Prediction of the oil flow distribution in oil-immersed transformer windings by network modelling and computational fluid dynamics

In the context of thermal performance and thermal design, it is of significance to predict the magnitude and the location of the `hot-spot` temperature inside a power transformer. In an attempt to accurately predict this hot-spot in an oil-immersed transformer, various numerical modelling approaches have been developed for calculating the cooling oil flow distribution, which are generally categorised as either `network models` or the methods that incorporate forms of computational fluid dynamics (CFD). In network modelling, the complex pattern of oil ducts and passes in a winding is approximated with a matrix of simple hydraulic channels, where analytical expressions are then applied to describe oil flow and heat transfer phenomena. On the other hand, CFD models often adopt discretisations of much higher fineness, which can be expected to offer a higher order of accuracy but also comes with a large increase in the required computational resources. In order to compare both modelling approaches, the network model implementation TEFLOW and a commercial CFD package, ANSYS-CFX, were applied on a typical `zigzag` oil channel arrangement of a disc-type winding to predict oil flow distribution and disc temperatures; experiments on hydraulic models have also been performed to validate the models. The principle work of this study is then comparing the results and concluding recommendations to industrial practices.