Localization of Voltage Sag Sources Using Convolutional Neural Network in IEEE 34-bus System

Abstract

The increased demand for electricity has caused several problems for traditional electrical power systems, such as voltage fluctuations and interruptions in supply. These events, power quality disturbances, cause several losses for both the concessionaire and its consumers, either by damaging appliances or interrupting their operation. Among these power quality disturbances, the voltage sag stands out for being the most frequent event, causing several losses. Therefore, it is extremely important to locate the source of these disturbances in the electrical distribution system, in order to mitigate the problem. In general, methods for locating disturbances use few electrical meters and an analysis of the characteristics of voltage and current signals, which results in the estimation of a large region as a result. This paper proposes a approach to find not a region, but the bus in the power distribution system in which the voltage sag disorder originated by using a model of deep learning.