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A smart grid fault diagnosis method that can identify measurement tampering attacks

A smart grid and fault diagnosis technology, applied in the direction of measuring electricity, measuring electrical variables, character and pattern recognition, etc., can solve the problem of inability to determine the fault type of faulty components, the existence of decision-making risks, and fault diagnosis methods that do not consider measurement tampering attacks Impact and other issues

Active Publication Date: 2020-10-23
XIHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] (1) The fault diagnosis method does not take into account the impact of the measurement tampering attack. When the measurement tampering attack occurs, the existing fault diagnosis method will cause serious misdiagnosis
[0009] (2) Existing fault diagnosis models based on production rules, such as the petri net model and the SNPS model cannot comprehensively utilize telemetry and telesignaling quantities to achieve fault diagnosis, which leads to the existence of risk in its decision-making, because tampered telemetry will Cause the relay protection device to malfunction or refuse to operate, that is, the accuracy of the remote signal can no longer be guaranteed, and the fault type of the faulty component cannot be determined

Method used

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  • A smart grid fault diagnosis method that can identify measurement tampering attacks
  • A smart grid fault diagnosis method that can identify measurement tampering attacks
  • A smart grid fault diagnosis method that can identify measurement tampering attacks

Examples

Experimental program
Comparison scheme
Effect test

experiment example 1

[0200] The preset failure scenarios of Experimental Example 1 are shown in Table 1:

[0201] Table 1

[0202]

[0203] First of all, when a fault occurs, the fault occurrence time is taken as the reference time (0s), and the remote measurement voltage amplitudes of 0.1s, 0.2s, and 0.5s are used for normalization. Then use the FCM algorithm for cluster analysis to obtain the clustering results of suspected fault areas, such as Figure 12 As shown, B12 is the farthest away from other components, and it is judged as the suspected fault area. Therefore, the bus B12 and the components connected to it are all judged as suspected faulty components, and it is necessary to establish a measurement tampering attack recognition model for it T , that is, to establish measurement and tampering attack recognition models for B12, L1206 and L1213 respectively Π T . Taking line L1213 as an example, obtain the pulse value curves of sensory neurons and memory neurons in its model, such as ...

experiment example 2

[0212] The preset failure scenarios of Experimental Example 2 are shown in Table 3:

[0213] table 3

[0214]

[0215] Figure 15 The fault diagnosis method shown in the embodiment of the present invention first detects the result of the measurement tampering attack. Figure 15 The abscissa is the neuron number, and the ordinate is the pulse value, obviously Figure 15 In (a), when the number of neurons is greater than 1600, the output pulse value of the zero-sequence diagnostic model (the part indicated by the triangle) is significantly lower than the detection threshold of 0.8, and the output pulse value of the negative-sequence diagnostic model (the part indicated by the circle) also has Some are below 0.8. According to the detection and determination method of the embodiment of the present invention, it is considered that a measurement tampering attack occurs at this time, and the element L0102 suffers from a measurement tampering attack. and Figure 15 In (b), the...

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Abstract

The invention discloses a smart grid fault diagnosis method capable of identifying measurement tampering attacks. Firstly, an electrical quantity clustering detection method is used to determine suspected faulty components, thereby reducing the scope of diagnosis. Secondly, the present invention establishes a measurement tampering attack recognition model based on the memory pulse neural membrane system, which effectively solves the problem of fault diagnosis misoperation caused by measurement tampering attacks. Finally, the present invention uses the memory backtracking idea of ​​the memory pulse neuromembrane system to establish a fault diagnosis model that can comprehensively utilize telemetry and telesignaling quantities, which not only changes the original shortcoming of not being able to use telemetry to model based on production rules, It is also possible to determine the type of fault in the event of a faulty component being diagnosed.

Description

technical field [0001] The invention belongs to the technical field of smart grid fault diagnosis, and in particular relates to the design of a smart grid fault diagnosis method capable of identifying measurement tampering attacks. Background technique [0002] False data injection attack is an important network attack method against smart grid. It means that the attacker exploits the bad data detection vulnerability based on the residual error in the state estimation of the transmission network, and successfully injects data into the data acquisition and monitoring system (SCADA) or wide-area measurement system. The system (WAMS) injects false data to achieve illegal purposes such as modifying the measured values ​​and state variables of the smart grid, controlling the operating status of the smart grid, or obtaining economic benefits. With the deep penetration of information and communication technology in the modern smart grid, the exchange of information flow between the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/00G01R31/50G06K9/62G06N3/06
CPCG01R31/00G06N3/061G06F18/23
Inventor 王涛刘伟陈孝天
Owner XIHUA UNIV
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