文章基本信息

标题：Real-Time Optimization and Nonlinear Model Predictive Control for a Post-Combustion Carbon Capture Absorber
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作者：Gabriel D. Patrón ; Luis Ricardez-Sandoval
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：11595-11600
DOI：10.1016/j.ifacol.2020.12.639
语种：English
出版社：Elsevier
摘要：AbstractA framework to perform real-time optimization (RTO) and nonlinear model predictive control (NMPC) is presented for a post-combustion carbon capture absorber unit. The NMPC is applied as a set point regulator with and without an accompanying RTO scheme. Moreover, a Kalman filter (KF) is used to perform state estimation for the scheme. The absorber RTO formulation considers solvent degradation cost, carbon tax, and electrical pumping costs. The two scenarios (with and without RTO) are assessed in situations with a fixed carbon tax, and a time-varying carbon tax. The results show that the RTO/NMPC scheme provides substantial economic benefit over the NMPC-only scheme, even for a short simulation time (~130 minutes). Furthermore, the RTO also aids in guaranteeing reachable set points for the NMPC, which may not occur otherwise.
关键词：KeywordsReal-time OptimizationControlNonlinear Process ControlControl of Large-scale Systems