A low-frequency oscillation mode identification method based on fourth-order mixed average cumulant and improved tls-esprit algorithm
A low-frequency oscillation and modal identification technology, applied in the direction of reducing/preventing power oscillation, reducing the flicker of AC network, and AC network circuit, etc. The effect of small calculation amount, accurate identification result and high identification precision
Active Publication Date: 2020-03-10
FUZHOU UNIV
View PDF1 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
The FFT method has good accuracy and robustness, but this method cannot effectively extract the attenuation characteristics of the oscillation; wavelet analysis has the problem that the wavelet basis is difficult to select and it is difficult to achieve fast online identification; Under the noise condition of the linear-to-noise ratio, there will be a large error in the identification accuracy; HHT analysis is suitable for the extraction of nonlinear and non-stationary signal characteristic parameters. The disadvantage is that there will be endpoint effects and modal aliasing in the process of signal extraction. And the complexity of the algorithm is high, which is not suitable for online identification; ESPRIT method based on space rotation invariant technology, this method has better anti-interference ability and calculation efficiency than Prony
[0004] The harmonic pollution in the power system is becoming more and more serious and complex. The data extracted from the field contains a lot of noise, and the existence of interference will affect the accuracy of the signal identification results.
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.
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0050] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0051] like figure 1 As shown, in this embodiment, Y(t)=e -0.3t cos(2π×0.5t)+e -0.6t The cos(2π×1.1t) test signal is analyzed, and the technical solution of the present invention is described in detail.
[0052] like figure 1 As shown, this embodiment provides a low-frequency oscillation mode identification method based on the fourth-order mixed average cumulant and improved TLS-ESPRIT, which specifically includes the following steps:
[0053]Step S1: Extract the low-frequency oscillation signal of the power system. The low-frequency oscillation signal of the power system can be expressed as follows:
[0054]
[0055] In the formula: 2P is twice the assumed number of signal modes; A m is the amplitude; σ m is the attenuation factor; f m is the frequency; θ m is the initial phase angle; v(t) is Gaussian white noise.
[0056] Step S2: The low-fr...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention relates to a fourth-order mixed mean cumulant and improved TLS-ESPRIT algorithm-based low-frequency oscillation mode identification method. Gaussian color noise is inhibited by using a fourth-order mixed cumulant, a TLS-ESPRIT algorithm is improved, a relative change rate of a singular value is introduced for order determination, and a matrix is constructed by using measured data to carry out low-frequency oscillation mode identification of a power system. According to the fourth-order mixed mean cumulant and improved TLS-ESPRIT algorithm-based low-frequency oscillation mode identification method, detected oscillation frequencies, attenuation factors, oscillation amplitudes and phase information of low-frequency oscillation signals of the power system in different oscillation modes are more accurate.
Description
technical field [0001] The invention relates to the field of safe operation of power systems, in particular to a low-frequency oscillation mode identification method based on a fourth-order mixed average cumulant and an improved TLS-ESPRIT algorithm. Background technique [0002] With the continuous progress of power technology, the interconnection of large power grids has been gradually realized, coupled with the widespread use of fast and high-amplification excitation devices, resulting in frequent occurrence of low-frequency oscillations. The low frequency power oscillation of the power system is a kind of active power oscillation that occurs in the power system, and the oscillation frequency is usually 0.2Hz-2.5Hz. The low-frequency oscillation problem affects the safety and stability of the power system. Therefore, it is the key to ensure the safe and reliable operation of the power system to effectively and quickly identify the low-frequency oscillation mode and study ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & AuthorityPatents(China)
IPC IPC(8): H02J3/24
CPCH02J3/002H02J3/24H02J2203/20
Inventor金涛刘思议刘对张程
OwnerFUZHOU UNIV