par Valero Masa, Alicia ;Werben, Stefan;Maun, Jean Claude
Référence IEEE Power and Energy Society General Meeting, 6344893
Publication Publié, 2012
Référence IEEE Power and Energy Society General Meeting, 6344893
Publication Publié, 2012
Article révisé par les pairs
Résumé : | Modernizing the power distribution system implies improving the reliability and performance of protection devices. By incorporating data-mining in the process of designing protection functions, the limits of performance are extended. We propose a method that uses data-mining, able to detect high impedance faults (HIFs) in multi-grounded distribution networks when conventional devices are insufficient. HIFs are produced when overhead lines contact a quasi-isolated surface, such as a tree or the ground. The fault current can be lower than the residual current under normal conditions; hence overcurrent devices do not detect this fault. We describe a set of indicators that characterize HIFs and that can be used in data-mining to distinguish fault situations from other situations. The result is a HIF detection function whose development is based on pattern recognition analysis. The presented methodology can be applied to other fault detection problems to achieve more reliable protection devices. © 2012 IEEE. |