Cost optimization methodology based on carbon-techno-economic analysis: An application to post-combustion carbon capture process

Sihwan Park, Haneul Mun, Jinwoo Park, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Recently, a carbon tax has been introduced to encourage emissions reduction, and it has become an additional cost burden. To evaluate the carbon emissions and process costs simultaneously in a single indicator, a carbon-techno-economic analysis (CTEA) methodology that combines carbon tax and process cost was developed in this study. The proposed CTEA model was used to optimize the post-combustion carbon capture (PCC) process, which is an energy- and cost-intensive process. In CTEA optimization, as the carbon tax price increases from $12.5/tonne CO2 to $250/tonne CO2, more energy is provided to the PCC process to increase the carbon capture level from 58.92 % to 99.64 %. This results in a decrease in power generation of the natural gas combined cycle power plant from 462.33 MW to 436.07 MW, and an increase in the incremental cost of electricity from $14.05/MWh to $17.74/MWh. The decrease in profit from CTEA optimization is only 8.75 %, which is relatively smaller than the 11.68 % and 32.32 % decrease in profit from energy and TEA optimization, respectively. The results demonstrate that CTEA-based process optimization is beneficial and highlight the trade-off relationship among carbon tax, process cost, and profit. The results of this study can guide commercial companies in setting operational strategies for their processes as carbon tax prices change and can also assist governments in establishing carbon tax policies to encourage carbon emission reductions in industries.

Original languageEnglish
Article number139887
JournalJournal of Cleaner Production
Volume434
DOIs
StatePublished - 1 Jan 2024

Keywords

  • Bayesian optimization
  • Carbon tax
  • Carbon-techno-economic analysis
  • Post-combustion carbon capture

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