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26 June 2023 Method of transformer top oil temperature forecasting based on grey-autoregressive differential moving average model
Jingxian Qi, Zhengning Pang, Zhen Liu, Yanan Du
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Proceedings Volume 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023); 1271414 (2023) https://doi.org/10.1117/12.2683155
Event: Third International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 2023, Sanya, China
Abstract
The top oil temperature index of transformer is an important indicator of transformer load capacity and service life. In this paper, the grey prediction model is used to predict the transformer oil temperature initially, and then the autoregressive differential moving average model is used to fit and train the deviation sequence for its prediction deviation. Finally, the optimized prediction model is obtained. The obtained transformer top oil temperature value is divided into training set data and test set data, and divided according to corresponding proportion, so as to achieve accurate prediction of transformer top oil temperature. The experimental results show that the optimized grey-autoregressive differential moving average model prediction algorithm has good prediction effect.
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Jingxian Qi, Zhengning Pang, Zhen Liu, and Yanan Du "Method of transformer top oil temperature forecasting based on grey-autoregressive differential moving average model", Proc. SPIE 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 1271414 (26 June 2023); https://doi.org/10.1117/12.2683155
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KEYWORDS
Transformers
Autoregressive models
Data modeling
Data processing
Power grids
Mathematical optimization
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