Open AccessHealth index prediction of dissolved gases in transformer oil based on statistical distribution model
Author(s) -
Xiaogang Liu,
Jiajia Li,
Xiaoguang Wang,
Zhongyuan Wu,
Chenyao Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2087/1/012085
Subject(s) - transformer , dissolved gas analysis , statistics , transformer oil , exponential function , mathematics , statistical model , engineering , mathematical analysis , voltage , electrical engineering
In this paper, dissolved gas analysis (DGA) and statistical distribution model (SDM) were used to predict the health index (HI) of dissolved gas in transformer oil. First, the individual DGA data are classified according to transformer ages ranging from 1 to 4 years. Then, representative fitting models were selected and extrapolated from 5 to 25 years. The inverse cumulative distribution function (ICDF) of the selected distribution model was used to calculate the single conditional parameter data from 5 to 25 years. Finally, the traditional scoring method is used to estimate the future HI value. The results show that DGA parameters can be expressed by exponential equation based on statistical model. The predicted values of DGA health index of transformer oil from 1 to 7 years were basically consistent with the calculated values, and the DGA score was 100 points. By the 20th year, the DGA score had dropped to 75, requiring timely monitoring. The research results can provide powerful data support and theoretical reference for transformer life prediction.