Developing a new framework for techno-economic hydrogen energy risk management through probabilistic R.Graph

In the quest for sustainable energy, hydrogen stands out as a green energy vector. However, its adoption is hindered by safety, environmental, and efficiency challenges due to the risks of hydrogen leakage. Traditional risk management methods in the literature show limitations, especially when assessing continuous variables and the probabilistic nature of risks. To bridge this gap, this paper introduces the Probabilistic R.Graph method—an enhancement of the deterministic R.Graph model. This novel approach excels in quantitative risk management, enabling a more nuanced assessment of risks by factoring in continuous variables and probabilities. It assists in assessing the economic, safety, and environmental consequences of risks, recognizing the acceptable levels of risk for decision-makers through a straightforward and understandable cause-and-effect diagram. Applied to a steam-reforming hydrogen generation unit, the Probabilistic R.Graph method helped categorize leakage scenarios in the low, medium, and high and assess their cascading effects on safety, economy, and environment. It enabled the identification of preventive measures that are both effective and economical, such as pressure relief valves. The method proved particularly valuable in prioritizing safety risks like health injuries and fatalities due to their greater severity over other considerations like economic loss. This paper validates the method's practicality in real-world settings, especially for enhancing safety and sustainability in hydrogen energy systems.