A Prediction Model for Power Frequency Breakdown Voltage of Transformer Oil Gap

The structure of a power transformer through the combination of oil and paper as the main insulation system is the key to its safe and reliable operation. In this paper, a grey correlation model is constructed by Support Vector Machine (SVM) from the perspective of the electric field change during the discharge process, and the model is optimized by using the idea of cross-validation to find the optimal parameters to construct the optimal transformer oil gap frequency breakdown voltage prediction model. In this paper, the SVM model is used to predict the transformer oil gap frequency breakdown voltage from the 30 min withstand voltage test, and the predicted breakdown voltage is compared with the actual breakdown voltage. The validity of the model was verified.