Optimization of alkaline electrolyzer operation in renewable energy power systems: A universal modeling approach for enhanced hydrogen production efficiency and cost-effectiveness.

This study presents a comprehensive analysis of an Alkaline Water Electrolysis System (AWES) for hydrogen production, focusing on thermal balance, operating conditions, efficiency, and lifecycle cost. A thermal balance model was developed and further refined using machine learning techniques based on experimental data, to accurately calculate electrolysis power, cooling requirements, and temperature maintenance, enabling cost-effective operation. This study provides insights for optimizing AWES performance and economic feasibility in hydrogen production. Selecting appropriate operating conditions considering current density, inlet temperature, and electricity price is crucial. Implementing these optimizations improves energy efficiency, reduces lifecycle hydrogen production costs, and enables integration with renewable energy systems. • An overall understanding of the alkaline electrolyzer operating conditions and performance is provided. • A universal modeling method based on thermal-balance model for operation optimization is proposed. • Machine learning approach is applied to calibrate model accuracy. • Mapping of hydrogen production efficiency and cost effectiveness is produced for full operation range. [ABSTRACT FROM AUTHOR]