Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 230, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2021.113827
Keywords
Solid oxide electrolyser; Co-electrolysis; Renewable energy; Artificial intelligence; Genetic algorithm; Hybrid simulation
Categories
Funding
- Research Grant Council, University Grant Committee, Hong Kong SAR [PolyU 152214/17E, PolyU 152064/18E]
- Royal Society [NAF\R1\180146]
- CAS Pioneer Hundred Talents Program [KJ 2090130001]
- USTC Research Funds of the Double First-Class Initiative [YD 2090002006]
- Natural Science Foundation of China [21673062]
- USTC
Ask authors/readers for more resources
A hybrid simulation method is proposed for the accurate and fast optimization of the co-electrolysis process in SOECs, with a focus on thermal-neutral condition as the target. The smallest peak-temperature-gradients inside the SOEC are found to be crucial for preventing thermal failure in operation at the thermal-neutral condition.
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 multiphysics 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available