Computational Modeling of Electrolytic Hydrogen Production: An idealized Phyton-Based Simulation Approach

Abstract

This research presents a technical and experimental analysis of the energy efficiency of alkaline electrolysis systems for hydrogen production, evaluating the impact of the voltage per cell and the number of cells on the overall performance. Through simulations in Python and tests with different configurations, an inverse trend between efficiency and voltage per cell was identified, while increasing the number of cells showed a positive effect on the overall system efficiency. The experimental results were supported with simulated efficiency plots and contour maps that allowed visualization of the optimal operating zones. The real tests showed that configurations with low voltage per cell can reach efficiencies higher than 20 %, while systems operating at 4.0 V show efficiencies lower than 13 %. It was also shown that efficiency can exceed 50% when operating with more than 150 cells at low voltage, which highlights the potential for redesigning current systems. The problem statement and its background contextualize the role of hydrogen as a key energy carrier in the transition to clean sources. It is argued that the optimization of processes such as electrolysis is critical to replace fossil fuel-based production, reduce carbon emissions and strengthen global energy security.