IDEAS home Printed from https://ideas.repec.org/a/ksa/szemle/2234.html
   My bibliography  Save this article

A kisvárosi, megújuló energiára épülő távhő versenyképességének vizsgálata közgazdasági modellezéssel
[Economic modelling of the competitiveness of small urban renewable district heating]

Author

Listed:
  • Mezősi, András
  • Kerekes, Lajos

Abstract

A dekarbonizáció egyik fontos területe a fűtési szektor, azon belül is a távfűtés kar bon mentes termelésre való átállítása. Kutatásunkban arra keressük a választ, hogy Magyarországon, kisvárosi környezetben megvalósuló, megújuló energiára épülő távhőszolgáltatási rendszer milyen költségszinten lenne képes távhőt szolgáltatni. Ehhez egy általunk készített közgazdasági modellt használunk, amelyet három településre is alkalmaztunk. Elemzésünk unikális abból a szempontból, hogy integráltan vizsgálja a távhőhálózat bővítését és a különböző távhőtermelési technológiákat. A kutatás során megállapítottuk, hogy a megújulók konszolidáltabb gázárak mellett is közel vannak a versenyképességhez; alacsony fogyasztási mennyiség esetében a biomassza, magasabb fogyasztás esetében a geotermia is versenyképes lehet a földgáztüzeléssel szemben. A hőszivattyúk a referenciaesetben csak minimális szinten jelennek meg, ugyanakkor alacsonyabb áramár esetében e technológia jelentős elterjedését figyelhetjük meg: ez elsősorban alacsonyabb távhőfogyasztás esetében érvényesül. A napkollektorparkok egyik forgatókönyvben sem jelennek meg domináns technológiaként, ugyanakkor kis méretben kiegészítő jelleggel működhetnek.

Suggested Citation

  • Mezősi, András & Kerekes, Lajos, 2025. "A kisvárosi, megújuló energiára épülő távhő versenyképességének vizsgálata közgazdasági modellezéssel [Economic modelling of the competitiveness of small urban renewable district heating]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 178-202.
    • Handle: RePEc:ksa:szemle:2234
    DOI: 10.18414/KSZ.2025.2.178
    as

    Download full text from publisher

    File URL: http://www.kszemle.hu/tartalom/letoltes.php?id=2234
    Download Restriction: Registration and subscription. 3-month embargo period to non-subscribers.
    File URL: https://libkey.io/10.18414/KSZ.2025.2.178?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. Reidhav, Charlotte & Werner, Sven, 2008. "Profitability of sparse district heating," Applied Energy, Elsevier, vol. 85(9), pages 867-877, September.
    2. Mezősi, András & Kácsor, Enikő & Diallo, Alfa, 2023. "Projects of common interest? Evaluation of European electricity interconnectors," Utilities Policy, Elsevier, vol. 84(C).
    3. Lund, Rasmus & Persson, Urban, 2016. "Mapping of potential heat sources for heat pumps for district heating in Denmark," Energy, Elsevier, vol. 110(C), pages 129-138.
    4. Jalil-Vega, Francisca & Hawkes, Adam D., 2018. "The effect of spatial resolution on outcomes from energy systems modelling of heat decarbonisation," Energy, Elsevier, vol. 155(C), pages 339-350.
    5. Nielsen, Steffen & Möller, Bernd, 2013. "GIS based analysis of future district heating potential in Denmark," Energy, Elsevier, vol. 57(C), pages 458-468.
    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. Bühler, Fabian & Petrović, Stefan & Karlsson, Kenneth & Elmegaard, Brian, 2017. "Industrial excess heat for district heating in Denmark," Applied Energy, Elsevier, vol. 205(C), pages 991-1001.
    2. Sachs, Julia & Moya, Diego & Giarola, Sara & Hawkes, Adam, 2019. "Clustered spatially and temporally resolved global heat and cooling energy demand in the residential sector," Applied Energy, Elsevier, vol. 250(C), pages 48-62.
    3. Unternährer, Jérémy & Moret, Stefano & Joost, Stéphane & Maréchal, François, 2017. "Spatial clustering for district heating integration in urban energy systems: Application to geothermal energy," Applied Energy, Elsevier, vol. 190(C), pages 749-763.
    4. Stegnar, Gašper & Staničić, D. & Česen, M. & Čižman, J. & Pestotnik, S. & Prestor, J. & Urbančič, A. & Merše, S., 2019. "A framework for assessing the technical and economic potential of shallow geothermal energy in individual and district heating systems: A case study of Slovenia," Energy, Elsevier, vol. 180(C), pages 405-420.
    5. 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.
    6. 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.
    7. Fabian Bühler & Stefan Petrović & Torben Ommen & Fridolin Müller Holm & Henrik Pieper & Brian Elmegaard, 2018. "Identification and Evaluation of Cases for Excess Heat Utilisation Using GIS," Energies, MDPI, vol. 11(4), pages 1-24, March.
    8. Leurent, Martin & Da Costa, Pascal & Rämä, Miika & Persson, Urban & Jasserand, Frédéric, 2018. "Cost-benefit analysis of district heating systems using heat from nuclear plants in seven European countries," Energy, Elsevier, vol. 149(C), pages 454-472.
    9. Averfalk, Helge & Ingvarsson, Paul & Persson, Urban & Gong, Mei & Werner, Sven, 2017. "Large heat pumps in Swedish district heating systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1275-1284.
    10. Bachmann, Max & Kriegel, Martin, 2023. "Assessing the heat distribution costs of linear and radial district heating networks: A methodological approach," Energy, Elsevier, vol. 276(C).
    11. Andreas Müller & Marcus Hummel & Lukas Kranzl & Mostafa Fallahnejad & Richard Büchele, 2019. "Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28," Energies, MDPI, vol. 12(24), pages 1-25, December.
    12. Bühler, Fabian & Petrović, Stefan & Holm, Fridolin Müller & Karlsson, Kenneth & Elmegaard, Brian, 2018. "Spatiotemporal and economic analysis of industrial excess heat as a resource for district heating," Energy, Elsevier, vol. 151(C), pages 715-728.
    13. Giulia Spirito & Alice Dénarié & Fabrizio Fattori & Mario Motta & Samuel Macchi & Urban Persson, 2021. "Potential Diffusion of Renewables-Based DH Assessment through Clustering and Mapping: A Case Study in Milano," Energies, MDPI, vol. 14(9), pages 1-30, May.
    14. Ben Amer-Allam, Sara & Münster, Marie & Petrović, Stefan, 2017. "Scenarios for sustainable heat supply and heat savings in municipalities - The case of Helsingør, Denmark," Energy, Elsevier, vol. 137(C), pages 1252-1263.
    15. Novosel, T. & Pukšec, T. & Duić, N. & Domac, J., 2020. "Heat demand mapping and district heating assessment in data-pour areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    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. Hyunkyo Yu & Erik O. Ahlgren, 2023. "Enhancing Urban Heating Systems Planning through Spatially Explicit Participatory Modeling," Energies, MDPI, vol. 16(11), pages 1-26, May.
    18. Leurent, Martin, 2019. "Analysis of the district heating potential in French regions using a geographic information system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    19. Persson, U. & Möller, B. & Werner, S., 2014. "Heat Roadmap Europe: Identifying strategic heat synergy regions," Energy Policy, Elsevier, vol. 74(C), pages 663-681.
    20. Nielsen, Steffen, 2014. "A geographic method for high resolution spatial heat planning," Energy, Elsevier, vol. 67(C), pages 351-362.

    More about this item

    JEL classification:

    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    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:ksa:szemle:2234. 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: Odon Sok The email address of this maintainer does not seem to be valid anymore. Please ask Odon Sok to update the entry or send us the correct address (email available below). General contact details of provider: http://www.kszemle.hu .

    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.