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Superstructure optimization reveals novel cost-optimal power-to-methanol pathways using hybrid solid oxide electrolysis cells

Author

Listed:
  • Qi, Meng
  • Alirahmi, Seyed Mojtaba
  • Cui, Chengtian
  • Zhang, Zhiwei
  • Zhang, Xiaodong
  • Wang, Lina
  • Chen, Ming
  • Díaz-Sainz, Guillermo
  • Yu, Haoshui

Abstract

Power-to-methanol offers a promising pathway for large-scale, long-term energy storage, yet hydrogen (H2)/syngas production remains the key techno-economic bottleneck. Solid oxide electrolysis cells (SOECs) can efficiently produce H2 and carbon monoxide, but with multiple options available (such as steam electrolysis, co-electrolysis, and CO2 electrolysis) and possible coupling with (reverse) water–gas shift reactions, it is still unclear which option and process pathway, whether alone or in hybrid, most effectively minimizes methanol production costs. This study addresses this gap with a two-stage framework that combines surrogate-based superstructure optimization with detailed process integration and assessment. The optimization reveals two cost-optimal, previously unexplored pathways featuring hybrid SOEC configurations: (i) production of CO-based feed gas using steam and CO2 electrolysis, and (ii) production of CO2-based feed gas with an additional water–gas shift step to generate additional H2 while producing CO2. Advanced process design is then conducted and shows that CO-based methanol synthesis outperforms the CO2-based route in terms of methanol yield and energy consumption. The combined steam and CO2 electrolysis configuration achieves the highest energy efficiency (74%), compared with co-electrolysis and steam electrolysis alone. The levelized cost of methanol is estimated at 1050–1155 USD/t, with the potential to decrease to bio- or fossil-methanol cost levels under projected reductions in electricity price and SOEC stack cost.

Suggested Citation

  • Qi, Meng & Alirahmi, Seyed Mojtaba & Cui, Chengtian & Zhang, Zhiwei & Zhang, Xiaodong & Wang, Lina & Chen, Ming & Díaz-Sainz, Guillermo & Yu, Haoshui, 2026. "Superstructure optimization reveals novel cost-optimal power-to-methanol pathways using hybrid solid oxide electrolysis cells," Applied Energy, Elsevier, vol. 410(C).
  • Handle: RePEc:eee:appene:v:410:y:2026:i:c:s030626192600231x
    DOI: 10.1016/j.apenergy.2026.127579
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