Abstract
The financial constraints of the country make it difficult to maintain the operational cost and enhancing the reliability of power transformers in the grid. The industry embarked on the process of finding a way to improve the lifespan of the high voltage apparatus by implementing an effective plan to manage the assets. Thus, applying economical, reliable, comprehensive conditioning and assessment process of maintenance is a priority to support a proper plan. Power transformers are very expensive apparatus in the power system; hence, conditioning and assessment is a compulsory project. It is generally recognized that the lifespan of the power transformer is determined by how good the insulation system is. Therefore, economical and reliable moisture content diagnostic, conditioning and monitoring methods are compulsory to conduct extensive and effective transformer state evaluation. In this study, an adaptive neuro fuzzy inference system is used as the modelling tool to predict the parameters of dew point measurements. Furthermore, the efficiency of the diagnostic method is improved and the accuracy is validated by the Frequency domain spectroscope technique, to reduce the maintenance, assessment costs and time taken to diagnose the transformer...
M.Phil. (Electrical and Electronics Engineering)