A Dynamic Model of Thermally Induced Bubble Growth in Transformer Oil-Pressboard Insulation

During the operation of oil-immersed power transformers, especially under high load or moisture conditions, air bubbles are easily formed inside the insulation system, which in turn induce partial discharges and threaten the operational safety of the equipment. In order to deeply reveal the physical mechanism of bubble generation in the oilpressboard insulation system, this pressboard, starting from the microstructure, combined with the theory of bubble dynamics, establishes a bubble growth dynamics model that takes into account the factors of moisture vaporization, interfacial tension, and viscous resistance in the oil, and deduces the criteria for the bubbles to be detached from the interface of the oil-pressboard. The model is constructed based on the Rayleigh-Plesset equation and the Hertz-Knudsen evaporation model, and the growth behavior of bubbles under typical working conditions is simulated by the differential equation coupling the evolution of the molar amount of water vapor and the change of bubble size. The simulation results show that the water content and pore structure in the pressboard have a significant effect on the Initial Temperature of Bubble Escape (ITBE), and the calculated bubble detachment conditions are basically consistent with the experimental data, which verifies the reasonableness of the model. This study provides a theoretical basis for evaluating the transformer insulation condition and its overload capacity, and supports the prediction of bubble generation risk in operation.

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Publication Details

Published
2025-08-03
DOI
https://doi.org/10.1109/icempe66159.2025.11123086
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
0.00

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article

A Dynamic Model of Thermally Induced Bubble Growth in Transformer Oil-Pressboard Insulation

Hongshun Liu, Jingtong Feng, Ali Abdo, Jiali Liu et al.
Power Transformer Diagnostics and Insulation
article

A Dynamic Model of Thermally Induced Bubble Growth in Transformer Oil-Pressboard Insulation

Hongshun Liu, Jingtong Feng, Ali Abdo, Jiali Liu, Ruxue Zhao, Yizhen Sui
article en

Abstract

During the operation of oil-immersed power transformers, especially under high load or moisture conditions, air bubbles are easily formed inside the insulation system, which in turn induce partial discharges and threaten the operational safety of the equipment. In order to deeply reveal the physical mechanism of bubble generation in the oilpressboard insulation system, this pressboard, starting from the microstructure, combined with the theory of bubble dynamics, establishes a bubble growth dynamics model that takes into account the factors of moisture vaporization, interfacial tension, and viscous resistance in the oil, and deduces the criteria for the bubbles to be detached from the interface of the oil-pressboard. The model is constructed based on the Rayleigh-Plesset equation and the Hertz-Knudsen evaporation model, and the growth behavior of bubbles under typical working conditions is simulated by the differential equation coupling the evolution of the molar amount of water vapor and the change of bubble size. The simulation results show that the water content and pore structure in the pressboard have a significant effect on the Initial Temperature of Bubble Escape (ITBE), and the calculated bubble detachment conditions are basically consistent with the experimental data, which verifies the reasonableness of the model. This study provides a theoretical basis for evaluating the transformer insulation condition and its overload capacity, and supports the prediction of bubble generation risk in operation.

Shandong University (CN)
Natural Science Foundation of Shandong Province, State Key Laboratory of Electrical Insulation and Power Equipment
Openalex Percentile: Top 79%
Power Transformer Diagnostics and Insulation
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A Dynamic Model of Thermally Induced Bubble Growth in Transformer Oil-Pressboard Insulation — Hongshun Liu, Jingtong Feng, et al. · (2025) | TGRS Research Map | TGRS