Optimized Method for Locating the Source of Voltage Sags

Short-Duration Voltage Variations (SDVVs) are the power quality disturbances (PQD) that mainly affect industrial systems, and originated for various reasons, in particular short circuits over large areas, even those originating remote points of electrical system. The location problem aims to indicate area or region distance from substation is connected source causing voltage sags, a fundamental task ensure good quality. One strategies used determine sources SDVVs an implementation machine learning algorithms modern distribution networks, called Smart Grids. Monitoring Grid plays key role, however mostly it generates volume data (Big Data) as result, multiple challenges arise due properties this such volume, variety velocity. This work presents optimization through genetic algorithm select meters which already exist Grid, using sag method order reduce obtained analyzed throughout localization process. Optimization was evaluated comparison with non-optimized method, showed difference between hit rates less than 1%.