Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction
The Solid Oxide Electrolyser Cell (SOEC) offers high-efficiency hydrogen production due to favourable thermodynamics and reaction kinetics at elevated temperatures. However, high operating temperatures increase energy consumption and thermal gradients, leading to material degradation and reduced dur...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
|
| Series: | International Journal of Sustainable Energy |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/14786451.2025.2482837 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850094154688757760 |
|---|---|
| author | Syafawati Hasbi Ityona Amber Mamdud Hossain Mohd Shahneel Saharudin |
| author_facet | Syafawati Hasbi Ityona Amber Mamdud Hossain Mohd Shahneel Saharudin |
| author_sort | Syafawati Hasbi |
| collection | DOAJ |
| description | The Solid Oxide Electrolyser Cell (SOEC) offers high-efficiency hydrogen production due to favourable thermodynamics and reaction kinetics at elevated temperatures. However, high operating temperatures increase energy consumption and thermal gradients, leading to material degradation and reduced durability. This study optimises SOEC operating conditions to minimise thermal gradients and enhance performance using numerical simulations and Response Surface Methodology (RSM). Key parameters examined include voltage (1.1–1.5 V), temperature (1073–1273 K), steam mass fraction (0.3–0.9), flow configurations, porosity, and charge transfer coefficients. Results show increasing voltage from 1.1 to 1.5 V raised current density from 0.75 A/cm² to 2.5 A/cm², while thermal gradients increased up to 15 K at higher temperatures. Counterflow configurations caused mid-cell hotspots, whereas parallel flow produced thermal gradient near the outlet. RSM optimisation identified optimal conditions of 1073, 1.5 V, and 0.9 steam mass fraction, reducing hotspot temperatures to 1086 K with minimal deviation. These findings support improved SOEC thermal management and hydrogen production efficiency. |
| format | Article |
| id | doaj-art-1d04a4f2fd1048d5b720fe5980dd2bf4 |
| institution | DOAJ |
| issn | 1478-6451 1478-646X |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Energy |
| spelling | doaj-art-1d04a4f2fd1048d5b720fe5980dd2bf42025-08-20T02:41:43ZengTaylor & Francis GroupInternational Journal of Sustainable Energy1478-64511478-646X2025-12-0144110.1080/14786451.2025.2482837Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reductionSyafawati Hasbi0Ityona Amber1Mamdud Hossain2Mohd Shahneel Saharudin3School of Computing and Engineering Technology, Robert Gordon University, Aberdeen, UKSchool of Computing and Engineering Technology, Robert Gordon University, Aberdeen, UKSchool of Computing and Engineering Technology, Robert Gordon University, Aberdeen, UKSchool of Computing and Engineering Technology, Robert Gordon University, Aberdeen, UKThe Solid Oxide Electrolyser Cell (SOEC) offers high-efficiency hydrogen production due to favourable thermodynamics and reaction kinetics at elevated temperatures. However, high operating temperatures increase energy consumption and thermal gradients, leading to material degradation and reduced durability. This study optimises SOEC operating conditions to minimise thermal gradients and enhance performance using numerical simulations and Response Surface Methodology (RSM). Key parameters examined include voltage (1.1–1.5 V), temperature (1073–1273 K), steam mass fraction (0.3–0.9), flow configurations, porosity, and charge transfer coefficients. Results show increasing voltage from 1.1 to 1.5 V raised current density from 0.75 A/cm² to 2.5 A/cm², while thermal gradients increased up to 15 K at higher temperatures. Counterflow configurations caused mid-cell hotspots, whereas parallel flow produced thermal gradient near the outlet. RSM optimisation identified optimal conditions of 1073, 1.5 V, and 0.9 steam mass fraction, reducing hotspot temperatures to 1086 K with minimal deviation. These findings support improved SOEC thermal management and hydrogen production efficiency.https://www.tandfonline.com/doi/10.1080/14786451.2025.2482837Solid oxide electrolyser cellresponse surface methodsgreen hydrogen productioncomputational fluid dynamicsthermal gradient optimisation |
| spellingShingle | Syafawati Hasbi Ityona Amber Mamdud Hossain Mohd Shahneel Saharudin Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction International Journal of Sustainable Energy Solid oxide electrolyser cell response surface methods green hydrogen production computational fluid dynamics thermal gradient optimisation |
| title | Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction |
| title_full | Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction |
| title_fullStr | Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction |
| title_full_unstemmed | Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction |
| title_short | Performance optimisation of solid oxide electrolyser cell (SOEC) using response surface method (RSM) for thermal gradient reduction |
| title_sort | performance optimisation of solid oxide electrolyser cell soec using response surface method rsm for thermal gradient reduction |
| topic | Solid oxide electrolyser cell response surface methods green hydrogen production computational fluid dynamics thermal gradient optimisation |
| url | https://www.tandfonline.com/doi/10.1080/14786451.2025.2482837 |
| work_keys_str_mv | AT syafawatihasbi performanceoptimisationofsolidoxideelectrolysercellsoecusingresponsesurfacemethodrsmforthermalgradientreduction AT ityonaamber performanceoptimisationofsolidoxideelectrolysercellsoecusingresponsesurfacemethodrsmforthermalgradientreduction AT mamdudhossain performanceoptimisationofsolidoxideelectrolysercellsoecusingresponsesurfacemethodrsmforthermalgradientreduction AT mohdshahneelsaharudin performanceoptimisationofsolidoxideelectrolysercellsoecusingresponsesurfacemethodrsmforthermalgradientreduction |