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A Novel Automatic Detection Model for Single Line-to-ground Fault

Received: 15 February 2019 Accepted: 10 May 2019 The single line-to-ground (SLtG) fault is difficult to locate or troubleshoot rapidly by traditional methods, posing a serious threat to the safety and stability of the power system. Since the transient negative sequence current (NSC) is immune to the arc-suppression coil of the grid, this paper sets up an automatic detection model for the SLtG fault in the grid. Firstly, the positive sequence fault current and negative sequence fault current were extracted from the transient process current of the grid, and combined into the transient NSC. After that, the characteristic region of the NSC was determined by the change of the transient NSC. To further define this region, the matrix algorithm was introduced to extract the exact feature points of the fault region. Taking the feature points as the input vectors, the neural network (NN) was adopted to identify the fault position. Simulation results show that our model achieved a 4 % lower false acceptance rate (FAR), a 10 % lower false rejection rate (FRR), and a much higher efficiency than the traditional detection model. The research findings lay the basis for fault data analysis and online fault diagnosis and improve the reliability of grid operations.