A risk decision support model for hydrogen refueling stations based on cloud-analytic hierarchy process

Abstract

With the rapid development of the hydrogen energy industry and the vigorous promotion of the application of hydrogen fuel cell vehicles, hydrogen refueling station (HRS) has gradually penetrated into cities, mostly built in densely populated areas. Once leakage, fire, and/or explosion accident occurs, it is highly likely to cause casualties, property damage, and environmental pollution. In order to avoid HRS risks, this paper establishes a risk decision support model based on Cloud-Analytic Hierarchy Process for HRS. Firstly, the static and dynamic features of HRS emergency plan selection are analyzed, and the weight coefficient of each feature is determined by using the cloud analysis hierarchy process. Then, the case-based reasoning theory and the weighted Euclidean distance based on the cloud model are used to establish a decision support model based on emergency plan optimization. Finally, taking the HRS hydrogen storage tank fire as an example, the risk decision support model based on the cloud analysis hierarchical process is applied to form the optimal scheme of the HRS hydrogen storage tank fire emergency plan. The results show that the weighted Euclidean distance scheme selection method based on cloud model can be effectively combined with the weight acquisition method based on cloud analysis hierarchy process to provide decision support for HRS emergency risk management and control.