Load profiling of residential electricity consumers using clustering methods - Cancino, Albert E. (2008)
In modern electric utility business under a deregulated industry with competitive supply market, Distribution Utilities (DUs) must know the consumption behaviour of its. Traditionally, residential customers of electric utilities are profiled based on the monthly energy (kWh) consumption and some nonelectric indicators such as the socioeconomic and demographic characteristics. This research compared four clustering techniques which are based on pattern recognition methods, including k-means, hierarchical agglomerative clustering, hybrid hiearchial agglomerative ? k means and improved k-means to derive the representative load profile of residential customers of a Distribution Utility (DU) which serves 4.1 million customers in its franchise. The best technique used for the application was based on adequacy measures such as the (a) Mean square error or error function, (b) Mean index adequacy, (c) Clustering dispersion indicator, (d) Similarity matrix indicator, (e) Davies-Bouldin indicator, (f) Ratio of within cluster sum of squares to between cluster variation. Based on the analysis, the Hierarchical Agglomerative and Hybrid Hierarchical Agglomerative - K-Means clustering exhibits better characteristics than the other clustering techniques in terms of adequacy. The chosen methodology was applied to establish residential customer consumption bracket level that are affected by the existing Time-Of-Use rates of the Distribution Utility.
Thesis (M.S. Electrical Engineering) -- University of the Philippines, Diliman.
Keywords: Electric power consumption -- Philippines; Cluster analysis; Electric utilities