Modular operation of co-electrolysis process for syngas production
- Process Systems Engineering
- Focus/Key Topic:
Co-electrolysis of CO2 and H2O for syngas production is one of the promising Power-to-X applications. Utilizing excess or renewable electricity, we can produce syngas with a lower carbon footprint than fossil-based routes. To this end, flexible operation (i.e., the variation of power load over time) of such a process is essential.
When the applied electric load is changed for flexible operation, the selectivities toward H2 and CO in the electrolyzer inherently vary. In other words, the H2/CO ratio in the outlet stream increases when we apply higher voltage, and vice versa. These phenomena can interrupt the operation at subsequent processes such as the CO2 separation unit due to the changes in the stream concentration.
In order to avoid such an unfavorable operation, we propose a module-based flexible operation. Since electrolyzer stacks can be operated independently, we can quickly shut down some stacks when reducing the overall power load. This novel operation can keep the outlet stream concentration constant. However, additional capital investment for overcapacity that allows for the modular operation is the main drawback. Also, we should verify whether the dynamic behavior of the downstream process for gas separation is fast enough to adopt the modular operation.
In this work, the student will develop dynamic models for the co-electrolysis process. The process employs membrane units for gas separation. Then, the student will formulate dynamic optimization problems to determine the optimal operational profile considering electricity price fluctuations.
What we expect from you:
- You should be interested in modeling and optimization
- You should be familiar with programming
- It would be nice if you have experience with Modelica, GAMS or gPROMS
- It would be nice if you have basic knowledge of electrochemistry or membrane
- You should be able to communicate in English
If you are interested in this research topic, please send your short CV and transcript to Kosan Roh (email@example.com).