Dynamic Data Reconciliation and Model Validation of a MEA-Based CO₂ Capture System using Pilot Plant Data

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• 作者：Anderson S. Chinen^* ; Joshua C. Morgan^* ; Benjamin P. Omell^* ; Debangsu Bhattacharyya^*+ ; ^{Debangsu.Bhattacharyya@mail.wvu.edu" class="auth_mail" title="E-mail the corresponding author} ; David C. Miller^** ; ^{david.miller@netl.doe.gov" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Dynamic modeling ; validation ; dynamic data reconciliation ; MEA solvent modeling ; CO2 capture
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：7
• 页码：639-644
• 全文大小：986 K

文摘

This work focuses on development of a “gold standard” process model for a MEA-based post-combustion CO₂ capture process. The steady-state model includes a comprehensive thermodynamic framework in conjunction with the chemistry model. Parameters for all thermodynamic, transport, and physical properties models are regressed using extensive data available in the literature. An integrated mass transfer model is developed and validated using experimental data. The steady-state model is validated using data collected from the U.S. DOE’s National Carbon Capture Center (NCCC) in Wilsonville, Alabama. In addition to the steady-state runs, dynamic test runs were conducted at NCCC by introducing carefully-designed step changes and recording the transients of all key variables. Due to measurement noise and missing measurements for a number of key variables, a dynamic data reconciliation problem was solved to ensure material and energy balance of the collected data. Both the steady-state and dynamic models were validated against plant data for a wide range of operating conditions.