Statistical Correlations Between Various Drivers of Energy Demand in Post-Combustion Carbon Capture Retrofitted Power Plants

Abstract

Power plants are one of the main sources emitting the CO2 that is responsible for climate change consequences. Post-combustion carbon capture (PCC), particularly using an aqueous solution, is highly recommended to be used as a mitigation solution to reduce the emissions of CO2 from power plants. Although PCC is a promising solution, the process still needs further development to reduce the energy demand for solvent regeneration. This paper reviews the challenges related to the post-combustion processes and finds the correlations between selected variables addressed by several researchers. Moreover, this study provides valuable insights into the factors influencing the reduction in energy demand and efficiency penalties. The research findings highlight the importance of considering two key drivers during the design of the PCC process. These are the absorber temperature and the type and amount of the selected solvent. Indeed, statistical analyses show that there is a correlation between the identified drivers’ values and the energy demand of solvent regeneration.

Keywords

• post-combustion capture
• aqueous solution
• absorber temperature
• energy demand drivers
• solvent regeneration energy
• statistical analysis