Dynamic analysis and linear model predictive control for operational flexibility of post-combustion CO2 capture processes

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A key feature of amine-based post-combustion CO2 capture process is a wide operating range induced by periodic load changes in power plants, which necessitates flexible operation. One possible approach to enhance the operational flexibility is to design a reliable controller that can effectively regulate the process over the operating range. To this end, in this study, a robust model predictive controller is designed by analyzing the dynamic characteristics of a post-combustion CO2 capture process. Specifically, gap metric analysis is performed to analyze the sensitivity of the process. From this analysis, optimal operating conditions are identified by evaluating similarity among the dynamics around different operating conditions. Then, a single linear model predictive controller is designed on the basis of the linear approximation of the original nonlinear model at the chosen conditions. Finally, the effectiveness of the controller is illustrated through a case study on an example CO2 capture process.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2020-09
Language
English
Article Type
Article
Citation

COMPUTERS & CHEMICAL ENGINEERING, v.140, pp.106968

ISSN
0098-1354
DOI
10.1016/j.compchemeng.2020.106968
URI
http://hdl.handle.net/10203/275927
Appears in Collection
CBE-Journal Papers(저널논문)
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