Enabling thermal-neutral electrolysis for CO2-to-fuel conversions with a hybrid deep learning strategy

Haoran Xu, Jingbo Ma, Peng Tan, Zhen Wu, Yanxiang Zhang, Meng Ni, Jin Xuan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


High-temperature co-electrolysis of CO2/H2O through the solid oxide electrolysis cells (SOECs) is a promising method to generate renewable fuels and chemical feedstocks. Applying this technology in flexible scenario, especially when combined with variable renewable powers, requires an efficient optimisation strategy to ensure its safety and cost-effective in the long-term operation. To this purpose, we present a hybrid simulation method for the accurate and fast optimisation of the co-electrolysis process in the SOECs. This method builds multi-physics models based on experimental data and extends the database to develop the deep neural network and genetic algorithm. In the case study, thermal-neutral condition (TNC) is set as the optimisation target in various operating conditions, where the SOEC generates no waste heat and needs no auxiliary heating equipment. Small peak-temperature-gradient (PTG) inside the SOEC is found at the TNC, which is vital to prevent thermal failure in the operation. For the cell operating with 1023 K and 1123 K of inlet gas temperatures, the smallest PTGs reach 0.09 and 0.31 K mm−1 at 1.13 and 1.19 V, respectively. Finally, a 4-D map is presented to show the interactions among the applied voltage, required power density, inlet gas composition, and temperature under the TNC. The proposed method can be flexibly modified based on different optimisation targets for various applications in the energy sector.

Original languageEnglish
Article number113827
JournalEnergy Conversion and Management
Publication statusPublished - 15 Feb 2021


  • Artificial intelligence
  • Co-electrolysis
  • Genetic algorithm
  • Hybrid simulation
  • Renewable energy
  • Solid oxide electrolyser

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology


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