Detecção de fraudes no consumo de energia elétrica usando árvores de decisão

Abstract

In recent years, the injury caused by the nontechnical losses to power distribution utilities, in Brazil have been estimated at R$ 7 billion per year. This reality represents a challenge for some of country’s utilities, who need effective measures to combat commercial losses. In this scenario, this dissertation presents a methodology able of detecting fraud in the consumption of electric energy, using a technique of data mining, known as decision tree. Performance tests of the method were done using real data from the history of electricity consumption and the inspection of consumer units (CU’s) suspected of being irregular in the metropolitan region of Belém. The results showed that the proposed decision-tree based method performs well in the detection of fraud in the electric power consumption.