Hierarchical consistency tracking (HCT) model: A rapid and efficient approach for dynamic thermal analysis of alkaline water electrolysis

The intermittent power output of renewable energy sources necessitates alkaline water electrolysis (AWE) systems to operate under fluctuating conditions, emphasizing the need for a comprehensive understanding of their dynamic thermal behavior. However, current methods for dynamic thermal detection in AWE systems suffer from limitations such as limited temperature signals, insufficient temperature distribution analysis, and a lack of dynamic thermal analysis methods. To address these challenges, a hierarchical consistency tracking (HCT) model is proposed, which incorporates three hierarchical procedures: segmental characteristic temperatures (CT) extraction, surface consistency extraction, and dynamic consistency tracking. By analyzing infrared images captured from the electrolyzer, the HCT model extracts CT, quantifies temperature distribution patterns, and enables the assessment of thermal consistency during dynamic processes. This model offers a rapid and efficient approach with several advantages, including a more comprehensive understanding of temperature distribution, quantification of dynamic thermal consistency, and optimization of operating parameters and internal structures to improve temperature uniformity. Moreover, the HCT model provides a cost-effective and efficient solution for thermal characterization by eliminating the need for additional temperature sensors during dynamic operation.