The periodic scale feature matrix aims to explore the characteristics of photovoltaic (PV) power generation on an hourly basis, uncovering periodic features within a 24-hour cycle. Five features are calculated for each 24-hour cycle: average value, maximum value, minimum value, standard deviation, and variance of the generated power. The average value represents the central tendency of the dataset, reflecting the typical level of power generation within a given time period. The maximum value indicates the highest level of power generation during that period, while the minimum value denotes the lowest level. The standard deviation measures the extent to which values deviate from the mean, its magnitude reflecting data volatility, which is crucial for understanding power generation fluctuations within a given cycle. Variance, the average of the squared differences from the mean, similarly measures the dispersion of data points. These statistical features provide insights into the overall condition and variation trends of the power generation dataset across different time periods. The specific steps are illustrated in Figure 1.