In this thesis, we explore a proposal from Stedin that advocates heating the city of Stad aan `t Haringvliet with hydrogen rather than natural gas. Switching from natural gas to hydrogen presents plenty of unknown factors which must be properly evaluated for an accurate and realistic risk picture, including the danger of running out of hydrogen. The objective of this study is to examine the security of a 100% hydrogen supply in city buildings. For this MSc thesis, the security of supply is defined as a reliable and uninterrupted supply of hydrogen for heating purposes. We explore the security of supply by evaluating the risk to it. To achieve this goal, we construct a hydrogen supply system using Stedin's criteria. The Classical Model for Structured Expert Judgement and the Bayesian Network are the two mathematical techniques we use to evaluate the risks. The lack of acceptable data makes the task of quantifying the risk to supply much more difficult in this regard. Expert opinion remains the sole trustworthy source of information in these conditions for quantifying uncertainty. However, expert opinion should be validated using objective performance measures. As a result, we adopt the Classical Model for Structured Expert Judgement. The resulting uncertainty distributions of the Structured Expert Judgement research are then integrated into a Bayesian Network that models the uncertainty within the hydrogen supply system. Bayesian Networks are an effective tool for visualizing a domain's probabilistic model, examining all random variable interactions, and inferring probability for scenarios based on available data.\ The findings of Structured Expert Judgment reveal that there will be a forecast of 114 minutes of not enough hydrogen in the buildings of Stad aan 't Haringvliet in the first year of realizing Stedin's pilot, given the event that there will be a lack of hydrogen in Stad aan `t Haringvliet. Moreover, the security of supply is expected to not be achieved with an estimated probability of 0.06839 for the first year of realizing this pilot. Furthermore, failure rates for each component of the hydrogen supply system have also been quantified using the Classical Model, and one or more mitigations have been proposed for each component. Quantifying the Bayesian Network with the distributions for each component of the hydrogen supply system that resulted from the expert judgment study, yields distinct results than experts' aggregated distributions on the estimated probability and the duration of not meeting the energy demand. The results show that the best-estimated probability for not having enough hydrogen in the buildings equals 0.2067 and when we consider the event of having a lack of hydrogen in the buildings, the best estimated time for how long this will last equals 3.135 minutes in the first year of realizing Stedin's pilot.