Unravelling uncertainty and variability in early stage techno-economic assessments of carbon capture technologies. (January 2017) - van der Spek, Mijndert; Sanchez Fernandez, Eva; Eldrup, Nils Henrik; Skagestad, Ragnhild; Ramirez, Andrea; Faaij, André
Highlights: Two different capital cost estimates on the same AMP/PZ postcombustion solvent technology were compared. Significant differences in equipment costs (66%) and total capital requirement (65%) were found. These were mainly caused by different equipment sizing and column equipment cost estimation. Pedigree analysis/diagnostic diagrams are a good addition to traditional sensitivity analysis. The LCOE proved most sensitive to the power plant efficiency penalty due to capture and compression. Abstract: This paper addresses the uncertainty and variability in techno-economic studies of carbon capture technologies, based on a detailed comparison of the results of different studies on postcombustion CO2 capture with advanced amines, and on an in-depth uncertainty analysis using a combination of sensitivity and pedigree analyses. The results show that despite efforts to harmonize capital cost estimates, the capital cost results of the same PCC carbon capture systems can still show large (65%) differences. This uncertainty may simply be inherent to early stage cost estimates. Amongst the most important causes for the variability shown in this work are differences in equipment sizing methods and purchased equipment cost estimates. This capital cost variability only mildly propagates into the Levelised Cost of Electricity and Cost of CO2 Avoided, more so in case of low power plant utilisation scenarios. To enhance insight into these uncertainties and enable their communication, the paper argues to use in-depth uncertainty evaluation for early stage techno-economic studies. It suggests to complement current practice of sensitivity analysis with pedigree analysis and to combine the results of both analyses in diagnostic diagrams. This may lead to more informed interpretation of the results of techno-economic studies, and helps focus techno-economic research efforts towards the parameters that most influence final performance indicators.