Composite insulator electric field optimization method based on multi-target genetic algorithm

A composite insulator and multi-objective genetic technology, which is applied in the field of optimization of the electric field distribution of composite insulators, can solve the problem that it is difficult to meet the requirements of a more uniform electric field

Active Publication Date: 2015-10-28
HOHAI UNIV CHANGZHOU
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Problems solved by technology

In the electric field analysis of insulators, the two objective functions (field strength range_E and maximum field strength gradient Max_GradE) are contradictory, and their minimum values ​​are no

Method used

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  • Composite insulator electric field optimization method based on multi-target genetic algorithm
  • Composite insulator electric field optimization method based on multi-target genetic algorithm
  • Composite insulator electric field optimization method based on multi-target genetic algorithm

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Embodiment

[0082] The multi-objective optimization is implemented using the multi-objective genetic algorithm module GADST in matlab software. For multi-objective optimization, the fitness function returns different values. The function returns a column vector holding the values ​​of multiple output variables. Due to the limitation of the function interface, the column vector is returned here to store the simulation results of the output variables Range_E and Max_GradE respectively.

[0083] The setting value of the optimization program is shown in Table 1.

[0084] Table 1 Multi-objective optimization program setting values

[0085]

[0086] The large, medium and small shed radii 0.1025, 0.0825, 0.0625 are used as initial parameters. The parameters of Range_E and Max_GradE are optimized with multi-objective genetic algorithm, and the optimal solutions obtained are: 0.0955, 0.0933, 0.0585 respectively. The field strength distribution corresponding to the optimal parameters is as f...

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Abstract

The invention discloses a composite insulator electric field optimization method based on a multi-target genetic algorithm. The method comprises steps as follows: 1) solving an electrostatic field open domain problem; 2) establishing a composite insulator geometric model; 3) performing numerical computation on the composite insulator electric field intensity in Maxwell software; 4) in order to break through the limitation of a Maxwell software optimization module, adopting the VB (visual basic) script of the Maxwell software to realize data connection of the Maxwell software and MATLAB software; 5) in the MATLAB software, optimizing shed radiuses with the multi-target genetic algorithm; 6) obtaining optimized composite insulator electric field distribution. According to the method, the field intensity Range_E minimization and the field intensity gradient Max_GradE minimization are taken as multiple optimization targets, and large, medium and small shed radiuses of a composite insulator are optimized, so that the composite insulator electric field distribution is more uniform.

Description

technical field [0001] The invention relates to a composite insulator electric field optimization method based on a multi-objective genetic algorithm, and belongs to the technical field of composite insulator electric field distribution optimization. Background technique [0002] Composite insulators for transmission lines are widely used line support devices in power systems. Because composite insulators have the advantages of good anti-fouling performance, light weight, and easy maintenance, they have been widely used in my country's power systems. It has played a significant role in safe operation and promoting the development of my country's electric power industry. [0003] However, composite insulators also encounter some problems in practical use, such as brittle mandrel, severe reduction of electrical performance under ice coating, and serious uneven distribution of electric field. Among them, the serious inhomogeneity of electric field distribution is an urgent prob...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/12
CPCY02E60/00
Inventor 苗红霞贾澜施祺姜欣宜
Owner HOHAI UNIV CHANGZHOU
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