Uma metodologia de diagnóstico de distúrbios em sistemas de distribuição baseada nos sinais de corrente

Abstract

With a growth in demand for electrical energy, it is noticed that the Brazilian power system tends to become more complex, as well as more susceptible to the occurrence of various types of failures. Disturbances that cause interruptions in the power supply, for example, are monitored daily through regulations on energy distribution services. However, there is still a need to automate the distribution systems so their equipment, such as automatic reclosers, act swiftly, safely and effectively during the disturbance classification processes. With the information stemming from the identification and classification of disturbances, the electric power companies can act to minimize their frequency of occurrence. In order to achieve this objective, this work presents a set of methods able to classify certain disturbances and faults in the distribution system - short circuits, inrush current, connection of large loads, harmonic distortion, current unbalance and frequency variation - based only on the analysis of the behavior of current signal oscillographs. This classification occurs through the segmentation of the signals employing, mostly the discrete wavelet transform, via multiresolution analysis. Other techniques, such as the Fourier transform and the ordinary least squares, are used in the background in order to assist in some decisions. A database with 510 synthetic signals (simulated in a test system, parameterized with real data from a distribution system and built in the Alternative Transients Program software), and 41 real currents signals from short-circuit have been applied in order to validate the methods. The results indicate to feasibility of using the algorithm as a tool for classifying disturbances.