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Electric power system low-frequency oscillation mode identification method based on FastICA and TLS-ESPRIT

A low-frequency oscillation and mode identification technology, applied in the field of power technology systems, can solve the problems of wavelet transform wavelet base selection, mode aliasing, end effect, etc., achieve good application prospects, improve signal-to-noise ratio, and identify accurately Effect

Active Publication Date: 2021-04-20
FUJIAN UNIV OF TECH
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Problems solved by technology

[0004] Wavelet transform has the problem of difficult wavelet base selection; although Prony analysis is a widely used low-frequency oscillation identification method in today's academic circles, this method is very sensitive to noise and cannot obtain ideal results when the signal-to-noise ratio is lower than 50dB; In actual application, the HHT method itself will have modal aliasing, endpoint effects and false components; although the ESPRIT algorithm can accurately identify the oscillation mode of the system, its performance will also vary in the case of colored noise and low signal-to-noise ratio. decrease

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  • Electric power system low-frequency oscillation mode identification method based on FastICA and TLS-ESPRIT
  • Electric power system low-frequency oscillation mode identification method based on FastICA and TLS-ESPRIT
  • Electric power system low-frequency oscillation mode identification method based on FastICA and TLS-ESPRIT

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Embodiment Construction

[0037] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0038] Such as Figure 1 to Figure 5 As shown in one of them, the present invention discloses a method for identifying low-frequency oscillation modes of power systems based on FastICA and TLS-ESPRIT, which includes the following steps:

[0039] Step 1. Obtain the wide-area measurement signal as the initial input mixed signal x and perform FastICA processing. The specific steps are:

[0040] Step 1-1, obtaining the low-frequency oscillation signal for zero-mean and whitening processing;

[0041] Step 1-2, construct separation matrix W and calculate the inverse matrix of separation matrix W;

[0042] Steps 1-3, perform an iterative loop to update the separ...

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Abstract

The invention discloses an electric power system low-frequency oscillation mode identification method based on FastICA and TLS-ESPRIT. The method comprises the following steps: obtaining a low-frequency oscillation signal to carry out zero mean and whitening processing; constructing a separation matrix and calculating an inverse matrix of the separation matrix; performing iterative loop, and updating a separation matrix; after convergence is judged, using the signal recovered by FastICA as a new dominant signal for sampling; carrying out TLS-ESPRIT analysis on the new dominant signal, and calculating the frequency, attenuation factor, amplitude and phase of each oscillation mode. According to the method, the original characteristics of the signal can be well reserved under the condition of noise interference, and the signal-to-noise ratio is improved; and moreover, the method is accurate in identification and higher in precision, can reflect the characteristics of the low-frequency oscillation signal more accurately and comprehensively, and has a good application prospect in the design of a low-frequency oscillation early-warning and damping controller.

Description

technical field [0001] The invention relates to the field of power technology systems, in particular to a method for identifying low-frequency oscillation modes of power systems based on FastICA and TLS-ESPRIT. Background technique [0002] With the continuous expansion of the scale of the interconnected grid, the risk of low-frequency oscillation is greatly increased. When the system has an oscillation mode with weak damping or negative damping in some specific operating modes, severe oscillations will lead to the disintegration of the power system and even endanger the stable operation of the entire power grid. Therefore, discovering and timely and accurately extracting low-frequency oscillation modes and obtaining characteristic parameters is of great significance to the safe and stable operation of power systems. [0003] Over the years, there have been many research methods on the problem of low-frequency oscillations, and the eigenvalue analysis method is one of the c...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00G01R25/00
CPCY04S10/00
Inventor 张程刘佳静邱炳林林谷青匡宇
Owner FUJIAN UNIV OF TECH
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