Low frequency oscillation modal identification method based on improved generalized morphological filtering

Abstract

The invention relates to a low frequency oscillation modal identification method based on improved generalized morphological filtering and aims to the low frequency oscillation modal identification of power system. A generalized morphological filtering is utilized to carry out de-noising processing to low frequency oscillation signals, and TLS-ESPRIT algorithm in adopted to do modal identification. For a problem of determining the order in the process of the TLS-ESPRIT algorithm being used to do the low frequency oscillation model identification, a ratio method between singular value difference and maximum singular value is adopted to determine the older. The method has the advantages of less calculation, fast speed, and less influence from subjective factors in the process of the order determination. According to the invention, the accurate identification of the low frequency oscillation mode under the noise interference is achieved, and a good application prospect is achieved.

Description

technical field [0001] The invention relates to the safe and stable operation of a power system, in particular to a low-frequency oscillation mode identification method based on improved generalized shape filtering. Background technique [0002] The stable operation of power system is the fundamental problem of power system. Due to the continuous expansion of the scale of the power system, especially the construction of high-voltage direct current transmission and the extensive use of nonlinear loads, the dynamic stability and transient stability of the power grid have become one of the key issues affecting its reliable and safe operation. Studies have shown that the high-magnification fast excitation transposition widely used in the power system will lead to weakening of the system damping and even some negative damping, so that it is extremely easy to induce low-frequency oscillations in the power grid under some small disturbances, and when the oscillations are severe, it...

AI Technical Summary

Problems solved by technology

[0004] With the extensive use of nonlinear devices, the pollution in the power grid is becoming more and more serious and complex. The signals taken from the power system contain a lot of noise, and the existence of interference will seriously interfere with the accuracy of signal identification.

At present, the modal identification of the power system generally eliminates the noise through the built-in singular value decomposition. In this case, the estimation of the noise is not enough, especially the noise processing ability is limited in the case of low signal-to-noise ratio.

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