Dynamic modeling and control of an intercooled absorber for post-combustion CO2 capture

Walters, Matthew S.; Edgar, Thomas F.; Rochelle, Gary T.

doi:10.1016/j.cep.2016.05.012

Cited by 25 publications

(12 citation statements)

References 19 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Waters et al [73] developed a rate-based dynamic model in gPROMS for an intercooled absorber with piperazine (PZ) solvent. Absorber intercooling can effectively improve the solvent capture capacity within the absorber, thus decreasing the energy consumption in solvent regeneration.…”

Section: Dynamic Models For Advanced Pcc Processmentioning

confidence: 99%

“…The dynamic modelling of PCC process has gone through many years of development and improvement, and has now become mature in methods and theory. Many scholars have also developed corresponding PCC models on various simulation platforms, such as gPROMS ® [36], [37], [47], [73], Aspen Dynamics ® [25], Modelica ® [49], [52], [61], Matlab ® [55], [68], [74], and gCCS ® [29], [30], [35]. However, most of these models have only been validated through steady state pilot plant data, which cannot be used to assess the transient performance of the model.…”

Section: Dynamic Validation Of the Pcc Modelmentioning

confidence: 99%

See 1 more Smart Citation

Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation

Wu¹,

Wang

Liao³

et al. 2020

Applied Energy

122

View full text Add to dashboard Cite

 Critical review on dynamic modelling, system identification and control of the PCC process  Classification of the existing studies according to the approaches used  Comprehensive analysis of the advantages and limitations of current studies  Summary of research achievements and challenges for flexible operation of solvent-based PCC  Prediction of the future research opportunities in solvent-based PCC process

show abstract

Section: Dynamic Models For Advanced Pcc Processmentioning

confidence: 99%

Section: Dynamic Validation Of the Pcc Modelmentioning

confidence: 99%

Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation

Wu¹,

Wang

Liao³

et al. 2020

Applied Energy

122

View full text Add to dashboard Cite

show abstract

“…However, the Radfrac column model does not export to Aspen Plus Dynamics ® . Dynamic rate-based models have been developed on other software platforms, such as gPROMS ® [18,23,24], Matlab ® [25], and UniSim ® [17]. The dynamic models developed on the Aspen Plus ® platform are either only for the stripper column [9] or equilibrium-based [26].…”

Section: Introductionmentioning

confidence: 99%

Control of Solvent-Based Post-Combustion Carbon Capture Process with Optimal Operation Conditions

et al. 2019

View full text Add to dashboard Cite

Solvent-based post-combustion carbon capture (PCC) is a mature and essential technology to solve the global warming problem. The high energy consuming issue and the flexible operation required by the power plants inquire about the development of effective control systems for PCC plants. This study proposes the optimal-based control approach that utilizes optimal set-point values for the quality controllers. The five optimal-based control schemes studied all employed L/G (liquid to gas ratio in absorber) as one quality control variable. Performance comparisons with a typical conventional control scheme are conducted employing a rate-based dynamic model for the MEA (monoethanolamine) solvent PCC process developed on a commercial process simulator. Compared to the typical control scheme, the optimal-based control schemes provide faster responses to the disturbance changes from the flue gas conditions and the set-point change of the CO2 capture efficiency, as well as better results in terms of IAEs (integral of absolute errors) of capture efficiency and reboiler heat duty during the stabilization period. LG-Tstr and LG-Tabs-Cascade are the best schemes. In addition to L/G, these two schemes employ the control of Tstr (the temperature of a stage of stripper) and a cascade control of Tabs (the temperature of a stage of absorber) (outer loop) and Tstr (inner loop), respectively.

show abstract

“…In recent years, monoethanolamine (MEA)-based post-combustion CO 2 capture technology has been extensively studied to capture the CO 2 from the coal-fired power plants [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The MEA-based CO 2 capture technique has several distinguishing features, such as a high CO 2 capture level, easy integration to power plants without much reformation of the existing plants, and relatively low construction cost, which makes it the most promising technique for commercial use [1,17].…”

Section: Introductionmentioning

confidence: 99%

Nonlinearity Analysis and Multi-Model Modeling of an MEA-Based Post-Combustion CO2 Capture Process for Advanced Control Design

Liang

et al. 2018

Applied Sciences

View full text Add to dashboard Cite

Abstract:The monoethanolamine (MEA)-based post-combustion CO 2 capture plant must operate flexibly under the variation of the power plant load and the desired CO 2 capture rate. However, in the presence of process nonlinearity, conventional linear control strategy cannot achieve the best performance under a wide operation range. Considering this problem, this paper systematically studies the multi-model modeling of the MEA-based CO 2 capture process for the purpose of (1) implementing well-developed linear control techniques to the design of an advanced controller and (2) achieving a wide-range flexible operation of the CO 2 capture process. The local linear models of the CO 2 capture process are firstly established at given operating points using the method of subspace identification. Then the nonlinearity distribution at different loads of an upstream power plant and different CO 2 capture rates is investigated via the gap metric. Finally, based on the nonlinearity investigation results, the suitable linear models are selected and combined together to form the multi-model system. The proposed model is validated using the measurement data, which is generated from a post-combustion CO 2 capture model developed in the go-carbon capture and storage (gCCS) simulation platform. As the proposed multi-linear model has a simple mathematical expression and high prediction accuracy, it can be directly employed as the control model of a practical advanced control strategy to achieve a wide operating range control of the CO 2 capture process.

show abstract

Dynamic modeling and control of an intercooled absorber for post-combustion CO2 capture

Cited by 25 publications

References 19 publications

Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation

Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation

Control of Solvent-Based Post-Combustion Carbon Capture Process with Optimal Operation Conditions

Nonlinearity Analysis and Multi-Model Modeling of an MEA-Based Post-Combustion CO2 Capture Process for Advanced Control Design

Contact Info

Product

Resources

About