Intelligent substation fault positioning method based on gated recurrent unit network
A technology for intelligent substation and fault location, applied in the directions of fault location, biological neural network model, measurement of electricity, etc., can solve the problem of lack of intelligent substation fault location method, etc., to achieve the effect of efficient and accurate decision-making
Active Publication Date: 2022-02-25
CHONGQING UNIV +1
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[0007] Therefore, the defect of the existing technology is that there is a lack of an intelligent substation fault location method based on the gated cyclic unit network, which can locate the secondary system fault of the substation and provide efficient auxiliary decision-making for the operation and maintenance personnel
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[0091] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0092] Such as Figure 1-Figure 8As shown, a smart substation fault location method based on a gated cyclic unit network includes the following steps: Step 1: For different intervals, such as line intervals, transformer intervals, bus intervals, and center switch intervals, collect the intervals of each interval When the secondary equipment and its network port, optical fiber, switch port, etc. are faulty, the alarm signal sent by the relevant equipment is constructed, and the alarm signal set and the corresponding fault location of each interval in each fault scenario are constructed. The specific operation is as follows:
[0093] 1) The station control layer equipment collects the alarm signal sent by the relevant equipment when the next secondary equipment fails at each interval, and forms the alarm signal set and its corresponding...
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The invention discloses an intelligent substation fault positioning method based on a gated recurrent unit network, and the method comprises the following steps: A, collecting alarm signals from related equipment for each fault scene of secondary equipment of an intelligent substation in each interval, and forming an alarm signal set and a corresponding fault position; step B, respectively constructing a GRU network of each interval, then, adding a full-connection Dense layer, and finally adding a Softmax classification layer, and further constructing a GRU fault positioning model of each interval; step C, training the GRU fault positioning model of each interval, respectively sending respective training data to carry out fault positioning training, and optimizing each parameter in the GRU fault positioning model by taking the accuracy rate as an index; and after the training of the GRU fault positioning models is completed, respectively sending respective test data for testing, and counting the accuracy of each GRU fault positioning model. According to the method, the fault of the secondary system of the transformer substation can be accurately positioned, and efficient and accurate auxiliary decision making is provided for operation and maintenance personnel.
Description
technical field [0001] The invention relates to the technical field of fault location of a secondary system of an intelligent substation, in particular to a method for fault location of an intelligent substation based on a gated cycle unit network. Background technique [0002] The safe and reliable operation of smart substations is crucial to the operation of power systems. In recent years, secondary system failures in smart substations have caused unsafe operation of the system. When the secondary system of the smart substation is abnormal and generates a large number of alarm signals, it is difficult for the operation and maintenance personnel to extract useful information from it, and it is difficult to accurately determine the location of the fault. [0003] Many studies have been done on the fault location of the secondary system at home and abroad. The patent "Method and System for Fault Location of Substation Secondary Circuit Based on Graph Neural Network" proposes...
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IPC IPC(8): G01R31/08G06N3/04
CPCG01R31/088G06N3/044Y04S10/50
Inventor 王洪彬周念成李智童晓阳王强钢
Owner CHONGQING UNIV