Ramos, SérgioDuarte, JoãoDuarte, F. JorgeVale, ZitaFaria, Pedro2015-05-042015-05-042013-04http://hdl.handle.net/10400.22/5901This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.engData miningClusteringSmart GridTypical load profilesconference object10.1109/ISGT-LA.2013.6554489