Estimation of voltage sags patterns with k-means algorithm and clustering of fault zones in high and medium voltage grids

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Autor principal: Miguel Romero
Formato: Artículo científico
Lenguaje:en
Publicado: Universidad Nacional de Colombia 2011
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author Miguel Romero
author_facet Miguel Romero
contents Estimation of voltage sags patterns with k-means algorithm and clustering of fault zones in high and medium voltage grids Miguel Romero Luis Gallego Andrés Pavas Ingeniería means algorithm Sags classification patterns voltage sags This paper proposes k-means clustering algorithm to identify voltage sags patterns and group fault zones with similar impact in high and medium voltage electric. The proposed methodology comprises three stages. First, network modeling and faults simulation were performed in order to get information about voltage sags caused by faults in the transmission system. Voltage sags patterns were identified at the second stage by means of a k-means clustering algorithm, allowing the determination of fault zones. Using the power quality measurements data base of the major electricity utility of Bogotá, voltage sags were classified according to the previously determined voltage sags patterns. At the third stage of the methodology a comparison between simulated and measured sags is performed, allowing the identification of sags caused by faults. 2011 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64322338020 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.31
format Artículo científico
id redalyc_64322338020
institution Redalyc
language en
publishDate 2011
publisher Universidad Nacional de Colombia
spellingShingle Estimation of voltage sags patterns with k-means algorithm and clustering of fault zones in high and medium voltage grids
Miguel Romero
Ingeniería
means algorithm
Sags classification
patterns voltage sags
Estimation of voltage sags patterns with k-means algorithm and clustering of fault zones in high and medium voltage grids Miguel Romero Luis Gallego Andrés Pavas Ingeniería means algorithm Sags classification patterns voltage sags This paper proposes k-means clustering algorithm to identify voltage sags patterns and group fault zones with similar impact in high and medium voltage electric. The proposed methodology comprises three stages. First, network modeling and faults simulation were performed in order to get information about voltage sags caused by faults in the transmission system. Voltage sags patterns were identified at the second stage by means of a k-means clustering algorithm, allowing the determination of fault zones. Using the power quality measurements data base of the major electricity utility of Bogotá, voltage sags were classified according to the previously determined voltage sags patterns. At the third stage of the methodology a comparison between simulated and measured sags is performed, allowing the identification of sags caused by faults. 2011 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64322338020 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.31
title Estimation of voltage sags patterns with k-means algorithm and clustering of fault zones in high and medium voltage grids
topic Ingeniería
means algorithm
Sags classification
patterns voltage sags
url https://www.redalyc.org/articulo.oa?id=64322338020