This paper employs the gray correlation analysis method to compute the correlation between irradiance, ambient temperature, wind speed, and photovoltaic power generation efficiency. This method relies on screened data for data normalization, and after processing, it determines the degree of similarity between the factors. We propose a dynamic combined maintenance strategy for PV power generation systems that considers reliability, overhaul resources, and overhaul time constraints. We propose a two-layer optimization strategy based on extreme weather factors and failure-related characteristics, and we use empirical analysis to investigate the maintenance strategy’s effectiveness. The analysis reveals a positive correlation between irradiance and PV power generation efficiency, with a multiplicative increase in the range of 1-3. In the correlation analysis of ambient temperature and wind speed variables, the power generation curve is not consistent with its trend, which is related to the influence of extreme temperature and extreme wind speed, and the meteorological factors affecting the PV power generation efficiency change at different moments of the day, where the correlation coefficient at 6:45 is 0.912. When the failure correlation strength increases to a value of 0.1, the number of repairs rises to 8. When the weather accessibility ratio is 0.2, the reduction in system availability is up to 62%. The two-layer optimization strategy, which considers extreme weather factors and failure-related characteristics, is both economical and universal.