8. Remaining Life Analysis

Generally, the life of a transformer is equated to the life of its cellulose insulation. In other words, the aging of cellulose insulation determines the ultimate life of a transformer. It has been established that thermal degradation of cellulose insulation like paper and pressboard eventually limit transformer lifetimes. In order to develop a model for predicting life expectancy of oil-immersed transformers, it is necessary to understand the aging mechanism of cellulose insulation. Life estimation using transformer thermal model is a practical approach in predicting transformer end-of-life as detailed in IEEE and IEC guides. In such cases, calculation of life of in-service transformers is done based on temperature rise of transformers, its loading condition, and ambient temperature. But the results of such thermal models using temperature rise as the only index of aging introduce large errors in life estimation. Temperature rise, oil condition, loading history, and design parameters are all key factors that determine the loss of life of a transformer through thermochemical degradation. Degree of polymerization (DP) of cellulose insulation is an excellent indicator of insulation aging which incorporates the effect of all the key factors of aging. Hence, transformer life estimation using the DP value of its solid insulation has been explored over the years. But DP tests are destructive in nature and are very difficult to perform for transformer in service. So life estimation through non-destructive testing by measurement of furanic compounds in oil, which are present in oil in dissolved state, is an attractive alternative. Since this methodology is based on oil tests, it could be used for online monitoring of transformer life, too. A predictive model which involves reliability engineering, physical understanding of the degradation process, and actual knowledge of the present condition of a transformer is necessary for accurate estimation of remaining life, which will facilitate appropriate replacement time of transformer and planning of appropriate maintenance scenario.