Investigation on coupling mechanism of safety accident risk of hydrogen energy system based on N–K model

Abstract

The rapidly growing hydrogen energy sector faces the challenge of maximizing its clean energy benefits while managing the associated safety risks. Currently, a comprehensive understanding of the interconnected risk factors contributing to accidents remains elusive, particularly impeding the formulation of robust safety measures. Here, this study addresses this gap by employing the N–K model to elucidate the formation mechanism of coupled risks in hydrogen energy systems. Firstly, the system is divided into four subsystems: human, machine, job and management, risk factors associated with safety accidents in each subsystem are analyzed. Secondly, risks are divided into three categories: single-factor, dual-factor, and multi-factor coupling. The formation mechanism of the coupling risk is analyzed based on the concept of triggers. Thirdly, utilizing the N–K model, the internal coupling relationships and their triggers are quantitatively analyzed. The hydrogen incidents and accidents database (HIAD 2.1) was used as the main source of data, and 92 accident cases with known causes were extracted from the database based on the criterion of whether there were fatal accidents, and an example study was carried out based on the N–K model. The findings of this study reveal that the probability of safety accidents is directly correlated with the magnitude of the risk coupling value, which is influenced by the number of interacting risk factors. Significantly, the machine factor emerged as the predominant determinant of risk coupling. This study highlights the necessity for hydrogen energy systems to strengthen risk prevention mechanisms, rigorously evaluate system designs, and proactively mitigate the potential for multi-factor risk couplings. Implementing these measures will significantly enhance the overall safety of hydrogen energy systems, contributing to the development of more reliable and secure energy solutions.