Single-phase grounding-fault line selection method based on attention mechanism-convolution neural network for distribution network

In case of distribution network single-phase grounding fault, characteristics are difficult to capture, which may affect the selection correctness and thus bringing hidden dangers to the safe and stable operation of the power grid. Hence, a new method based on attention mechanism and convolutional neural network (CNN) is proposed. Firstly, zero-sequence current data is preprocessed by S-transform. Secondly, Attention-CNN model is established by introducing attention mechanism to CNN. Finally, performance of the proposed model is verified by both simulation and real grid data, and compared with other methods under different fault conditions. Results show that the proposed Attention-CNN model can accomplish more efficient and accurate selection, as well as wide application.