A temperature-dependent fire risk assessment framework for solar photovoltaic station

Author：Song, Y (Song, Ye); Zou, SK (Zou, Shaokun); Dong, QC (Dong, Qichang) ; Huang, L (Huang, Lin); Song, ZH (Song, Zihao); Yang, H (Yang, Hui); Shi, L (Shi, Long) 

Journal：Sustainable Energy Technologies and Assessments

DOI:  10.1016/j.seta.2023.103467

Keywords: cloud, reliability, model

Abstract: 

Since solar photovoltaic (PV) stations are experiencing rapid growth, their potential fire risk needs to be studied as a priority to avoid catastrophic consequences. This study developed a temperature-dependent fire risk assessment framework and applied it to a typical solar PV station. To overcome the challenges of lacking probabilities and subjective judgment, the overall fire risk of a solar PV station was calculated by combining fault tree analysis, Cloud-Analytic Hierarchy Process and Weighted Average Cloud Aggregation algorithms. Additionally, as an innovative part of the developed framework, an information diffusion technique was introduced to quantify the impacts of air temperature on the probability of those influencing events and the solar PV fire spread risk. It was known that high ambient temperatures and solar radiations, which lead to overheating and installation error of solar PV modules, are the important causes of fire incidents. The results showed that influences of the air temperatures cannot be ignored as certain basic events' probabilities are affected. The occurrence possibility of installation error decreases with increasing air temperature and then increases with a higher air temperature, whose trend is validated by previous experiments. After synthesizing the impacts, the trend of the fire spread risk considering different air temperatures was quantified, showing the lowest risk at an air temperature of 10 degrees C. The developed framework of this study presents a new perspective for future dynamic risk assessment of those scenarios under changing environmental and other conditions.