Probabilistic analysis of a fuel cell degradation model for solid oxide fuel cell and gas turbine hybrid systems

The performance of a solid oxide fuel cell (SOFC) is subject to inherent uncertainty in operational and geometrical parameters, which can cause performance variability and affect system reliability. Operating conditions such as current demand, cell temperature and fuel utilization play an important role on the degradation mechanisms, which affect typical SOFCs. In previous work, a deterministic empirical degradation model of a SOFC was developed as a function of such operating conditions. By the nature of experimental data and regression fitting, this model was not deterministic. The aim of this work is to evaluate the impact of the uncertainties in the degradation model through a stochastic analysis. In particular, the Response Sensitivity Analysis (RSA), an approximate stochastic method based on Taylor series expansion, is applied to a standalone SOFC model and a fuel cell hybrid system model both subjected to cell degradation. The attention is principally focused on the impact on the fuel cell lifetime. To provide an indication of degradation effect and resulting lifetime uncertainty on economic performance, a cursory economic analysis is performed.