Correlating Parameters With Methane Purity And Recovery By Pressure Swing Adsorption In Methane Enrichment From Biogas

• Main Author: Chelvan, Shaila Pannir
• Format: Monograph
• Language: English
• Published: Universiti Sains Malaysia 2022
• Subjects: T Technology; TP155-156 Chemical engineering
• Online Access: http://eprints.usm.my/55652/1/Correlating%20Parameters%20With%20Methane%20Purity%20And%20Recovery%20By%20Pressure%20Swing%20Adsorption%20In%20Methane%20Enrichment%20From%20Biogas.pdf; http://eprints.usm.my/55652/
• Institution: Universiti Sains Malaysia

Simulation model of methane enrichment from biogas by pressure swing adsorption (PSA) using Aspen AdsorptionTM version 11 was studied with binary mixture of biogas consisting of different compositions of methane and carbon dioxide. Breakthrough curves of simulated data and experimental data were compared to validate the model. The comparison revealed that methane and carbon dioxide breakthrough curves from experiment and simulation was in a good agreement. The effects of design parameters such as adsorption pressure, CO2 concentration in the feed and adsorption duration, on methane purity and recovery were analysed. Increase in adsorption pressure led to higher amount of carbon dioxide being adsorbed and improved purity of methane but lower methane recovery due to longer retention time in the column. Higher CO2 concentration in the feed and adsorption time resulted in the reduction of methane purity while biomethane recovery increased due to longer residence time at increased adsorption time. In this work, operating parameters were optimised to produce maximum methane purity and recovery from PSA unit. Optimised methane purity and recovery were recorded at 99.996 % and 98.785 % respectively at of 3 bar adsorption pressure, 50% carbon dioxide concentration and 143 seconds of adsorption time. This study presents silica gel as an effective adsorbent, competing other classes of carbon-based materials in separating CO2 to produce high biomethane purity. The developed model has great competence for making prediction of biogas upgrading performance by PSA.