Algoritmos de inteligência computacional utilizados na detecção de fraudes nas redes de distribuição de energia elétrica

Abstract

One of the main problems currently faced by electric utilities is the occurrence of energy losses in the distribution network caused by fraud and electricity theft. Because of the financial losses and risks to public safety, the development of solutions to detect and combat fraud in the distribution networks is of the utmost importance. This work presents an analysis of computational intelligence algorithms to extract knowledge in databases with information from monthly energy consumption to identify consumption patterns with anomalies which could represent fraud. The algorithms Artificial Neural Networks and Support Vector Machines were tested to see which one perform better on the identification consumption patterns with abnormalities. Tests have shown that the algorithms used are able to detect patterns in electricity consumption curves, including special situations of fraud that manual techniques did not detect.