Aiming at the problems of long calculation time and low location accuracy in current distribution network fault diag-nosis,a distribution network fault identification and location model based on adaptive convolutional neural network is proposed.The adaptive convolutional neural network is used to train power data features,effectively extract power fault feature informa-tion from distribution networks,and classify faults based on the full connection layer to achieve end-to-end fault detection.Ac-curate fault location is achieved through a two-terminal fault location model.The experimental results show that the proposed ACNN model has better overall performance compared with the DBN model.When the detection accuracy is improved by 7.12％,the model training time is reduced by 42.7％.
关键词
配电网/故障识别/故障定位/深度学习
Key words
distribution network/fault identification/fault location/deep learning
维普
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