Transformer hybrid polarization model parameter identification method based on improved wolf pack algorithm

A technology of model parameters and mixed polarization, applied in computing models, biological models, instruments, etc., can solve the problems of low identification accuracy, single learning object, difficulty in parameter identification, etc., and achieve wide search range, fine search, step-by-step The effect of size

Pending Publication Date: 2022-03-22
STATE GRID PUTIAN ELECTRIC POWER SUPPLY +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the introduction of the Maxwell branch, the model is more complicated, and there is a certain difficulty in parameter identification
The particle swarm algorithm is used for the parameter identification of the traditional mixed polarization model. However, due to the limitations of the algorithm, the algorithm has a single learning object in the later stage, and it is easy to fall into a local optimum, which makes the identification accuracy not high.

Method used

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  • Transformer hybrid polarization model parameter identification method based on improved wolf pack algorithm
  • Transformer hybrid polarization model parameter identification method based on improved wolf pack algorithm
  • Transformer hybrid polarization model parameter identification method based on improved wolf pack algorithm

Examples

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Embodiment 1

[0044] The mixed polarization model described in this embodiment introduces the Maxwell interface polarization branch on the basis of the extended Debye model, and the Maxwell interface polarization branch uses double-layer RC capacitors to characterize its complex interface polarization, as shown in figure 2 As shown, where C1 and C2 represent the equivalent capacitance of the medium, and R1 and R2 represent the resistance value. ε1, ε2 and γ1, γ2 respectively represent the dielectric constant and conductivity of different insulating media, and d1 and d2 represent the thickness of different insulating media.

[0045] After introducing the Maxwell interface polarization branch, the mixed polarization model is as follows image 3 shown;

[0046] Assuming that there are n RC series polarization branches and N interface polarization branches, the equivalent port admittance of the mixed polarization model can be obtained as:

[0047]

[0048] Plug into the complex capacitanc...

Embodiment 2

[0095] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. It is characterized in that, when the processor executes the program, any implementation of the present invention The parameter identification method of the transformer mixed polarization model described in the example.

Embodiment 3

[0097] This embodiment provides a computer-readable storage medium, on which a computer program is stored, wherein when the program is executed by a processor, the method for identifying parameters of a transformer mixed polarization model as described in any embodiment of the present invention is implemented.

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Abstract

The invention relates to a transformer hybrid polarization model parameter identification method based on an improved wolf pack algorithm, and the method comprises the following steps: the wolf pack algorithm is improved, an adaptive step length is introduced, and the step length of each movement of a wolf pack is determined by the current position of the wolf pack and the position of a head wolf pack; enabling a wolf pack position in the improved wolf pack algorithm to be a model parameter identification value of the hybrid polarization model, and constructing a wolf pack hunting function based on the model parameter identification value and a measured value; performing a wolf pack hunting activity, initializing a wolf pack position, generating a first wolf based on a wolf pack hunting function, and performing a wolf pack searching behavior, a wolf pack calling behavior and a wolf pack hunting behavior; the position of the first wolf is updated according to the mechanism that the strong wolf is the king, and the wolf pack is updated according to the mechanism that the weak meat is the strong food; and repeating the wolf pack hunting activities to perform iteration updating of the wolf pack, and outputting the model parameter identification value of the hybrid polarization model with the position of the current head wolf being the optimal after an iteration termination condition is reached.

Description

technical field [0001] The invention relates to a parameter identification method of a transformer mixed polarization model based on an improved wolf pack algorithm, and belongs to the technical field of transformer equivalent circuit model parameter identification. Background technique [0002] The transformer oil-paper insulation system is composed of insulating media with different dielectric constants such as insulating oil and insulating cardboard. Its microscopic dielectric response is very complex, mainly including dipole steering polarization reaction and interface polarization reaction. Although the extended Debye circuit model that uses multiple RC series branches in parallel to simulate the polarization process of the insulating medium takes into account the dipole turning polarization of the dielectric, it ignores the interface polarization reaction that gradually becomes prominent with the aging of the insulation, so it cannot It better fits the relaxation respo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N3/00
CPCG06F30/27G06N3/006
Inventor 林明星郑宇林翊乾陈扩松潘亦斌李语菲
Owner STATE GRID PUTIAN ELECTRIC POWER SUPPLY
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