Electric system low frequency oscillation mode identification method based on correlation functions

Abstract

The invention discloses an electric system low frequency oscillation mode identification method based on correlation functions. The method includes the following steps that firstly, a section of an active power signal of a circuit having high observability for a low frequency oscillation mode under the circumstance that no large disturbance exists in an electric system is read and serves as a signal to be analyzed, and a sampling time interval Ts is determined; secondly, the read active power signal is preprocessed to obtain a corresponding power fluctuation signal; thirdly, a self-correlation function of the power fluctuation signal is solved, and a system free oscillation signal is obtained; fourthly, based on an extended Prony method, mode identification is carried out on the free oscillation signal to obtain a low frequency oscillation mode frequency and a damping ratio. The electric system low frequency oscillation mode identification method has the advantages that the method is only based on random response signals, operation is simple, the calculation amount is small, and identification accuracy is good.

Description

technical field [0001] The present invention relates to the technical field of power system analysis and control, and in particular, relates to a method for identifying low-frequency oscillation modes of power systems based on correlation functions. Background technique [0002] Low-frequency oscillation is an inherent phenomenon of AC interconnection systems. The improvement of the interconnection degree of the power system, the expansion of the interconnection scale, and the extensive use of fast excitation systems in the power system will make the problem of low-frequency oscillation more prominent. At present, the low frequency oscillation problem seriously threatens the stability of the power system and limits the power transmission capacity of the interconnected grid. Accurately grasping the low-frequency oscillation mode of the system is of great significance to the safe and stable operation of the power system. [0003] Analysis of low-frequency oscillation modes ba...

AI Technical Summary

Problems solved by technology

[0004] In the method of low-frequency oscillation mode identification based on random response signals, the subspace method needs to measure the input signal of the system, but the unmeasurable input signal in the actual power system limits the application of this method; the random subspace method requires a huge matrix Singular value decomposition requires a large amount of calculation and complex algorithms; the method based on the ARMA model is difficult to accurately identify the damping ratio; the random decrement technique combined with Prony’s method, because the random decrement technique estimates the free oscillation signal is relatively rough, making Prony’s The identification of the damping ratio is not accurate enough

[0005] Therefore, in the prior art, there are technical problems that the required power system input signal cannot be measured, the amount of calculation is large, or the method is not accurate enough to identify the damping ratio

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