Model-Based Analysis and Optimization of Pressurized Alkaline Water Electrolysis Powered by Renewable Energy

Alkaline water electrolysis is a key technology for large-scale hydrogen production. In this process, safety and efficiency are among the most essential requirements. Hence, optimization strategies must consider both aspects. While experimental optimization studies are the most accurate solution, model-based approaches are more cost and time-efficient. However, validated process models are needed, which consider all important influences and effects of complete alkaline water electrolysis systems. This study presents a dynamic process model for a pressurized alkaline water electrolyzer, consisting of four submodels to describe the system behavior regarding gas contamination, electrolyte concentration, cell potential, and temperature. Experimental data from a lab-scale alkaline water electrolysis system was used to validate the model, which could then be used to analyze and optimize pressurized alkaline water electrolysis. While steady-state and dynamic solutions were analyzed for typical operating conditions to determine the influence of the process variables, a dynamic optimization study was carried out to optimize an electrolyte flow mode switching pattern. Moreover, the simulation results could help to understand the impact of each process variable and to develop intelligent concepts for process optimization.