POWER TRANSFORMER FAULTS IDENTIFICATION USING FUZZY BASED DISSOLVED GAS ANALYSIS METHOD

Abstract

Power system reliability depends on the consistency of electrical equipment. Power transformer is one of the most important equipment in electrical power system due to its cost and failure consequence. Dissolved Gas Analysis (DGA) is a sensitive and reliable technique for the detection of incipient fault condition of transformer by monitoring and quantifying the presence of certain key gases like hydrogen, methane, ethane, ethylene and acetylene in its oil. This paper proposes the Fuzzy Roger system for detection of faults from Hydrocarbon gas data collected from Dissolved Gas Analysis of power transformers. The gas ratios and relative proportions of gases are used to diagnose the fault. Fuzzy Roger based diagnosis system is insensitive to errors in the oil sampling, storage and testing processes. Output of Fuzzy Rogers method is compared with conventional method. The computational efficiency, reliability and success rate of proposed method is presented. Result shows that Fuzzy Rogers method is found to be more reliable and efficient for transformer fault diagnosis.