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.
Highlights
Sound uncertainty analysis is critical to the informed interpretation of carbon capture and storage (CCS) techno-economic analyses (TEA)(van der Spek et al, 2016; Rubin, 2012)
Uniform Triangular Normal or lognormal if the value physically cannot be below zero Beta Poisson probability distribution, that is a probability density function (PDF) that is based on knowledge of the process/parameter rather than data
The results demonstrate some spread in the values of Sobol indices that results from replicating the calculation, the relative im portance is shown to be predicted consistently; for both cases para meters 5–6 and 8–9 are shown to have the highest effect on the CO2 capture prediction
Summary
Sound uncertainty analysis is critical to the informed interpretation of carbon capture and storage (CCS) techno-economic analyses (TEA). Building on a previous CCS costing guideline paper (Rubin et al, 2013), this work sets out to provide a review of, and guidelines on, uncertainty analysis methods for use in CCS TEA It combines knowl edge and experience acquired in academia, research institutes and nongovernmental organizations (NGOs). The overarching goal of this manuscript is to ad vance the sound and fit-for-purpose use of uncertainty analysis in CCS TEA by providing practitioners and users with a reference document of relevant methods, tools and approaches, and a guideline of when and how to use them These guidelines do not intend to provide an ex haustive account of every available method, rather to showcase dif ferent methods over a broad spectrum that can act as an illustration of the type of methods available. These guidelines are applicable to TEAs of CO2 utilisation and negative emission technolo gies
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