Absorption-based CO2 capture processes

Abstract

Post-combustion CO2 capture (PCC) via chemical absorption into amine solvent is evaluated as one of the most industrialized capture methods among various carbon capture technologies, and has been demonstrated with operation on various industrial scales. The PCC process captures CO2 from the flue gas exhausted from a power plant, and the regeneration heat required to regenerate the CO2 rich amine solvent is also supplied from the steam extraction from the power plant. As such, since the PCC process is integrated with the power plant, its operation is significantly affected by the operation of the power plant. On the other hand, the power plant is flexibly operated by changing the power generation load according to seasonally, daily, and hourly changing power demand. Therefore, the PCC process also must be operated by changing the operating conditions in accordance with the significant changes in power generation load. At the same time, one can consider an economical operation strategy in the PCC process by varying the CO2 capture level and amount of steam extraction, according to the time-varying energy price. In these ways, it is possible to bring great economic profits by operating the PCC process flexibly in consideration of the time-varying energy price, carbon capture and emission cost, etc. For the flexible operation of the PCC process, it is necessary not only to optimize the economic feasibility of the process but also to have a control strategy that can change the operating conditions quickly, stably, and flexibly. To this end, this study aims to cover the topics required for the flexible operation of PCC processes, from dynamic process modeling, analysis of dynamics, controller design, and integrated control design that considers operation economics. By constructing a dynamic PCC process model, dynamic behavior is analyzed with step response and gap metric analysis. In addition, an advanced control technique, the so-called model predictive control (MPC), is applied for efficient control. Furthermore, an economic model predictive control (EMPC), which considers the real-time changing economic feasibility of the operation, is established and applied to the PCC process. Going beyond the simple linear MPC control technique, this study presents an integrated operation and control strategy that takes into account not only disturbance but also changes in economic factors over time. In addition to the conventional PCC process, the feasibility of a modular CO2 capture process suitable for small scale CO2 capture is analyzed through process modeling, design, and optimization. The advanced modular process with improved amine solvent and process intensification may point the way to the next-generation CO2 capture process. The modularized CO2 capture process is expected to realize the economy of scale even on a relatively small plant scale, and is also expected to lower entry barriers to CO2 capture technology in various industries other than the conventional PCC field.