2024 AIChE Annual Meeting

(116e) Process Modeling and Operability Analysis for the Optimization of a Proton-Conducting Solid Oxide Electrolyzer for Green Hydrogen Production

Authors

Li, W., West Virginia University
Lima, F., West Virginia University
Hydrogen stands out as the most effective energy carrier[1], with the ability to be sourced from various raw materials, including water. Among the several methods of hydrogen production, water electrolysis emerges as an eco-friendly approach, offering high purity hydrogen as a product. Particularly, solid oxide electrolysis is deemed the most promising technique for efficiently producing hydrogen using renewable energy sources. This technology has the advantage of emitting only oxygen as a byproduct, thereby minimizing carbon emissions. The hydrogen and oxygen produced can then be directly utilized in fuel cells and other industrial applications. Despite its sustainability advantages, water electrolysis accounts for a mere 4% of global industrial hydrogen production, largely due to economic constraints[1].

In this work, an electrochemical model is developed to examine the current and voltage (J-V) characteristics of a solid oxide electrolyzer cell using a proton-conducting electrolyte (H-SOEC) for generating hydrogen. The developed model accounts for critical overpotentials such as activation, concentration, and ohmic overpotentials. Validation of the model was achieved through close alignment between simulation outcomes and experimental data sourced from literature[2,3]. This modeling study is conducted in Python, where overpotentials are simulated for different temperatures and current densities. Then considerations for voltage efficiency and production of hydrogen in each case are analyzed for further optimization using the Process Operability framework[4,5].


In particular, the operability framework[4,5] provides the mapping of the feasible regions of operation for the scenarios proposed, taking into consideration the available inputs while seeking to maintain the process within desired voltage efficiency and net-negative carbon emission goals. The produced input-output mappings by operability also serve to quantify process feasibility and control aspects[6]. Therefore, this work is expected to provide better understanding of the proton conducting solid oxide electrolyzer for the hydrogen production process bounds, toward facilitating the overall process design and improved efficiency.

References:

[1] Kamlungsua, K., Su, P.-.-C. and Chan, S.H. (2020), Hydrogen Generation Using Solid Oxide Electrolysis Cells. Fuel Cells, 20: 644-649. https://doi.org/10.1002/fuce.202070602

[2] Meng Ni, Michael K.H. Leung, Dennis Y.C. Leung, Electrochemical modeling of hydrogen production by proton-conducting solid oxide steam electrolyzer, International Journal of Hydrogen Energy, Volume 33, Issue 15, 2008, Pages 4040-4047, ISSN 0360-3199, https://doi.org/10.1016/j.ijhydene.2008.05.065.

[3] Wang, Y., Zu, B., Zhan, R., Du, Q., Ni, M., & Jiao, K. (Accepted/In press). Three-dimensional Modeling and Performance Optimization of Proton Conducting Solid Oxide Electrolysis Cell. Fuel Cells. https://doi.org/10.1002/fuce.201900246

[4] Gazzaneo, V., Lima, F. V. Multilayer Operability Framework for Process Design, Intensification, and Modularization of Nonlinear Energy Systems. Ind. Eng. Chem. Res. 2019. https://doi.org/10.1021/acs.iecr.8b05482.

[5] Alves, V., Dinh, S., Kitchin, J. R., Gazzaneo, V., Carrasco, J. C., & Lima, F. V. (2024). Opyrability: A Python package for process operability analysis. Journal of Open Source Software, 9(94), 5966. https://doi.org/10.21105/joss.05966

[6] Gazzaneo, V., Carrasco, J. C., Vinson, D. R., & Lima, F. V. (2020). Process Operability Algorithms: Past, Present, and Future Developments. Industrial & Engineering Chemistry Research, 59(6), 2457–2470. https://doi:10.1021/acs.iecr.9b05181