Synthesis of green light olefins from direct hydrogenation of CO2. Part II: detailed process design and optimization

  • Hsuan Han Chiu
  • , Bor Yih Yu*
  • *Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

7 Scopus citations

Abstract

Background: In Part II, our objective is to investigate the optimal configuration and operating conditions for each process section of the CO2-based light olefin production process described in Part I. Method: The main sections (reaction, CO2 capture, and olefin recovery) in the entire process are rigorously designed and optimized. Six alternative reactor configurations were proposed, and optimized by maximizing the productivity. The Trade-offs between cost, indirect CO2 emission, and CO2 capture ratio were analyzed for the CO2 capture section through multi-objective optimization. Three scenarios for olefin recovery were proposed and optimized by minimizing costs. Significant findings: For the reaction section, the configuration employing two fixed-bed reactors with co-current heat exchange (Scheme R6) results in the highest conversion (75.45 %) and selectivity towards light olefins (82.49 %). Both are significantly higher than the available data in the literature. For the CO2 capture section, the optimal configuration has a 90 % CO2 capture ratio and requires a specific energy of 3.63 GJ/Ton-CO2. For the olefin recovery section, over 50 % of the costs can be reduced if hydrogen is removed before entering the cryogenic distillation process (Scheme O1). These findings support that the entire process presented in Part I of this study is in economical and environmentally-friendly conditions.

Original languageEnglish
Article number105287
JournalJournal of the Taiwan Institute of Chemical Engineers
Volume155
DOIs
StatePublished - 02 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Taiwan Institute of Chemical Engineers

Keywords

  • Bayesian optimization
  • CO utilization
  • Genetic algorithm
  • Light olefins
  • Multi-objective optimization
  • Particle swarm optimization

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