IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2502.12035.html

Planning minimum regret $CO_2$ pipeline networks

Author

Listed:
  • Stephan Bogs
  • Ali Abdelshafy
  • Grit Walther

Abstract

The transition to a low-carbon economy necessitates effective carbon capture and storage (CCS) solutions, particularly for hard-to-abate sectors. Herein, pipeline networks are indispensable for cost-efficient $CO_2$ transportation over long distances. However, there is deep uncertainty regarding which industrial sectors will participate in such systems. This poses a significant challenge due to substantial investments as well as the lengthy planning and development timelines required for $CO_2$ pipeline projects, which are further constrained by limited upgrade options for already built infrastructure. The economies of scale inherent in pipeline construction exacerbate these challenges, leading to potential regret over earlier decisions. While numerous models were developed to optimize the initial layout of pipeline infrastructure based on known demand, a gap exists in addressing the incremental development of infrastructure in conjunction with deep uncertainty. Hence, this paper introduces a novel optimization model for $CO_2$ pipeline infrastructure development, minimizing regret as its objective function and incorporating various upgrade options, such as looping and pressure increases. The model's effectiveness is also demonstrated by presenting a comprehensive case study of Germany's cement and lime industries. The developed approach quantitatively illustrates the trade-off between different options, which can help in deriving effective strategies for $CO_2$ infrastructure development.

Suggested Citation

  • Stephan Bogs & Ali Abdelshafy & Grit Walther, 2025. "Planning minimum regret $CO_2$ pipeline networks," Papers 2502.12035, arXiv.org.
    • Handle: RePEc:arx:papers:2502.12035
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2502.12035
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Liang & Chen, Wenying, 2017. "Development and application of a multi-stage CCUS source–sink matching model," Applied Energy, Elsevier, vol. 185(P2), pages 1424-1432.
    2. Abdoli, B. & Hooshmand, F. & MirHassani, S.A., 2023. "A novel stochastic programming model under endogenous uncertainty for the CCS-EOR planning problem," Applied Energy, Elsevier, vol. 338(C).
    3. Nicolle, Adrien & Massol, Olivier, 2023. "Build more and regret less: Oversizing H2 and CCS pipeline systems under uncertainty," Energy Policy, Elsevier, vol. 179(C).
    4. Christopher Yeates & Cornelia Schmidt-Hattenberger & Wolfgang Weinzierl & David Bruhn, 2021. "Heuristic Methods for Minimum-Cost Pipeline Network Design – a Node Valency Transfer Metaheuristic," Networks and Spatial Economics, Springer, vol. 21(4), pages 839-871, December.
    5. Tapia, John Frederick D. & Lee, Jui-Yuan & Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2016. "Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations," Applied Energy, Elsevier, vol. 184(C), pages 337-345.
    6. Middleton, Richard S. & Bielicki, Jeffrey M., 2009. "A scalable infrastructure model for carbon capture and storage: SimCCS," Energy Policy, Elsevier, vol. 37(3), pages 1052-1060, March.
    7. Nicolle, Adrien & Massol, Olivier, 2023. "Build more and regret less: Oversizing H2 and CCS pipeline systems under uncertainty," Energy Policy, Elsevier, vol. 179(C).
    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. Sun, Alexander Y., 2020. "Optimal carbon storage reservoir management through deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
    2. Li, Bei & Li, Yuanming & Liu, Shuangxing & Xue, Ming & Li, Xingchun & Wu, Peng, 2025. "A dynamic optimization layout model for CO2–flue gas co-storage considering interactions and geological heterogeneity," Energy, Elsevier, vol. 333(C).
    3. Wang, Peng-Tao & Wei, Yi-Ming & Yang, Bo & Li, Jia-Quan & Kang, Jia-Ning & Liu, Lan-Cui & Yu, Bi-Ying & Hou, Yun-Bing & Zhang, Xian, 2020. "Carbon capture and storage in China’s power sector: Optimal planning under the 2 °C constraint," Applied Energy, Elsevier, vol. 263(C).
    4. Zhang, Shuai & Liu, Linlin & Zhang, Lei & Zhuang, Yu & Du, Jian, 2018. "An optimization model for carbon capture utilization and storage supply chain: A case study in Northeastern China," Applied Energy, Elsevier, vol. 231(C), pages 194-206.
    5. Bardon, Paul & Massol, Olivier, 2025. "Decarbonizing aviation with sustainable aviation fuels: Myths and realities of the roadmaps to net zero by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    6. Herman, Kyle S. & Hall, Jeremy K. & Sovacool, Benjamin K. & Iskandarova, Marfuga, 2025. "The industrial decarbonization paradigm: Carbon lock-in or path renewal in the United Kingdom?," Ecological Economics, Elsevier, vol. 235(C).
    7. Vulin, Domagoj & Muhasilović, Lejla & Arnaut, Maja, 2020. "Possibilities for CCUS in medium temperature geothermal reservoir," Energy, Elsevier, vol. 200(C).
    8. Xu, Xiaoyi & Li, Qi & Cai, Bofeng & Liu, Guizhen & Pang, Lingyun & Jing, Meng & Guo, Jing, 2024. "Cost assessment and potential evaluation of geologic carbon storage in China based on least-cost path analysis," Applied Energy, Elsevier, vol. 371(C).
    9. Karjunen, Hannu & Tynjälä, Tero & Hyppänen, Timo, 2017. "A method for assessing infrastructure for CO2 utilization: A case study of Finland," Applied Energy, Elsevier, vol. 205(C), pages 33-43.
    10. Zhang, Shuai & Zhuang, Yu & Liu, Linlin & Zhang, Lei & Du, Jian, 2019. "Risk management optimization framework for the optimal deployment of carbon capture and storage system under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    11. Xie, Xiaoyu & Li, Kai & Zhang, Xian & Yao, Yue & Fan, Jing-Li, 2025. "Exploring the CCUS potential of China's coastal areas based on a source-to-offshore sink matching model," Energy, Elsevier, vol. 338(C).
    12. Fan, Jing-Li & Shen, Shuo & Wei, Shi-Jie & Xu, Mao & Zhang, Xian, 2020. "Near-term CO2 storage potential for coal-fired power plants in China: A county-level source-sink matching assessment," Applied Energy, Elsevier, vol. 279(C).
    13. Tapia, John Frederick D. & Lee, Jui-Yuan & Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2016. "Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations," Applied Energy, Elsevier, vol. 184(C), pages 337-345.
    14. Yao, Yue & Wang, Ying & Xiang, Xiaojuan & Xie, Xiaoyu, 2025. "A review of offshore carbon dioxide geological storage from a source-sink perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 222(C).
    15. Migo-Sumagang, Maria Victoria & Tan, Raymond R. & Aviso, Kathleen B., 2023. "A multi-period model for optimizing negative emission technology portfolios with economic and carbon value discount rates," Energy, Elsevier, vol. 275(C).
    16. Kemp, Alexander G. & Kasim, Sola, 2013. "The economics of CO2-EOR cluster developments in the UK Central North Sea," Energy Policy, Elsevier, vol. 62(C), pages 1344-1355.
    17. Massol, Olivier & Tchung-Ming, Stéphane & Banal-Estañol, Albert, 2018. "Capturing industrial CO2 emissions in Spain: Infrastructures, costs and break-even prices," Energy Policy, Elsevier, vol. 115(C), pages 545-560.
    18. Oei, Pao-Yu & Mendelevitch, Roman, 2016. "European Scenarios of CO₂ Infrastructure Investment until 2050," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 37, pages 171-194.
    19. Qianlin Zhu & Chuang Wang & Zhihan Fan & Jing Ma & Fu Chen, 2019. "Optimal matching between CO2 sources in Jiangsu province and sinks in Subei‐Southern South Yellow Sea basin, China," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 9(1), pages 95-105, February.
    20. Zhang, Kai & Lau, Hon Chung & Liu, Shuyang & Li, Hangyu, 2022. "Carbon capture and storage in the coastal region of China between Shanghai and Hainan," Energy, Elsevier, vol. 247(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2502.12035. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.