Abstract: This study is on hot spot temperature (HST) prediction models, including loss of life (LoL) of transformers, and uses the Asaba transmission substation as a case study. One year loading profile data was collected from the substation while Artificial Neural Network (ANN) and Bagging Regression (BR) algorithms were modeled using this data on MATLAB and Python to predict the HST for Day-Ahead (24-Hours), Week-Ahead (120-Hours), and Weekend (48-Hours). The results.....
Keywords: Transformer Hot Spot Temperature, Loss of Life, Artificial Neural Network, Bagging Regression, Asaba Transmission Substation, Thermal Stress, Insulation Life, Aging Factor
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