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An electric energy consumer characterization framework based on data mining techniques

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4 Author(s)
V. Figueiredo ; Dept. of Electr. Eng., Polytech. Inst. of Porto, Portugal ; F. Rodrigues ; Z. Vale ; J. B. Gouveia

This paper presents an electricity consumer characterization framework based on a knowledge discovery in databases (KDD) procedure, supported by data mining (DM) techniques, applied on the different stages of the process. The core of this framework is a data mining model based on a combination of unsupervised and supervised learning techniques. Two main modules compose this framework: the load profiling module and the classification module. The load profiling module creates a set of consumer classes using a clustering operation and the representative load profiles for each class. The classification module uses this knowledge to build a classification model able to assign different consumers to the existing classes. The quality of this framework is illustrated with a case study concerning a real database of LV consumers from the Portuguese distribution company.

Published in:

IEEE Transactions on Power Systems  (Volume:20 ,  Issue: 2 )