Master Thesis – Data-Driven System Identification for Dynamic Modeling of rSOC-Systems

A promising technology investigated at the Institute of Energy Technologies - Fundamental Electrochemistry (IET-1) is the reversible Solid Oxide Cell (rSOC), which enables the efficient conversion of electrical energy into hydrogen and vice versa. Coupled with renewable energy sources such as solar and wind power, rSOC systems play an important role in future sustainable energy infrastructures. However, the fluctuating nature of renewable generation subjects these systems to dynamic operating conditions, creating significant challenges for control, efficiency, and long-term durability.

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In previous projects, a detailed dynamic model of the system was developed based on first-principle (white-box) approaches. While such models provide valuable insight, advanced model-based control methods such as Model Predictive Control (MPC) are often limited by discrepancies between...