Reducing initial barriers for CCS deployment on pulverized coal-fired power plants in China by optimizing the capture ratio of carbon dioxide

The major barriers for applying carbon dioxide (CO₂) capture technology to coal-fired power plants in China and worldwide are the consequent drop in power plant energy efficiency and significantly higher cost of electricity (COE). This paper proposes a new perspective for determining the most cost-efficient CO₂ capture ratio using a modeling and simulation approach that balances the per unit parasitic energy consumption for absorbent regeneration with the per unit capital cost of the CO₂ capture unit of a coal-fired power plant. Using a typical 550 MW supercritical pulverized coal-fired power plant in China as the reference plant, with monoethanolamine (MEA) absorption unit for CO₂ capture, a process model of the power generation unit together with the MEA CO₂ capture unit was developed and detailed process simulations were conducted with the model. Then, a sensitivity analysis was then conducted to study the impact on key plant behavior indicators, including per unit energy penalty for absorbent regeneration, net power output and power generation efficiency, total capital cost of the power plant together with the MEA CO₂ absorption unit, per unit capital cost of the MEA unit, COE, as well as the per unit CO₂ avoidance cost (indicated by cost per tonne (t) CO₂ avoided), across a CO₂ capture ratio range between 20% and 99%. The results show that when CO₂ capture ratio is low, while the unit energy consumption for absorbent regeneration per tCO₂ avoided increases steadily with the increase of CO₂ capture ratio, the cost per tCO₂ avoided decreases as the MEA absorption train is scaled up given the high capital cost of each MEA train. After CO₂ capture ratio reaches certain level (60% for this plant), the cost per tCO₂ avoided starts to increase with CO₂ capture ratio, since the unit energy consumption for absorbent regeneration per tCO₂ avoided has increased to so high that it supplants the scaling effect of the MEA train and becomes the dominant factor that determines the increase or decrease trend of the cost per tCO₂ avoided. Besides, due to the physical restraint on the upper bound of CO₂ capture capability of one single MEA train by the diameter of the absorber, an additional MEA train is needed when the CO₂ capture ratio increases to certain points (40% and 85% for this plant), resulting in jumps of several parameters including the total capital cost for the power plant and MEA CO₂ capture unit, per unit capital cost for the MEA CO₂ capture unit, and last the cost per tCO₂ avoided. Based on all these result, finally a cost-optimal CO₂ capture ratio of 40% (365 RMB/tCO₂-_avoided) was obtained, which is easier for the power plant to bear while realizing a significant reduction in CO₂ emission of this plant. Therefore, applying this approach for determining CO₂ capture ratios could help minimize the barrier for the initiation of carbon dioxide capture and storage (CCS) in China's power industry. Besides, future replacement or improvement for the MEA CO₂ capture technology has the potential to further reduce the cost per tCO₂ avoided, which needs special attention.