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Scalable algorithms for designing CO2 capture and storage infrastructure

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Abstract

CO2 capture and storage (CCS) is a climate change mitigation strategy that aims to reduce the amount of CO2 vented into the atmosphere from industrial processes. Designing cost-effective CCS infrastructure is critical in meeting CO2 emission reduction targets and is a computationally challenging problem. We formalize the computational problem of designing cost-effective CCS infrastructure and detail the fundamental intractability of designing CCS infrastructure as problem instances grow in size. We explore the problem’s relationship to the ecosystem of network design problems, and introduce three novel algorithms for its solution. We evaluate our proposed algorithms against existing exact approaches for CCS infrastructure design and find that they all run in dramatically less time than the exact approaches and generate solutions that are very close to optimal. Decreasing the time it takes to determine CCS infrastructure designs will support national-level scenario analysis, undertaking risk and sensitivity assessments, and understanding the impact of government policies (e.g., tax credits for CCS).

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Notes

  1. Enhanced oil recovery is the process of injecting CO2 into oil fields to increase production. Oil fields will pay for CO2 for this purpose, so the capture facility will collect proceeds from sale of CO2 to the oil field.

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Funding

This research was partially funded by the Great Plains Institute (GPI) through the State Carbon Capture Work Group.

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Authors and Affiliations

  1. School of Computing, Montana State University, Bozeman, MT, USA

    Caleb Whitman & Sean Yaw

  2. Los Alamos National Laboratory, Los Alamos, NM, 87544, USA

    Brendan Hoover & Richard Middleton

Authors
  1. Caleb Whitman
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  2. Sean Yaw
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  3. Brendan Hoover
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  4. Richard Middleton
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Correspondence to Sean Yaw.

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Whitman, C., Yaw, S., Hoover, B. et al. Scalable algorithms for designing CO2 capture and storage infrastructure. Optim Eng 23, 1057–1083 (2022). https://doi.org/10.1007/s11081-021-09621-3

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