Research on Transformer Hot-Spot Temperature Inversion Method Under Three-Phase Unbalanced Conditions

When a transformer operates under three-phase unbalanced conditions, the location of the winding hot-spot temperature (HST) is no longer fixed on a certain phase. Taking an S13-M-100 kVA/10 kV transformer as the research object, this paper proposes a streamline inversion method for inverting the winding HST based on the analysis of oil flow morphology. The study employs the finite volume method for coupled calculations of a transformer’s thermal fluid field and combines a support vector regression (SVR) model for the HST inversion. An orthogonal experimental method is used to construct the training and testing sample sets, and the grid search method is utilized to optimize the parameters of the SVR model. In response to variations in hot-spot locations under three-phase unbalanced conditions, representative streamlines are reasonably selected, and a genetic algorithm-based dimensionality reduction optimization is performed on the feature quantities. The research results indicate that the established inversion model exhibits high inversion accuracy under three-phase unbalanced conditions, with a maximum temperature difference of 3.71 K, and the robustness check verifies the stability of the model.