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The presence of moisture in oil impregnated paper insulation (OIP) is detrimental to its long time performance. Until recently, it was thought insulation ageing was only a function of temperature and electrical stress. It has now been realized that moisture in all its forms causes rapid degradation of the electrical and mechanical properties with time. In this study, insulation paper samples were conditioned for desired level of moisture and were impregnated with premium quality transformer oil. The oil impregnated samples with 1 to 3 % moisture content were aged at 90 to 130°C. The indices for determining the extent of ageing considered in this work are degree of polymerization (DP), furan, carbon monoxide and carbon dioxide content. These quantities were monitored throughout the ageing experimental run. End-of-life (EOL) criterion used here is the reduction in the value of DP. Phenomenological models for estimating the service life of insulation are proposed and are validated against actual experimental data.

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Inadvertent failure of power transformers has serious consequences on the power system reliability, economics and the revenue accrual. Insulation is the weakest link in the power transformer prompting periodic inspection of the status of insulation at different points in time. A close Monitoring of the electrical, chemical and such other properties on insulation as are sensitive to the amount of time-dependent degradation becomes mandatory to judge the status of the equipment. Data-driven Diagnostic Testing and Condition Monitoring (DTCM) specific to power transformer is the aspect in focus. Authors develop a Monte Carlo approach for augmenting the rather scanty experimental data normally acquired using Proto-types of power transformers. Also described is a validation procedure for estimating the accuracy of the Model so developed.