Research on life loss of transformer based on machine learning algorithms

Transformer life assessment and failure diagnostics are always important problems for power grid companies. Ambient temperature and load profle are the main factors which affect the transformer insulation, and lifetime. Based on the model of transformer life loss calculated by GB/T 1094.7-2008 recommended ambient temperature and transformer load, a data-driven static model for estimating transformer life loss and a learning model for transformer life loss based on SVM algorithm are developed. The research fnds that the SVM algorithm model using RBF kernel function can effectively and accurately solve the problem of transformer life assessment.