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-lin e fault section estimation using information of relays and circuit bre akers. This system has similar profile of an expert system, but can be constructed much more easily from elemental samples. These samples as sociate fault section with its primary, local and/or remote protective relays and breakers. The diagnostic system can be applicable to the p ower system control center for single or multiple fault sections estim ation, even in the cases of failure operation of relay and breaker, or error-existent data transmission. The proposed approach has been prac tically verified by testing on a model power system. The test results, although preliminary, suggest our system can be implemented by variou s electric utilities with relatively low customization effort.