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The complex environment of mountain photovoltaic (PV) power plant brings great challenges to the operation and maintenance of the power plant. In order to better realize the intelligent operation and maintenance of mountain PV power plant, and we propose a method to analyze and aggregate the output curve of mountain PV power plant according to the temporal and spatial correlation. This data pre-method analyzed the correlation and difference between the series current data of the mountain PV power plant at different dates and locations. The data was reconstructed by multiple fitting and K-means clustering, and the typical day was filtered and the azimuth and inclination were divided. It can effectively solve the problem of inaccurate fault diagnosis caused by dirty actual output data of mountain PV power plants.