Transformer health assessment using neuro fuzzy based reasoning

Abstract

Generally transformer is an essential component in a power system newlineand any failure of it can cause enormous loss for society. Hence, healthiness newlineand reliability of power transformer has been a concern for substation newlineengineers. Timely or early identification of developing faults in them lessens newlinethe unplanned power outages and betters the dependability of power and newlineservices to the consumer. Many attempts are made during the past few years newlineto work out techniques for transformer health assessment. There are key newlinediagnostic measurements to show the status of a transformer. These newlinemeasurements incorporate insulation properties, temperature, water in oil, newlinepartial discharge, acoustic signature, Dissolved Gas Analysis (DGA), and newlineload voltage and current. Among those measurements, DGA is a universal newlinetechnique for the assessment of overall health of a transformer. DGA includes extracting dissolved gasses within oil and analyzing them for its composition using gas chromatograph. Online monitoring systems also are used to measure the dissolved gases in the oil. Ethylene (C2H4), Hydrogen (H2), acetylene (C2H2), methane (CH4), ethane (C2H6), CO (carbon monoxide), and CO2 (carbon dioxide) are the typical gases generated newlineinside the transformer. newline newline