Neurofuzzy implementation of digital protection for power transmission systems

Abstract

Protecting transmission lines is an important task to safeguard electric power systems. Faults on transmission lines need to be detected, classified and located accurately for speedy clearance and reclosure. In this framework the most important aspects are fast and reliable fault detection and classification. The traditional protection algorithms are based on deterministic computations on a well-defined model of the system to be protected. This results in difficulty in taking system variation into account when the rules vary. They do not have the ability to adapt dynamically to the system operating conditions, and to make correct decisions if the signals are uncertain.