Power Transformer Insulation Assessment Based on Oil-Paper Measurement Data Using SVM-Classifier

Abstract

Oil immersed paper insulation condition is a crucial aspect of power transformer’s life condition diagnostic. The measurement testing database collected over the years made it possible for researchers to implement classification analysis to in-service power transformer. This article presents classification analysis of transformer oil-immersed paper insulation condition. The measurements data (dielectric characteristics, dissolved gas analysis, and furanic compounds) of 149 transformers with primary voltage of 150 kV had been gathered and analyzed. The algorithm used for developing classification model is Support Vector Machine (SVM). The model has been trained and tested using different datasets. Different models have been created and the best chosen, resulting in 90.63% accuracy in predicting the oil-immersed paper insulation condition. Further implementation was executed to classify oil-paper condition of 19 Transformers which Furan data is not available. The classification results combined, reviewed, and compared to conventional assessment methods and standards, confirming that the model developed has the ability to do classification of current oil-paper condition based on Dissolved Gasses and Dielectric Characteristics.

Impacts of Ambient Temperature Change on the Breakdown Voltage of a Distribution Transformer

“…Results showed an overall improvement in the cooling performance of transformer compared to the conventional use of pure transformer oil but the SiC-Oil nanofluid gave the lowest transformer temperature. Several investigations [18]- [19] have been carried out in recent time to analyse and characterise factors that could influence the lifespan of a transformer.…”