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Multi-Objective Optimization of a Hybrid Fossil/Renewable Carbon Methanol Cluster

  • Sachin Jog
  • , Juan D. Medrano-García
  • , Daniel Vázquez
  • , Gonzalo Guillén-Gosálbez*
  • *Corresponding author for this work

Research output: Indexed journal article Articlepeer-review

4 Citations (Scopus)

Abstract

Replacing fossil carbon- with renewable carbon-based technologies is imperative for transitioning to sustainable chemical production. However, most production pathways based on renewable carbon are currently economically unappealing. Here, we show that hybrid clusters exploiting synergies between different fossil and renewable carbon-based processes in terms of heat, mass, and power integration could make defossilized chemical technologies more competitive. We consider an integrated carbon cluster based on fossil and renewable carbon feedstocks for methanol production, including a novel oxy-combustion cycle for purge gas treatment and power generation. Using multiobjective optimization considering economic and environmental criteria (i.e., unitary production cost and global warming potential (GWP) impact, respectively), we find that integrated clusters could reduce the cost of carbon-neutral methanol by up to 30%, while leading to reductions in GWP impact from 21 to 142% for a given unitary production cost target, and heating utility savings between 80 and 100%. We conclude that hybridization of fossil and renewable technologies could become instrumental in enabling a gradual shift toward sustainable chemical production pathways.

Original languageEnglish
Pages (from-to)1473–1483
Number of pages11
JournalACS Sustainable Chemistry and Engineering
Volume13
Issue number4
DOIs
Publication statusPublished - 3 Feb 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • climate change mitigation
  • global warming potential
  • heat integration
  • integrated carbon cluster
  • multiobjective optimization

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