Distribution network single-phase earth fault identification method based on long-short time memory network

Abstract

The invention belongs to the technical field of intelligent control, and discloses a distribution network single-phase earth fault identification method based on a long-short memory network, which comprises the following steps: performing classification identification of arc-containing fault class and arc-free fault class and classification identification of earth type on a single-phase earth fault; acquiring zero sequence currents of continuous multiple periods during a fault steady state period, taking the waveform of the zero sequence current of a period time slot as a sample point, and performing classification identification of the arc-containing fault class and the arc-free fault class on the zero sequence currents of continuous multiple period time slots by using an LSTM deep learning classifier; single-phase earth fault of the arc-containing fault class and the arc-free fault class calculating unit period earth transition resistance of continuous multiple period time slots by using instantaneous voltage and current of continuous multiple period fault phases respectively; and carrying out classification identification on the unit period earth transition resistance of the continuous multiple period time slots by using a multilayer neural network by taking a change curve of the unit period earth transition resistance of one period time slot as a sample point to finish theidentification of the single-phase earth fault.

Description

technical field [0001] The invention relates to the technical field of distribution networks, in particular to a method for identifying single-phase grounding faults in a distribution network based on a long-short-term memory network. Background technique [0002] my country's medium and low voltage distribution network is dominated by overhead lines, the structure of the line is complex, there are many branches, and it is prone to failure. According to statistics, during the operation of the power system, power outages caused by distribution network faults account for more than 95% of the total power outages, of which 70% are caused by single-phase ground faults or busbar faults. In order to realize the rapid isolation of distribution system faults and restore the normal operation of the distribution network system, it is necessary to accurately and quickly realize the fault location of the distribution network. At present, fault location mainly relies on manual line inspe...

AI Technical Summary

Problems solved by technology

[0015] The present invention provides a long-short-term memory network-based identification method for single-phase grounding faults in distribution networks, which solves the problems of low reliability of existing identification methods, mainly relying on manual line inspection, and slow response speed.

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