Application of improved grey model residual modified fusion algorithm in dissolved gas forecasting

Application of improved grey model residual modified fusion algorithm in dissolved gas forecasting

The power transformer directly affects whether the power system can operate safely and reliably, and the prediction of the dissolved gas content in the transformer oil is an effective means to discover transformer defects and latent faults, which helps to better carry out state maintenance work. Thi...

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Bibliographic Details
Main Authors: Wenjie Wu, Yigang He, Jiajun Duan
Format: Article
Language:English
Published: Wiley 2019-11-01
Series:The Journal of Engineering
Subjects:
regression analysis
transformer oil
power transformers
time series
markov processes
grey systems
dissolved gas content
power system
power transformer
dissolved gas forecasting
improved grey model residual modified fusion algorithm
original prediction method
residual correction
markov correction models
longer time span
prediction accuracy
grey prediction model
original sequence
gas components
time series data
state maintenance work
latent faults
transformer defects
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9200

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https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9200

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