IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v324y2022ics0306261922009734.html
   My bibliography  Save this article

Technology pathways for industrial cogeneration systems: Optimal investment planning considering long-term trends

Author

Listed:
  • Hoettecke, Lukas
  • Schuetz, Thomas
  • Thiem, Sebastian
  • Niessen, Stefan

Abstract

Cogeneration plants appear highly attractive for industrial companies as production sites typically combine demands for electricity, heating, and cooling. However, gas-fired cogeneration might become economically less attractive with further increasing carbon prices and companies’ commitment to decarbonization targets. This paper proposes a methodology to determine technology pathways from an optimization model. Technology pathways describe the evolution of an energy supply system over a multi-decade planning horizon. Therefore, projected long-term trends are integrated into the decision-making process for energy supply infrastructure. Three investment strategies are compared regarding their accuracy and computational complexity. The methodology is illustrated for industrial sites from dairy, pharmaceutical and automotive industry in Southern Germany. Results highlight the advantages of technology pathways compared to optimization approaches based on a representative year. A strategic planning approach identifies optimal decarbonization pathways with economic saving potentials of up to 20 %. For most of the considered case studies, a sequential decision approach with a rolling horizon heuristic yields similar results in 89 % less solving time.

Suggested Citation

  • Hoettecke, Lukas & Schuetz, Thomas & Thiem, Sebastian & Niessen, Stefan, 2022. "Technology pathways for industrial cogeneration systems: Optimal investment planning considering long-term trends," Applied Energy, Elsevier, vol. 324(C).
  • Handle: RePEc:eee:appene:v:324:y:2022:i:c:s0306261922009734
    DOI: 10.1016/j.apenergy.2022.119675
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922009734
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.119675?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. Stadler, Michael & Cardoso, Gonçalo & Mashayekh, Salman & Forget, Thibault & DeForest, Nicholas & Agarwal, Ankit & Schönbein, Anna, 2016. "Value streams in microgrids: A literature review," Applied Energy, Elsevier, vol. 162(C), pages 980-989.
    2. Pecenak, Zachary K. & Stadler, Michael & Fahy, Kelsey, 2019. "Efficient multi-year economic energy planning in microgrids," Applied Energy, Elsevier, vol. 255(C).
    3. Philipp, Matthias & Schumm, Gregor & Peesel, Ron-Hendrik & Walmsley, Timothy G. & Atkins, Martin J. & Schlosser, Florian & Hesselbach, Jens, 2018. "Optimal energy supply structures for industrial food processing sites in different countries considering energy transitions," Energy, Elsevier, vol. 146(C), pages 112-123.
    4. Wallerand, Anna S. & Kermani, Maziar & Kantor, Ivan & Maréchal, François, 2018. "Optimal heat pump integration in industrial processes," Applied Energy, Elsevier, vol. 219(C), pages 68-92.
    5. Thiem, Sebastian & Danov, Vladimir & Metzger, Michael & Schäfer, Jochen & Hamacher, Thomas, 2017. "Project-level multi-modal energy system design - Novel approach for considering detailed component models and example case study for airports," Energy, Elsevier, vol. 133(C), pages 691-709.
    6. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    7. Prina, Matteo Giacomo & Lionetti, Matteo & Manzolini, Giampaolo & Sparber, Wolfram & Moser, David, 2019. "Transition pathways optimization methodology through EnergyPLAN software for long-term energy planning," Applied Energy, Elsevier, vol. 235(C), pages 356-368.
    8. Bohlayer, Markus & Bürger, Adrian & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2021. "Multi-period investment pathways - Modeling approaches to design distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 285(C).
    9. Mavromatidis, Georgios & Petkov, Ivalin, 2021. "MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems," Applied Energy, Elsevier, vol. 288(C).
    10. Trotter, Philipp A. & Cooper, Nathanial J. & Wilson, Peter R., 2019. "A multi-criteria, long-term energy planning optimisation model with integrated on-grid and off-grid electrification – The case of Uganda," Applied Energy, Elsevier, vol. 243(C), pages 288-312.
    11. Wei, Jingdong & Zhang, Yao & Wang, Jianxue & Cao, Xiaoyu & Khan, Muhammad Armoghan, 2020. "Multi-period planning of multi-energy microgrid with multi-type uncertainties using chance constrained information gap decision method," Applied Energy, Elsevier, vol. 260(C).
    12. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    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. Yutong Zhao & Shuang Zeng & Yifeng Ding & Lin Ma & Zhao Wang & Anqi Liang & Hongbo Ren, 2024. "Cost–Benefit Analysis of Distributed Energy Systems Considering the Monetization of Indirect Benefits," Sustainability, MDPI, vol. 16(2), pages 1-14, January.

    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. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
    2. 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).
    3. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2021. "Energy equipment sizing and operation optimisation for prosumer industrial SMEs – A lifetime approach," Applied Energy, Elsevier, vol. 299(C).
    4. Richarz, Jan & Henn, Sarah & Osterhage, Tanja & Müller, Dirk, 2022. "Optimal scheduling of modernization measures for typical non-residential buildings," Energy, Elsevier, vol. 238(PA).
    5. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    6. Gorman, Nicholas & MacGill, Iain & Bruce, Anna, 2024. "Re-dispatch simplification analysis: Confirmation holism and assessing the impact of simplifications on energy system model performance," Applied Energy, Elsevier, vol. 365(C).
    7. Costa, Alberto & Ng, Tsan Sheng & Su, Bin, 2023. "Long-term solar PV planning: An economic-driven robust optimization approach," Applied Energy, Elsevier, vol. 335(C).
    8. Blanco, Herib & Leaver, Jonathan & Dodds, Paul E. & Dickinson, Robert & García-Gusano, Diego & Iribarren, Diego & Lind, Arne & Wang, Changlong & Danebergs, Janis & Baumann, Martin, 2022. "A taxonomy of models for investigating hydrogen energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    9. Kamila Svobodova & John R. Owen & Deanna Kemp & Vítězslav Moudrý & Éléonore Lèbre & Martin Stringer & Benjamin K. Sovacool, 2022. "Decarbonization, population disruption and resource inventories in the global energy transition," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    10. Yuan, Meng & Sorknæs, Peter & Lund, Henrik & Liang, Yongtu, 2022. "The bidding strategies of large-scale battery storage in 100% renewable smart energy systems," Applied Energy, Elsevier, vol. 326(C).
    11. Ekaterina Rhodes & Kira Craig & Aaron Hoyle & Madeleine McPherson, 2021. "How Do Energy-Economy Models Compare? A Survey of Model Developers and Users in Canada," Sustainability, MDPI, vol. 13(11), pages 1-39, May.
    12. Mavromatidis, Georgios & Petkov, Ivalin, 2021. "MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems," Applied Energy, Elsevier, vol. 288(C).
    13. Chicombo, Adélia Filosa Francisco & Musango, Josephine Kaviti, 2024. "Urban households energy transition pathways: A gendered perspective regarding Mozambique," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    14. Marrero-Trujillo, Verónica & Arias-Gaviria, Jessica & Arango-Aramburo, Santiago & Larsen, Erik R., 2023. "Gamification model for communicating and evaluating renewable energy planning," Utilities Policy, Elsevier, vol. 84(C).
    15. Schlosser, F. & Jesper, M. & Vogelsang, J. & Walmsley, T.G. & Arpagaus, C. & Hesselbach, J., 2020. "Large-scale heat pumps: Applications, performance, economic feasibility and industrial integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    16. Sacha Hodencq & Mathieu Brugeron & Jaume Fitó & Lou Morriet & Benoit Delinchant & Frédéric Wurtz, 2021. "OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale," Energies, MDPI, vol. 14(18), pages 1-30, September.
    17. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2022. "Risk assessment of energy investment in the industrial framework – Uncertainty and Sensitivity Analysis for energy design and operation optimisation," Energy, Elsevier, vol. 239(PA).
    18. Plazas-Niño, F.A. & Ortiz-Pimiento, N.R. & Montes-Páez, E.G., 2022. "National energy system optimization modelling for decarbonization pathways analysis: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    19. Limpens, Gauthier & Rixhon, Xavier & Contino, Francesco & Jeanmart, Hervé, 2024. "EnergyScope Pathway: An open-source model to optimise the energy transition pathways of a regional whole-energy system," Applied Energy, Elsevier, vol. 358(C).
    20. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).

    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:324:y:2022:i:c:s0306261922009734. 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.