Diffusion of Characteristic Gases in Oil‐Immersed Transformer by Computational Fluid Dynamics Simulation and Experimental Verification

The complex diffusion of characteristic gases within oil‐immersed transformers significantly influences the timeliness between the fault occurrence and gas detection. So far, the gas transport processes and spatio‐temporal distributions remain inadequately understood. In this work, we developed a computational fluid dynamics (CFD) model that integrates the steady‐state thermal‐fluid fields with the transient processes of gas diffusion and dissolution. The model was numerically simulated based on dispersed two‐phase flow theory. Targeting a 110 kV oil‐natural and air‐natural (ONAN) transformer, we investigated the gas diffusion paths, effect of oil flow and dissolution differences among various gases in oil. The proposed CFD model is verified by gas flow experiment on a field transformer. The results revealed that free gases primarily rise vertically towards the tank top, and are hardly affected by oil flow; differences between various compositions can be negligible. Although the dissolved gases exhibited distinct diffusion characteristics, the path distributions involving molecular diffusion and convective diffusion. The convective diffusion driven by oil flow is found to be the dominant factor. Due to the effects of oil pressure and gas volume fraction, the mass transfer rates of gas dissolution in oil surface and oil channel inside the winding are higher than other spots. The mass transfer rates and dissolved gas content follow a descending order by C 2 H 6 > C 2 H 4 > C 2 H 2 > CH 4 > H 2 . According to the measured results of the gas dissolved in oil and the errors of CFD simulation are less than 15%. This study aims to provide a solid basis for achieving both rapid gas detection and sensitive fault identification in transformer.