Post-combustion amine absorption is the most mature CO₂ capture technology, while membrane separation is a promising alternative due to its modularity and operational simplicity. Process intensification through exhaust gas recirculation (EGR) has also gained attention for increasing flue gas CO₂ concentration and reducing capture energy demand. However, comprehensive techno-economic comparisons of absorption, membrane, and hybrid systems under EGR-integrated NGCC conditions remain limited. This study presents a techno-economic assessment of multiple CO₂ capture configurations for a 450 MW NGCC power plant. Process simulations were performed using Aspen Plus and Aspen Custom Modeler to evaluate absorption, membrane, and hybrid systems integrated with conventional and selective EGR. The analysis considers full steam cycle integration and compares energy consumption, net plant efficiency, levelized cost of electricity (LCOE), and CO₂ avoidance cost. The results show that EGR significantly improves carbon capture performance. Among all cases, selective EGR combined with amine absorption delivers the best performance, reducing the energy penalty by more than 30% compared with standalone absorption and by over 70% relative to membrane separation. This configuration achieves an LCOE of approximately 72 USD/MWh and a CO₂ avoidance cost of about 39 USD/tCO₂, outperforming the selective EGR–membrane system (77 USD/MWh and 51 USD/tCO₂). These findings demonstrate that integrating selective EGR with amine absorption is a highly promising strategy for improving the technical and economic feasibility of CCSU in NGCC power plants.

Post-combustion CO₂ capture using monoethanolamine (MEA) is a mature mitigation technology, yet its high energy demand and complex dynamics remain major challenges. This study presents a unified dynamic modeling and control framework for an MEA-based absorption–regeneration system, focusing on a comparative evaluation of PID, fuzzy logic control (FLC), and model predictive control (MPC) under realistic operating disturbances. A control-oriented surrogate model was developed in MATLAB R2024b/Simulink and validated against published benchmark trends. The control objective was to maintain CO₂ capture efficiency above 90% while minimizing reboiler energy consumption under ±10% inlet CO₂ concentration and flue gas flow disturbances. Simulation results showed that PID control ensures basic stability but exhibits slow recovery and high energy usage, while FLC improves robustness with limited dynamic improvement. MPC consistently maintained capture efficiency above the target value, reduced the settling time by approximately 37%, and achieved a 12.4% reduction in average reboiler duty compared to PID control. The results demonstrate that a unified, implementation-oriented modeling framework enables the effective assessment of advanced control strategies and supports the energy-efficient operation of industrial MEA-based CO₂ capture systems.