Research Article
An Intelligent Fault Prediction Method for Distribution Grid Transformers Based on Digital Twins and Deep Learning
@INPROCEEDINGS{10.1007/978-3-032-00303-4_30, author={Lulu Liu and Simayi Xuelati and Lina Yang and Gaoqian Xue and Mei Zhao}, title={An Intelligent Fault Prediction Method for Distribution Grid Transformers Based on Digital Twins and Deep Learning}, proceedings={Advanced Hybrid Information Processing. 8th International Conference, ADHIP 2024, Jiaxing, China, September 20--22, 2024, Proceedings, Part III}, proceedings_a={ADHIP}, year={2026}, month={11}, keywords={Digital Twin Deep Learning Distribution Network Transformer Fault Intelligent Forecasting}, doi={10.1007/978-3-032-00303-4_30} }- Lulu Liu
Simayi Xuelati
Lina Yang
Gaoqian Xue
Mei Zhao
Year: 2026
An Intelligent Fault Prediction Method for Distribution Grid Transformers Based on Digital Twins and Deep Learning
ADHIP
Springer
DOI: 10.1007/978-3-032-00303-4_30
Abstract
Aiming at the problem that the fault prediction accuracy of distribution network transformer is low and cannot provide reliable basis for transformer operation and maintenance, digital twin and deep learning are introduced. By constructing the digital twin model of distribution network transformer, classifying the movement state of distribution network transformer; Innovatively deep learning fault samples to achieve intelligent prediction of transformer operation status in distribution networks. The experimental results show that the prediction results of this method are more accurate and the calculation time is shorter. This method has guiding significance for the knowledge system of digital twins in the application of distribution transformer fault prediction.