High impedance faults (HIFs) present great difficulty of identification and location in distribution networks (DN) due to their characteristics of low current magnitude. Advances in smart grids and distribution automation allow the detection of disturbances that were previously unnoticeable in DN. This work aims to present a new method for detection and location of HIFs from smart meters placed at strategic points in the feeder, using a voltage unbalance based approach. The methodology was evaluated through simulations in MATLAB / Simulink, focusing on the detection of high impedance series faults. The results showed that the algorithm effectively identifies broken conductors, with or without ground faults, located either at the load or source side. Once technical and economic feasibility is proven, these methods can assist energy distribution utilities in restoring the normal operating conditions of the distribution network.
methodology that brings more consistent results. Abstrad--This paper proposes an alternative methodology for the characterization of industrial process sensitivity to voltage sags using a power quality (PQ) monitoring system. Several methodologies have been used for voltage sag characterization as can be seen in the literature. The load behavior is classified Considering that PQ monitors do not characterize voltage for each event registered by PQ monitors. Several sags with the methodologies applied in this research, it is characterization methods are analyzed to Select the most required that PQ monitors supply waveform data. MSExcel has consistent methodology for the characterization Of load been used to develop further event characterization with sensitivity.waveform data.
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