Heat transfer modeling in a transformer using magneto-CFD analysis and GWO algorithm considering dynamic thermal model

One of the most expensive power system components is transformer. The correct use and health of the transformer increase the reliability of the power network.The transformer health is depend on careful planning for it. Therefore, hot spot temperature must be calculated for accurate transformer planning. Also, in order to increase the accuracy of transformer hot spot temperature estimation, the dynamic thermal model is used. On the other hand, the use of meta-heuristic algorithms has been less considered by researchers to calculate the transformer hot spot temperature. Thus, in this paper, the grey wolf, imperialist competitive and artificial bee colony algorithms are used to estimate the transformer hot spot temperature. Besides, electromagnetic analysis of the transformer is investigated using ANSYS-MAXWEL software. On the other hand, conjugate heat transfer modeling in the transformer is presented to compare the results with the grey wolf optimization algorithm. The results show that the grey wolf optimization algorithm can be a good alternative for transformer hot spot temperature estimation. • Transformer magneto-CFD analysis and conjugate heat transfer. • Transformer HST estimation using the grey wolf optimization algorithm. • Accurate dynamic thermal model in transformer HST estimation.