Reconstruction and Detection Method of Power System Harmonic Compression Signal Based on Compressive Sensing

Abstract

The invention discloses a power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing. The power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing comprises the steps that harmonious wave original signals of a power system and a measurement matrix with a binary sparse random measurement matrix serving as a power system harmonious wave data compressed sample are sent to a frequency mixer for compressed sampling in a simulation domain, then A / D conversion is carried out on the simulation signals, and a compressed sampling value is obtained; it is determined that a compressed sensing sparse base is a discrete Fourier transform base; initialization of fundamental wave filtering is carried out; fundamental wave filtering is carried out; the frequency, amplitude and phase of a fundamental component are detected; the fundamental wave constituent in the compressed sampling value is filtered away; parameter initialization is carried out on a spectrum projection gradient method; a sparse vector estimation value of a harmonious wave component is reconstructed through the spectrum projection gradient method; the frequency, amplitude and phase of the harmonious wave component are detected; reconstruction of the harmonious wave original signals of the power system is finished. The power system harmonious wave compressed signal reconstruction and detection method based on compressed sensing overcomes the defect that all existing recovery algorithms do not take the influence of the fundamental wave component in the harmonious wave signals on signal reconstruction into account, so that the recovery effect is not ideal.

Description

technical field [0001] The invention relates to a power system harmonic compression sampling and detection method. In particular, it relates to a method for reconstruction and detection of power system harmonic compression signal based on compressed sensing. Background technique [0002] The ideal voltage and current waveforms of the power system are sine waves or cosine waves, but due to the existence of various nonlinear components in the power system, the voltage and current waveforms are distorted and harmonics are generated, and the existence of harmonics will increase the power loss of the power grid , equipment life shortened, protection malfunction and many other hazards. In recent years, with the increasing scale of the power system and the rapid development of power electronics technology, more and more harmonic source loads and devices have been widely used in the power system, and the harmonic pollution has become more and more serious. Harmonics have been cons...

AI Technical Summary

Problems solved by technology

Among these algorithms, the SPG method has the highest signal reconstruction accuracy, but these algorithms do not consider the characteristics of the harmonic signal and the influence of the fundamental component on the signal reconstruction, which makes the recovery effect not very ideal

[0009] Moreover, the existing compressed sensing technology in the field of harmonic analysis does not involve detection technology, and can only compress the harmonic data, and cannot detect the parameters of the harmonic components

[0010] In the field of harmonic detection, Fourier transform (DFT) is often used for harmonic component detection. The coefficient spectral line vector of the discrete Fourier transform of the harmonic signal (that is, the original harmonic signal sparsely represents the coefficient under the DFT basis) is a discrete spectrum Line, which contains the frequency, amplitude and phase information of each component, but due to the spectrum leakage and fence effect in Fourier analysis, it is necessary to perform spectral line interpolation correction on the discrete spectral lines obtained by discrete Fourier transform of harmonic signals In order to realize the detection of harmonic component parameters with high precision

Images