Diffusion characteristics of multi-component gases in gas to liquid insulating oil via molecular dynamics analysis

In power transformers, insulating oil deteriorates continuously due to aging, overheating, discharge, and other factors, accompanied by the production of characteristic gases such as H₂, CH₄, C₂H₂, C₂H₄, C₂H₆, and varying degrees of diffusion within the oil. However, due to differences in gas structure and insulation systems, the diffusion characteristics of characteristic gases in gas to liquid (GTL) insulating oil are not yet clear, and the interactions among multiple gas molecules remain unclear. In order to elucidate this diffusion mechanism, this study employs molecular dynamics methods to investigate the diffusion behavior of mixed gases in stationary GTL insulating oil at the microscopic level. By comparing the diffusion coefficients, trajectories, free volume fractions, and interaction energies of single-component, binary, and multicomponent gas systems, the influence of mixed gas addition on diffusion is analyzed. The results indicate that for single-component diffusion systems, the diffusion coefficients of gases in GTL insulating oil exhibit the order: H₂ > hydrocarbon gases, and the diffusion coefficients of hydrocarbon gases are inversely proportional to molecular mass, with diffusion of different gases conforming to the "vacancy jump diffusion theory". For binary diffusion systems, the diffusion of gas molecules in mixed gas systems exhibits a synergistic effect, manifested by repulsive interactions between different gas molecules. Moreover, the addition of mixed gases reduces the interaction energy of CH₄ with GTL insulating oil by 9.21 kJ/mol and that of H₂ by 3.76 kJ/mol, respectively; the free volume fractions of H₂ and CH₄ increase by 27.5% and 113.7%, respectively, expanding gas movement space, weakening GTL's binding effect on gases, and increasing gas diffusion coefficients. Clarifying the diffusion characteristics of gases in GTL insulating oil will effectively serve the fault diagnosis of power transformers.