Analysis of Power Load Characteristics Based on Adaptive Ensemble Clustering Algorithm

With the growing number of power users and more flexible power consumption, how to cluster the power load curves efficiently becomes particularly important. In order to improve the accuracy, effectiveness and rapidity of load clustering, an adaptive integrated fuzzy clustering algorithm was proposed in this paper. Firstly, the initial clustering centroids were obtained by the improved DPC algorithm; then, under the dual guarantee of Euclidean distance and membership, FCM algorithm was used to cluster load curves; finally, the optimal number of clusters was obtained by the improved adaptive method in the iterative process; thus, the autonomous and accurate clustering of power load curve was realized. The proposed algorithm, DPC algorithm and FCM algorithm were applied to the load clustering experiment of power system respectively. The comparative analysis shows that this algorithm is effective and superior for load curve clustering.