A Digital Twin Platform Applied to Hydrogen Electrolyzers

Digital Twin (DT) technology emerges as a promising solution for addressing the challenges in electrolyzer operation, resulting from scalability issues, component degradation, and limited lifespan. This paper presents a service-oriented DT architecture and platform applied to an industrial-scale hydrogen electrolyzer. By effectively mimicking the behavior of the physical object, the DT enhances predictive diagnosis and supervision of its operation. Initially, a generic DT framework is realized, followed by a demonstration of its application using an electrolyzer use case. The approach combines digital the object with services, facilitating comprehensive monitoring, fostering proactive maintenance, and performance enhancements. Condition monitoring and anomaly detection strategies are implemented to enhance real-time supervision. The overarching objective of this platform is to facilitate the creation of scalable, extendable, interoperable, and dynamic DTs for electrolyzers, thereby advancing their performance and efficiency in hydrogen production systems. Moreover, the DT architecture is platform-agnostic, allowing for the seamless extension to other use cases.