To solve the problem that the clustering results of traditional single clustering algorithm is unsteady and the reliability of load pattern extraction is low, a new method of pattern classification based on the technology of principal component analysis and clustering ensemble approaches is presented. First, principal component analysis is used in the process of data preprocessing to reduce information redundancy of high-dimension feature vectors. Then, different clustering members are obtained by four cluster analyses of feature vectors. Finally, the clustering members are combined with the Co-association Matrix and the clustering result is better than single clustering algorithm. The clustering results of principal component analysis and ensemble clustering algorithm achieved by electricity consumption data show that it can effectively improve the accuracy of clustering and reduce computation complexity. The evaluation indicator of Silhouette is used to assess the clusters of load profiles.
