Uncertainty analysis in the techno-economic assessment of CO2 capture and storage technologies

Critical review and guidelines for use

Journal Article (2020)
Authors

Mijndert W. Van Der Spek (Heriot-Watt University)

Timothy Fout (National Energy Technology Laboratory)

Monica Garcia (IEAGHG, Cheltenham)

Vishalini Nair Kuncheekanna (Norwegian University of Science and Technology (NTNU))

Michael Matuszewski (National Energy Technology Laboratory)

Sean McCoy (University of Calgary)

Joshua Morgan (National Energy Technology Laboratory)

Shareq Mohd Nazir (KTH Royal Institute of Technology)

Andrea Ramírez Ramirez (TU Delft - Energy and Industry)

Simon Roussanaly (SINTEF Energy Resarch)

Edward S. Rubin (Carnegie Mellon University)

Research Group
Energy and Industry
To reference this document use:
https://doi.org/10.1016/j.ijggc.2020.103113
More Info
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Publication Year
2020
Language
English
Research Group
Energy and Industry
Volume number
100
DOI:
https://doi.org/10.1016/j.ijggc.2020.103113

Abstract

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.

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