(647e) Blue H2 Production of 12-Bed PSA Process Integrated with CO2 Absorption Process from Smr Syngas

Since H₂ is produced from mainly naphtha and natural gas reforming¹, and coal gasification² in chemical industries, an enormous amount of CO₂ emission is inevitable at present. To meet carbon neutralization, the H₂ production strategy is essential to shift from grey H₂ to blue H₂. In the process integration for simultaneous H₂ production and CO₂ capture, H₂ PSA processes currently in operation are essentially re-optimized because feed conditions are highly changed.

Herein, as a first step, the dynamic model of 12-bed H₂ PSA process is developed, which is widely used in petrochemical industries to produce H₂ from a reforming gas. The 12-bed PSA process using the layered beds with activated carbon and zeolite is operated at a 24-step cyclic sequence. The developed dynamic model is validated with industrial operating data. When dry-based reforming gas (H₂/CO/CH₄/CO₂; 72.25/2.62/6.71/18.42%) is used at real operating pressure and flowrate, H₂ purity of 99.99+% with 88+% recovery can be achieved, which agrees well with the real operating result. The role of each adsorptive layer was analyzed as a bulk separator or a purifier.

Then, a highly efficient blend-amine process, which is installed before the PSA process as a pre-combustion CO₂ capture, is optimized to achieve 90-99 % CO₂ capture with 99+ % purity from SMR syngas. Finally, the 12-bed PSA process integrated with the CO₂ capture process using blend-amine is studied. The optimal operating condition for the present 12-bed PSA process is affected by CO₂ capture rate in the range of 90 to 99% because feed composition and flowrate are significantly changed. Therefore, depending on the capture rate, the performance and dynamic behavior are analyzed to gain the insights of performance and dynamic behavior by using the verified dynamic model. Due to the complexity of the integrated process optimization by multi-operating variables, a machine learning technology is applied to find the optimum operating conditions at each CO₂ capture rate.

References:

1. Y. Park., J.H. Kang., D.K. Moon., Y.S. Jo, C.H. Lee., Chem. Eng. J. 408 (2021) 127299.
2. D.K. Moon, D.G. Lee, C.H. Lee, Appl. Energy. 186 (2016) 760.