Multi-type Loads Characteristics Analysis Based on PCA-K-means Model in Extreme Weather

To effectively analyze multi-type loads characteristics in extreme weather scenarios, a multi-type loads characteristics analysis method based on principal component analysis (PCA) and K-means clustering algorithm (PCA-K-means) model is proposed in this paper. Meteorological indicators were downscaled by PCA. The principal component with the most significant impact on the load is identified through correlation analysis and used to construct the principal component index. Integrating the principal component index and K-means clustering algorithm, the load data in extreme weather scenarios are clustered to form figures of multi-type loads associated with features, and the load characteristics are analyzed. The validity of the model is verified by arithmetic examples.