Particle tracing modelling on moisture dynamics of oil-impregnated transformer
Article
Article Title | Particle tracing modelling on moisture dynamics of oil-impregnated transformer |
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ERA Journal ID | 4421 |
Article Category | Article |
Authors | Cui, Yi (Author), Ma, Hui (Author), Saha, Tapan (Author), Ekanayake, Chandima (Author) and Martin, Daniel (Author) |
Journal Title | IET Science, Measurement and Technology |
Journal Citation | 10 (4), pp. 335-343 |
Number of Pages | 9 |
Year | 2016 |
Publisher | Institution of Engineering and Technology (IET) |
Place of Publication | United Kingdom |
ISSN | 1751-8822 |
1751-8830 | |
Digital Object Identifier (DOI) | https://doi.org/10.1049/iet-smt.2015.0196 |
Web Address (URL) | https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-smt.2015.0196 |
Abstract | An accurate estimation of moisture in oil-impregnated cellulose of a transformer is difficult due to the complex moisture dynamics inside the transformer, which is highly influenced by the temperature and dimension of the transformer. In this study, a novel particle tracing method is proposed for estimating the moisture in transformers. Different from the conventional approaches using Fick's diffusion law, the proposed method formulates moisture diffusion from a microscopic view of water particles’ motion. Especially, the transmission probability of water particles is employed to correlate the microscopic particles’ motion with the macroscopic moisture distribution. The proposed particle tracing method is applied to model moisture dynamics in both pressboard specimens and a prototype transformer. Extensive moisture diffusion and ageing experiments are carried out to verify the proposed method. |
Keywords | moisture measurement; transformer oil; probability; oil-impregnated transformer cellulose; moisture diffusion estimation; particle tracing method; Fick’s diffusion law; water particle motion transmission; probability; macroscopic moisture distribution; microscopic particle motion correlation; ageing experiment |
ANZSRC Field of Research 2020 | 400803. Electrical energy generation (incl. renewables, excl. photovoltaics) |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Queensland |
Institution of Origin | University of Southern Queensland |
Funding source | Australian Research Council (ARC) Grant ID LPII0100324 |
https://research.usq.edu.au/item/q7w42/particle-tracing-modelling-on-moisture-dynamics-of-oil-impregnated-transformer
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