Data Mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of medium voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, data mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.