Methodological improvements to ex-ante techno-economic modelling and uncertainty analysis of emerging CO2 capture technologies
Year: 2017
Type: dissertation
Abstract: Techno-economic analysis is a critical means to assess the feasibility of emerging climate mitigation technologies. Preferably, we would like to understand already in an early stage of development how a technology will perform in real life. But the further you go back in the technology development cycle, the more uncertain the performance becomes. Mijndert’s thesis focuses on the methodological challenges of making early stage assessments of technology performance. The thesis addresses improved ways to uncertainty analysis and communication, and introduces hybrid methods to predict the real life performance of yet experimental technologies. The analyses led to methodological improvements to techno-economic analysis, which were applied to a range of CO2 separation technologies, operating to capture CO2 from thermal power plants. As a result, the thesis makes a step to more realistic and transparent evaluation of new energy and climate technologies. The above is reflected in the research goal: to investigate key methodological issues concerning the reliability and uncertainty of ex-ante techno-economic analysis for emerging technologies, and, to propose methodological improvements to current modelling practices. To fulfil the research goal, the following three research questions were addressed: RQ1. What are the main challenges when using state-of-the-art techno-economic analysis methods to assess emerging CO2 capture technologies, and how can these challenges be addressed? RQ2. How is uncertainty analysis incorporated in techno-economic modelling of CO2 capture technologies, where are the most important gaps, and how can uncertainty analysis be improved? RQ3. How can flexible dispatch be incorporated in the techno-economic analysis and comparison of CO2 capture technologies, and how does this influence their performance?
Author: Mijndert van der Spek
Language: English
Subfield: Filtration and Separation
Field: Chemical Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2777633740