Refining SOFC Performance: Parameter Estimation and Model Validation for Dynamic Energy System Optimization

As environmental concerns intensify and energy demand rises, the global quest for sustainable energy sources becomes crucial. Given the intermittent nature of renewable electricity, the quest for transient solutions becomes imperative to ensure energy security. Solid oxide fuel cell (SOFC) stands out as a promising technology, characterized by its high electrical efficiency, fuel flexibility, and the capability for co-producing heat. Integrating SOFC into an energy system necessitates a dynamic model capable of handling fluctuations in electricity demand profiles. This underscores the significance of a reliable and reusable SOFC dynamic model. The present study focuses on constructing a detailed electrochemical SOFC stack model using gPROMS. Laboratory data is employed to perform model validation after mathematical pre-treatment. Furthermore, a sensitivity analysis was employed to select the most crucial parameters. Subsequently, parameter estimation was executed by minimizing the likelihood function. To assess the proximity between model predictions and experimental data and to evaluate the potential reuse of the model based on estimated parameter values, statistical analysis incorporated goodness of fit and t-test measures was performed.