Cost estimation of CCS integration into thermal power plants in Japan

Abstract

Carbon capture and storage (CCS) is an important technology to reduce CO₂ emissions from power and industry. To accelerate large-scale CCS deployment, further reduction of the cost to implement the full technology chain is necessary. Full chain CCS cost depends on multiple technological, market, and societal factors. Therefore, case-specific cost analysis is important. This study estimates the CCS cost in Japan, which can be considered as a case study for specific countries where offshore sites are more suitable for CO₂ storage than onshore sites regarding geological reasons and barrier reduction of public/political acceptance. With the phasedown of unabated coal power, retrofitting amine-based post-combustion CO₂ capture system is a realistic way for pulverized coal-fired power plants. Capture cost was determined by the process simulation of coal-fired power plant retrofits. Current political realities in Japan suggest that CO₂ transport will be done by ship. Transport cost was estimated via a bottom-up analysis of each sub-process. Injection and monitoring cost was based on the values reported by the Tomakomai demonstration project, which are applicable to onshore injection into an offshore storage site. We find the full chain CCS cost to be 99-111 USD/t-CO₂. Though changing the solution in the CO₂ capture process from monoethanolamine to the blend of 2-amino-2-methyl-1-propanol and piperazine reduces the regeneration energy by 0.85 GJ/t-CO₂, the CCS cost was only reduced by ~9 USD/t-CO₂. Likewise, even when the regeneration energy was reduced to 2.0 GJ/t-CO₂ using a hypothetical amine solution embedded in a highly optimized PCC system, the CCS cost was still ~93 USD/t-CO₂. Considering that capital expenditure accounts for ~65% of capture cost, downsizing capture facilities may provide further cost reduction. Since transport and storage costs were roughly equivalent to capture costs, full chain CCS implementation is likely necessary to reduce costs through learning-by-doing, scale-out, and market effects.