A NEW NEURAL NETWORKS APPROACH TO ONLINE FAULT SECTION ESTIMATION USING INFORMATION OF PROTECTIVE RELAYS AND CIRCUIT-BREAKERS

This paper proposes a new Neural Networks Diagnostic System for on-line fault section estimation using information of relays and circuit breakers. This system has similar profile of an expert system, but can be constructed much more easily from elemental samples. These samples associate fault section with its primary, local and/or remote protective relays and breakers. The diagnostic system can be applicable to the power system control center for single or multiple fault sections estimation, even in the cases of failure operation of relay and breaker, or error-existent data transmission. The proposed approach has been practically verified by testing on a model power system. The test results, although preliminary, suggest our system can be implemented by various electric utilities with relatively low customization effort.