Dynamic modeling and advanced control of post-combustion CO2 capture plants

Abstract

In this paper, model predictive control (MPC) strategies are implemented to address different stripper configurations for the CO2 capture process as part of supercritical pulverized coal-fired (SCPC) power plants. Dynamic models of the conventional and lean vapor compression (LVC) CO2 capture configurations are introduced. Linear and nonlinear MPC strategies are implemented to the CO2 capture processes for a power plant load-following scenario that simulates power plant cycling. Implementation of the MPC strategies for both the conventional and the LVC configurations are successful. Closed-loop responses for the carbon capture rate and total equivalent work are compared and analyzed. The results show that the proposed nonlinear MPC improves the performance by 95% in terms of the integral square error (ISE) results when compared to a PID controller. Also, the proposed LVC configuration with NLMPC implemented has a 5.5% economic improvement when compared to the traditional configuration with PID controllers.