SQP-based optimization algorithm: A novel calculation analysis for improved energy-economic efficiency and CO2 purity in stripper segments of CCUS systems

This study investigates the effect of stripper numerical segment and physical change configuration on CO2 purity, reboiler energy consumption, and overall economic performance in a monoethanolamine (MEA)-based post-combustion carbon capture (PCC) process. The number of numerical segments controls th...

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Vydáno v:Case studies in thermal engineering Ročník 75; s. 107133
Hlavní autoři: Takyi, Shadrack Adjei, Zhang, Yindi, Jiang, Wufeng, Han, Weiwei, Zeng, Fanhua
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.11.2025
Elsevier
Témata:
CCUS
CO2 purity
Energy optimization
SQP algorithm
Stripper segmentation
CCUS
Stripper segmentation
CO2 purity
SQP algorithm
Energy optimization
ISSN:2214-157X, 2214-157X
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Shrnutí:This study investigates the effect of stripper numerical segment and physical change configuration on CO2 purity, reboiler energy consumption, and overall economic performance in a monoethanolamine (MEA)-based post-combustion carbon capture (PCC) process. The number of numerical segments controls the numerical resolution of internal temperature and concentration profiles and therefore affects the predicted desorption performance and associated metrics such as specific reboiler duty and CO2 purity. The number of numerical segments in the stripper plays a critical role in accurately determining the driving force for desorption, solvent regeneration efficiency, and ultimately the purity of the captured CO2 stream. In this work, a detailed rate-based rigorous model was developed using chemical simulation software, incorporating industrially relevant thermodynamic and hydraulic constraints. Segment numbers were systematically varied across nine cases: 10, 20, 30, 40, 50, 70, 80, 90, and 100. The Sequential Quadratic Programming (SQP) algorithm was implemented in Fortran and externally coupled with the chemical simulation software via a sequential iterative loop. It was applied to minimize reboiler duty and operational cost, subject to process constraints including absorber lean loading, solvent circulation rate, and product purity specifications. The simulation and optimization results revealed that refining the number of numerical segments improves numerical resolution and reduces discretization error, leading to more accurate predictions of CO2 desorption performance. At the numerical resolution of 100 segments, the model achieved a capture efficiency of 99.87 % and a rich solvent loading of 0.48 molCO2/molMEA. Higher segment counts lead to more accurate values for lean loading and capture rates, which in turn facilitates further process optimization with increased column height and accompanying capital requirements. SQP successfully identified optimal operating conditions, particularly for pressure, reboiler temperature, and lean solvent conditions that balance energy savings with cost-effectiveness. This work contributes a quantitative and systematic framework for optimizing stripper design using deterministic optimization methods and offers new insights into the trade-offs between mass transfer efficiency, energy consumption, and economic feasibility in large-scale PCC systems. [Display omitted]
ISSN:2214-157X
2214-157X
DOI:10.1016/j.csite.2025.107133