RESEARCH INTEGRATING ARTIFICIAL INTELLIGENCE (AI) - NEURAL NETWORK IN THE SCADA OF TRANSFORMER STATION TO DIAGNOSE INCIPIENT FAULTS

Abstract

Power transformer incipient faults are diagnosed by different methods (online). Dissolved gas analysis (DGA) is one of widely used methods. Based on DGA and combination of analysis of online circuit parameters with artificial neural networks integrated in the SCADA software of transformer station might improve possibility of diagnosis power transformer incipient faults