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Propagation matrix modulus optimization fitting method and system based on particle swarm algorithm

A particle swarm algorithm and propagation matrix technology, applied in the field of optimal fitting method and system of propagation matrix modulus, can solve problems such as consuming a lot of time

Active Publication Date: 2020-06-30
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The problem is that, for a given target fitting accuracy, a fitting method with incremental number of poles usually consumes a lot of time trying different numbers of poles one by one

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  • Propagation matrix modulus optimization fitting method and system based on particle swarm algorithm
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  • Propagation matrix modulus optimization fitting method and system based on particle swarm algorithm

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Embodiment Construction

[0076] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0077] The purpose of the present invention is to provide an optimized fitting method of the propagation matrix modulus based on the particle swarm algorithm, so as to quickly find the model parameters (the number of poles and the delay size) that meet the accuracy requirements and obtain the corresponding fitting model.

[0078] In order to make the above objectives, features and advantages of the present invention more obvious and underst...

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Abstract

The invention relates to a propagation matrix modulus optimization fitting method and system based on a particle swarm algorithm. The method comprises the steps of determining the target fitting precision tol, the fitting frequency range, the pole number range and the delay tau range; generating N random numbers in the fixed interval; determining a real pole number point mi and a delay point tau i, and rounding down the real pole number point mi; initializing related parameters in an iteration process; performing iterative computation based on the related parameters; reading the historical optimal position vector of the group to obtain the number and delay of contained poles, and executing the previous step to obtain new poles; and fitting the modulus of the propagation function matrix byusing a vector fitting technology according to the obtained pole number, time delay and new poles, calculating a fitting error, and outputting a fitting result and the fitting error. According to thesystem, the model parameters meeting the precision requirement can be quickly found, and the corresponding fitting model is obtained.

Description

Technical field [0001] The present invention relates to the field of power transmission, in particular to a method and system for optimizing and fitting a propagation matrix modulus based on a particle swarm algorithm. Background technique [0002] Power transmission lines are important power transmission equipment. In the power system, except for electrical equipment and power plants, the rest are power grids composed of transmission lines, so transmission lines play an irreplaceable role in the power system. The frequency range of overvoltage caused by power equipment failure, lightning strike or improper operation is much larger than the frequency range of the normal operation of the system, and contains a lot of high frequency components. Therefore, in the transient calculation, a traveling wave model is established for the power transmission line. The traveling wave model regards the change of voltage and current on the power transmission line as a wave process. The incide...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06F30/20G06N3/00
CPCG06Q10/04G06Q50/06G06N3/006
Inventor 葛青宇焦重庆
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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