Methodology for information extraction from oscillograms and its application for high-impedance faults analysis. (March 2016)

• Record Type: Journal Article
• Authors: Batista, Oureste Elias; Flauzino, Rogério Andrade; de Araujo, Marcel Ayres; de Moraes, Lucas Assis; da Silva, Ivan Nunes
• Is Part Of: International journal of electrical power & energy systems. Volume 76(2016:Mar.)
• Page Start: 23
• Page End: 34
• Publication Date: 2016-03
• Subjects: Power system analysis -- Fault diagnosis -- Oscillogram analysis -- High-impedance faults -- Power distribution faults -- Information extraction; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.09.019
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The methodology helps locate and identify Single Line-to-Ground (SLG) faults. The technique does not make use of a previously established basis set. More than 80% correlation with the occurrence of high impedance fault. Almost 70% correlation with the location of high impedance fault. Great immunity to the fault resistance effect. Abstract: Safety and quality of supply represent targets that power distribution companies always strive to meet. Among those occurrences that can have simultaneous deleterious effects on both these targets, High-Impedance Faults (HIFs) stand out since the magnitudes of the effects on the system are too small to activate the relevant system protection devices. In this context, the main aim of this article is to present a new mathematical method for analysis of power systems transient events. This technique was used in the pre-processing of signals to help locate and identify Single Line-to-Ground (SLG) faults. The orthogonal component decomposition technique was tested qualitatively with the help of a real fault oscillogram recorded at a power distribution substation. Computer simulations based on a real distribution feeder model were performed and the numerical results showed that decomposition by Orthogonal Components was able to extract information with more than 80% correlation with the fault occurrence, almost 70% for the location and showed great immunity to the fault resistance effect.