Research On Advanced Control Technology Of Post-combustion CO₂ Capture System

As one of the most abundant greenhouse gases in the atmosphere,the global climate change caused by CO₂ has become one of the main environmental problems faced by human beings.Capturing CO₂ after combustion based on chemical absorption method is regard as the most effective choice to solve the CO₂ emission problem of fossil fuel power plants.In order to make the post-combustion CO₂capture system more suitable for power plants,more and more attention has been paid to the flexible operation of the capture system,which requires that the capture system can adapt to the change of flue gas flow and quickly adjust the carbon capture level in a wide range of operation.Hence,it is necessary to master the change characteristics of the capture system in the steady state at various working points,gain a thorough understanding of transient behaviors for carbon capture system,concurrently to propose advanced control strategies,and realize the flexible operation of the system.In this regard,it is of great significance to promote energy conservation and emission reduction,take the road of green,environmental protection and sustainable development.Based on the above analysis,in this work,there are four major contributions:1.Firstly,according to the dynamic behavior description of the post-combustion CO₂ capture system,the steady-state model was established in Aspen Plus,and the nonlinear distribution of the system under different steady-state conditions was analyzed.Then,the dynamic model was built in Aspen Plus Dynamics.In this plantform,the open-loop step response tests is carried out on the key variables of the system and qualitatively analyze the dynamic change rules among the major variables of the system.2.In view of the characteristics of large inertia and strong coupling of carbon capture system and the poor control effect of conventional PID control strategy,MATLAB/Simulink simulation platform was used to identify the state space equation in line with the actual situation.Conventional fuzzy PID（CFPID）controller is designed in the conventional operation interval of carbon capture system,and the overshoot problem in the capture system is improved.The feedforward fuzzy PID（FFPID）controller is designed based on the CFPID.The simulation results show that the FFPID can better track the set value of capture rate,and has the advantages of shorter adjustment time,smaller overshoot and lower steady-state error,so that the CO₂ capture system can better meet the control requirements.3.In order to avoid the problem of poor stability caused by the aggressive control effect in the capture system,the lean solvent flow increment was taken as the constraint condition and the model predictive control（MPC）was adopted for tracking control,so that the CO₂ capture system could better meet the requirements of flexible capture.The simulation results show that the performance of MPC is better than FFPID under three performance indexes,and it can prevent the flow of lean solvent from changing greatly,limit the amplitude of capture rate,and more in line with the industrial reality.Then,in view of the disturbance in the upstream power plant in the actual process,the flue gas flow rate is taken as the measurable disturbance variable,and the feedforward control is added to the original MPC controller.This method can quickly reduce the oscillation caused by flue gas disturbance to the system,and enhance the predictive control ability to suppress the disturbance.4.In view of the problem that the actual plant control effect and economic benefit need to be taken into account.Based on the MPC,the carbon emission and lean solvent energy consumption are taken as price factors,The economic performance function reflecting the economic excellence of the system is constructed,and the economic model prediction controller with terminal constraint is designed.The simulation results show that the economic model predictive control（EMPC）can maintain the excellent control quality of the CO₂ capture system under the economic optimal condition.