ANALYSIS OF POWER TRANSFORMER FAILURE IN OGBOMOSO SUB-STATION OF IBADAN ELECTRICITY DISTRIBUTION COMPANY
Abstract
A modern electric power system is a very large and complex network consisting of generators, power transformers, transmission lines, distribution lines, and other devices. Power transformer is one of the most important electricity equipment in power system. It plays important roles both in transmission and in distribution system. Power transformer condition should be maintained because of its importance in electricity network. There is an increasing need for better diagnostic and monitoring tools to assess the condition of transformers. Many monitoring, testing and condition assessment techniques have been used. By means of statistical failure analysis, the ageing processes related to the ages of the transformer can be shown. The failure data is fitted with mathematical and statistical distribution and the accompanying parameter can be estimated. This research paper presented the analysis of power transformer failure in Ogbomoso Sub-station of Ibadan Electricity Distribution Company (IBEDC). Statistically linked mathematical equations were formulated for the analysis of power transformer failure in Ogbomoso Sub-station.in order to predict the future failure of power transformer previously installed and the existing one to be installed. The results of the analysis showed that the failure of power transformer increased with ageing and that the failure of transformer could be represented by Weibull distribution. For most transformers, the empirical Cumulative frequency ( ) versus Age (t) on the weibull probability exhibited a remarkable linearity. The results obtained from this analysis will form a useful basis for power system engineers in order to predict the failure of power transformers in future and to put in place, adequate and appropriate maintenance strategies for the equipment.
Keywords: Complex Network, Electric Power, Transmission Line, Distribution Lines, Power Transformer, Statistical Failure Analysis, Ageing Processes.
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ISSN (Paper)2224-5804 ISSN (Online)2225-0522
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