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A technology of dynamic signal parameters and acquisition methods, applied in spectral analysis/Fourier analysis and other directions, which can solve problems such as difficulty and poor numerical stability
Active Publication Date: 2014-03-12
STATE GRID CORP OF CHINA +2
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However, directly solving the amplitude, phase frequency and attenuation factor parameters in the Prony algorithm will lead to solving a nonlinear least squares problem, which is difficult and has poor numerical stability
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Embodiment 2
[0070] In this embodiment, we introduce the process of determining the number of frequency components of the dynamic signal in detail.
[0071] Through Example 1, we have determined the autocorrelation matrix R e , and then the SVD algorithm can be applied to determine the matrix R e The effective rank P, and then determine the number of dynamic signal frequency components through the effective rank P, specifically the autocorrelation matrix R e Decomposed into:
[0072] R e =USV T (3)
[0073] where R e represents the autocorrelation matrix, U is p e ×p e dimensional orthogonal matrix, V is (p e +1)×(p e +1) dimensional orthogonal matrix, S is p e ×(p e +1)-dimensional non-negative diagonal matrix, the elements on its diagonal σ kk is the matrix R e singular value of , and satisfies It can be seen that the matrix R e Larger singular values are concentrated in the front section of the diagonal matrix S, so the diagonal matrix Σ composed of the first ...
Embodiment 3
[0087] In this embodiment, we introduce the process of determining the parameters of the dynamic signal model in detail.
[0088] The AR model is established. The AR model assumes that the signal x(n) is obtained by exciting a linear time-invariant discrete-time system with all poles by the zero-mean white noise sequence w(n), namely:
[0089] x ( n ) = - Σ k = 1 C a k x ( n - k ) + w ( n ) - - - ( 5 )
[0090] In the above formula, C is the order of the model, a k is the model parameter of the C-order AR model.
[0091] According to the effe...
Embodiment 4
[0097] In this embodiment, we introduce the parameter determination process of the dynamic signal in detail.
[0098] Using the Prony algorithm, the signal x(n) is regarded as composed of a group of sinusoidal components of decaying oscillations, namely:
[0099] x ( n ) = Σ i = 1 q A i e α i n T s cos ( 2 π f i n T s + θ i ) - - - ( 6 )
...
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Abstract
The application discloses a dynamic signal parameter acquisition method, comprising the steps of selecting dynamic sampling signal sequences of a power grid to form an autocorrelation matrix; determining an effective rank of the autocorrelation matrix and frequency components of the dynamic sampling signal sequence; establishing an auto-regressive (AR) model, and resolving a model parameter of the AR model; through a Prony algorithm, determining a dynamic sampling signal expression and a complex sequence, wherein the dynamic sampling signal sequence is expressed by the complex sequence under a condition of satisfying square error minimization; and introducing a characteristic polynomial root corresponding to the model parameter into the complex sequence, and resolving various parameters of the dynamic sampling signal sequence. The application, instead of directly solving parameters in the Prony algorithm, regards a current moment signal as a linear combination of original various moment signals through an AR parameter model thought, and converts a nonlinear problem into a linear estimation problem, so that the computing process is simpler and computing result is more accurate.
Description
technical field [0001] The present application relates to the technical field of power grid harmonic analysis, and more specifically, to a method for acquiring dynamic signal parameters. Background technique [0002] Due to the wide application of nonlinear devices such as power electronics in the power system, not only the harmonics and interharmonics are increasing, but also there are attenuating oscillation components, which seriously affect the safe operation of the power system. The analysis of harmonics, interharmonics and damped oscillation parameters is of great significance to power systems. [0003] The current harmonic analysis mainly adopts the Fourier method, which regards the signal as composed of a series of non-attenuating sinusoidal frequency components, so it is impossible to give the attenuation oscillation parameters in the dynamic signal, and at the same time, the spectrum leakage and fence effect in the Fourier analysis are also It will cause the probl...
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