In order to improve the speed and accuracy of distribution transformer outage prediction, a distribution transformer outage prediction method based on Logistic fast minimum error entropy algorithm was proposed. Aiming at the problem that the basic minimum entropy regression algorithm runs too slowly, a fast minimum error entropy algorithm was proposed, which can keep the same regression effect as the minimum entropy regression, and greatly reduce the running time of the algorithm. In view of the application of Logistic regression in outage prediction, a fast minimum error entropy regression algorithm based on logistic was proposed, and the weight of distribution transformer was selected. The overload duration, maximum active load rate, average active load rate, average three-phase unbalance degree and heavy three-phase unbalance degree were used as the characteristic variable data of distribution transformer outage prediction. A distribution transformer outage prediction model was established, and the effect was found to be better than Logistic regression in the comparative experiment.
