Lujia Wang, Guangyi Chen, Dong Shang, 等. Investigating Breathing Dynamics of a 110 kV Oil-Immersed Transformer Using Thermal-Fluid-Structure Interaction Modelling[J]. 高电压(英文), 2026,11(3).
Lujia Wang, Guangyi Chen, Dong Shang, et al. Investigating Breathing Dynamics of a 110 kV Oil-Immersed Transformer Using Thermal-Fluid-Structure Interaction Modelling[J]. High Voltage, 2026, 11(3).
Lujia Wang, Guangyi Chen, Dong Shang, 等. Investigating Breathing Dynamics of a 110 kV Oil-Immersed Transformer Using Thermal-Fluid-Structure Interaction Modelling[J]. 高电压(英文), 2026,11(3).DOI: 10.1049/hve2.70142.
Lujia Wang, Guangyi Chen, Dong Shang, et al. Investigating Breathing Dynamics of a 110 kV Oil-Immersed Transformer Using Thermal-Fluid-Structure Interaction Modelling[J]. High Voltage, 2026, 11(3).DOI: 10.1049/hve2.70142.
Investigating Breathing Dynamics of a 110 kV Oil-Immersed Transformer Using Thermal-Fluid-Structure Interaction Modelling
摘要
The breathing system of an oil-immersed transformer is of vital importance for maintaining equilibrium between internal and external pressures
with any malfunction potentially disrupting the transformer's stable operation. This study develops a thermal–fluid–structure interaction (TFSI) model to simulate the breathing phenomenon in a 110 kV oil-immersed transformer
addressing the limitations of current manual inspection methods. This model analyses key breathing parameters such as breathing volume and maximum breathing rate
along with their dynamic characteristics under various load factors and ambient temperatures
revealing nonlinear and linear relationships
respectively. To validate the model
the breathing parameters of a 110 kV oil-immersed transformer were monitored over a 7-day period using a breather equipped with a breathing monitoring functionality. Comparison between simulation results and monitoring data for the period from 7 p.m. March 7 to 7 p.m. March 8 revealed discrepancies of 6.93% for the maximum daily breathing rate and 6.73% for maximum daily breathing volume. This study contributes to the field by providing a more accurate and efficient method for analysing transformer breathing dynamics
potentially enhancing early detection of breathing system malfunctions
optimising breather maintenance schedules and improving diagnosis of pressure-related faults in oil-immersed transformers.
Abstract
The breathing system of an oil-immersed transformer is of vital importance for maintaining equilibrium between internal and external pressures
with any malfunction potentially disrupting the transformer's stable operation. This study develops a thermal–fluid–structure interaction (TFSI) model to simulate the breathing phenomenon in a 110 kV oil-immersed transformer
addressing the limitations of current manual inspection methods. This model analyses key breathing parameters such as breathing volume and maximum breathing rate
along with their dynamic characteristics under various load factors and ambient temperatures
revealing nonlinear and linear relationships
respectively. To validate the model
the breathing parameters of a 110 kV oil-immersed transformer were monitored over a 7-day period using a breather equipped with a breathing monitoring functionality. Comparison between simulation results and monitoring data for the period from 7 p.m. March 7 to 7 p.m. March 8 revealed discrepancies of 6.93% for the maximum daily breathing rate and 6.73% for maximum daily breathing volume. This study contributes to the field by providing a more accurate and efficient method for analysing transformer breathing dynamics
potentially enhancing early detection of breathing system malfunctions
optimising breather maintenance schedules and improving diagnosis of pressure-related faults in oil-immersed transformers.
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