numerical solution method for detailed modelling of large 5th generation district heating and cooling networks," Energy, Elsevier, vol. 255(C).
    2. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Optimisation modelling tools and solving techniques for integrated precinct-scale energy–water system planning," Applied Energy, Elsevier, vol. 318(C).
    3. Nielsen, Tore Bach & Lund, Henrik & Østergaard, Poul Alberg & Duic, Neven & Mathiesen, Brian Vad, 2021. "Perspectives on energy efficiency and smart energy systems from the 5th SESAAU2019 conference," Energy, Elsevier, vol. 216(C).
    4. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    5. Johan Simonsson & Khalid Tourkey Atta & Gerald Schweiger & Wolfgang Birk, 2021. "Experiences from City-Scale Simulation of Thermal Grids," Resources, MDPI, vol. 10(2), pages 1-20, January.
    6. 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).
    7. Chicherin, Stanislav & Anvari-Moghaddam, Amjad, 2021. "Adjusting heat demands using the operational data of district heating systems," Energy, Elsevier, vol. 235(C).
    8. Chicherin, Stanislav & Starikov, Aleksander & Zhuikov, Andrey, 2022. "Justifying network reconstruction when switching to low temperature district heating," Energy, Elsevier, vol. 248(C).
    9. Boussaid, Taha & Rousset, François & Scuturici, Vasile-Marian & Clausse, Marc, 2024. "Enabling fast prediction of district heating networks transients via a physics-guided graph neural network," Applied Energy, Elsevier, vol. 370(C).
    10. Yang, Miao & Ding, Tao & Chang, Xinyue & Xue, Yixun & Ge, Huaichang & Jia, Wenhao & Du, Sijun & Zhang, Hongji, 2024. "Analysis of equivalent energy storage for integrated electricity-heat system," Energy, Elsevier, vol. 303(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. Gerald Schweiger & Fabian Kuttin & Alfred Posch, 2019. "District Heating Systems: An Analysis of Strengths, Weaknesses, Opportunities, and Threats of the 4GDH," Energies, MDPI, vol. 12(24), pages 1-15, December.
    2. Østergaard, Dorte Skaarup & Tunzi, Michele & Svendsen, Svend, 2021. "What does a well-functioning heating system look like? Investigation of ten Danish buildings that utilize district heating efficiently," Energy, Elsevier, vol. 227(C).
    3. Benakopoulos, Theofanis & Tunzi, Michele & Salenbien, Robbe & Svendsen, Svend, 2021. "Strategy for low-temperature operation of radiator systems using data from existing digital heat cost allocators," Energy, Elsevier, vol. 231(C).
    4. Tunzi, Michele & Benakopoulos, Theofanis & Yang, Qinjiang & Svendsen, Svend, 2023. "Demand side digitalisation: A methodology using heat cost allocators and energy meters to secure low-temperature operations in existing buildings connected to district heating networks," Energy, Elsevier, vol. 264(C).
    5. Benakopoulos, Theofanis & Tunzi, Michele & Salenbien, Robbe & Hansen, Kasper Klan & Svendsen, Svend, 2022. "Implementation of a strategy for low-temperature operation of radiator systems using data from existing digital heat cost allocators," Energy, Elsevier, vol. 251(C).
    6. 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).
    7. Theofanis Benakopoulos & William Vergo & Michele Tunzi & Robbe Salenbien & Svend Svendsen, 2021. "Overview of Solutions for the Low-Temperature Operation of Domestic Hot-Water Systems with a Circulation Loop," Energies, MDPI, vol. 14(11), pages 1-25, June.
    8. 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.
    9. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Accounting for pipeline thermal capacity in district heating simulations," Energy, Elsevier, vol. 219(C).
    10. Li, Haoran & Hou, Juan & Hong, Tianzhen & Nord, Natasa, 2022. "Distinguish between the economic optimal and lowest distribution temperatures for heat-prosumer-based district heating systems with short-term thermal energy storage," Energy, Elsevier, vol. 248(C).
    11. Persson, Urban & Wiechers, Eva & Möller, Bernd & Werner, Sven, 2019. "Heat Roadmap Europe: Heat distribution costs," Energy, Elsevier, vol. 176(C), pages 604-622.
    12. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    13. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    14. Michael-Allan Millar & Bruce Elrick & Greg Jones & Zhibin Yu & Neil M. Burnside, 2020. "Roadblocks to Low Temperature District Heating," Energies, MDPI, vol. 13(22), pages 1-21, November.
    15. Theofanis Benakopoulos & Robbe Salenbien & Dirk Vanhoudt & Svend Svendsen, 2019. "Improved Control of Radiator Heating Systems with Thermostatic Radiator Valves without Pre-Setting Function," Energies, MDPI, vol. 12(17), pages 1-24, August.
    16. Averfalk, Helge & Werner, Sven, 2020. "Economic benefits of fourth generation district heating," Energy, Elsevier, vol. 193(C).
    17. Øystein Rønneseth & Nina Holck Sandberg & Igor Sartori, 2019. "Is It Possible to Supply Norwegian Apartment Blocks with 4th Generation District Heating?," Energies, MDPI, vol. 12(5), pages 1-19, March.
    18. Guelpa, E. & Capone, M. & Sciacovelli, A. & Vasset, N. & Baviere, R. & Verda, V., 2023. "Reduction of supply temperature in existing district heating: A review of strategies and implementations," Energy, Elsevier, vol. 262(PB).
    19. Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).
    20. Alessandro Guzzini & Marco Pellegrini & Edoardo Pelliconi & Cesare Saccani, 2020. "Low Temperature District Heating: An Expert Opinion Survey," Energies, MDPI, vol. 13(4), pages 1-34, February.

    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:209:y:2020:i:c:s0360544220315176. 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.