Application of clustering analysis in typical power consumption profile analysis
Peng Xian-gan · Power System Protection and Control · 2014
In order to gain the large power customers' typical power consumption profiles in a power supply area, a new clustering evaluation method is presented and a clustering analysis framework based on k-means, k-medoids, self-organized maps(SOM) and Fuzzy C-Means(FCM) is built. It analyzes the characteristic of the electricity consumption data and uses the Gaussian smoothing method to reduce the noise in the data. Clusters average radius, clusters average diameter and clusters average minimum distance are proposed and used to design the clustering evaluation method. This framework is utilized to analyze the daily electricity consumption curves of the whole customers in a certain area, which can automatically recognize the number of clusters. The result shows this methodology is clear in physical conception, simple and practical.