Fire Risk Assessment Method of Energy Storage Power Station Based on Cloud Model

Abstract

In response to the randomness and uncertainty of the fire hazards in energy storage power stations, this study introduces the cloud model theory. Six factors, including battery type, service life, external stimuli, power station scale, monitoring methods, and firefighting equipment, are selected as the risk assessment set. The risks are divided into five levels. Membership function is constructed using cloud model. The forward generator is responsible for calculating the complete coefficient matrix and the comprehensive evaluation matrix, while the reverse generator handles the same calculations separately. By utilizing fuzzy synthesis operators and cloud computing, the numerical attributes of the evaluation cloud model are derived, resulting in the creation of a visual representation that illustrates the fire hazard level for energy storage power stations. The results show that the cloud model can be used for fire risk assessment in energy storage power stations. Fuzzy variables can be accurately and clearly represented and corresponded to different safety levels. The effectiveness and feasibility of this assessment method have been verified through case analysis.