par Valero Masa, Alicia ;Werben, Stefan;Maun, Jean Claude
Référence (22-26 July 2012: San Diego, CA USA), Power and Energy Society General Meeting 2012 IEEE, I.E.E.E., page (1-8)
Publication Publié, 2012-07-23
Publication dans des actes
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.