Model Predictive Control for Integrated Operation of Coal-Fired Power Plant and Post-Combustion Carbon Capture

For environmental protection, solvent-based post-combustion carbon capture (PCC) process has begun to be applied to the coal-fired power plant (CFPP) to combat the CO2 emission issue. It is necessary to develop an appropriate control strategy for the integrated CFPP-PCC process. However, due to the strong interactions between PCC process and CFPP, it imposes challenge to achieve appealing control performance for the integrated system. For this reason, this paper presents a centralized model predictive control technique. Key variables within the entire process, including mass coal flowrate, main steam valve opening, lean solvent flowrate and reboiler steam flowrate are manipulated to control the main steam pressure, net power output, capture rate and reboiler temperature. Simulation in case of CFPP load change is carried out to demonstrate the effectiveness of the proposed control scheme. The results illustrate that model predictive controller is capable of achieving a satisfactory performance compared to conventional PI controllers.