It is estimated that by 2030 Germany will produce around 20 TWh of green hydrogen per year, highlighting the need for suitable storage. One possible solution is storing the hydrogen in porous underground media. In this work we analyse the reliability of such a potential storage site.
Reliability analyses typically require tens to hundreds of thousands of model evaluations for accurate results, especially when imprecise probabilities are involved due to limited data availability and input variables are modelled as intervals or probability boxes. The true model in this study has an associated runtime of around three days rendering a direct reliability analysis virtually impossible.
We use Julia to train an accurate surrogate model on which we are then able to perform our analyses. Propagating the imprecise input quantities through the surrogate model we obtain bounds on the probability of failure of the system. All algorithms used in this study are implemented in the UncertaintyQuantification package.
