Flexible operation and simultaneous scheduling and control of a CO2 capture plant using model predictive control

Post-combustion CO2 capture plants that employ amine-based solvents are regarded as the most feasible strategy to reduce the CO2 emission from coal-fired power plants. This study presents a dynamic flexibility analysis of a post-combustion CO2 capture process using model predictive control (MPC). The critical operating conditions in the plant's main load (flue gas flowrate) were initially identified in open-loop and closed-loop. Insights from this analysis have shown that oscillatory changes with high frequency content in the load are particularly harmful for this process in closed-loop. Taking this insight into account, a simultaneous scheduling and control framework was developed to identify optimal operating policies under critical operating conditions in the flue gas flowrate. The results obtained from this framework were compared against a conventional sequential control and scheduling approach. The results show that the proposed integrated framework specifies more economically attractive policies than those obtained from the sequential approach. (C) 2015 Elsevier Ltd. All rights reserved.