APIT-MEMD-based electric power system low-frequency oscillation mode identification method

A low-frequency oscillation, power system technology, applied in system integration technology, information technology support systems, reducing/preventing power oscillations, etc., can solve problems such as unsatisfactory, lack of solutions for multivariable signals, and improve small disturbances Stability, solving the problem of power imbalance and correlation between variables, the effect of high identification accuracy

Active Publication Date: 2019-04-19
NORTHEAST DIANLI UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for the correlation problem between multivariate signal data, the error still canno...

Method used

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  • APIT-MEMD-based electric power system low-frequency oscillation mode identification method
  • APIT-MEMD-based electric power system low-frequency oscillation mode identification method
  • APIT-MEMD-based electric power system low-frequency oscillation mode identification method

Examples

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example 1

[0045] An APIT-MEMD-based low-frequency oscillation mode identification method for power systems, see figure 1 , the method includes the following steps:

[0046] 101: Use APIT-MEMD to decompose the multivariate wide-area measured signal s(t), and extract the collection of IMFs representing different oscillation frequencies;

[0047] Wherein, the above wide-area measured signal s(t) is the measured data collected by all PMUs. For example, one PMU collects the rotor angle signal of one generator, and the data collected by n PMUs is the wide-area measured data.

[0048]102: Introduce the Teager energy operator to calculate the energy value of the IMF component, sort the energy value in the same measurement channel, and filter out the IMF component that is strongly correlated with the dominant oscillation mode;

[0049] 103: Use Hilbert-Hung Transform (HHT) to estimate the instantaneous oscillation frequency and instantaneous damping ratio of the dominant oscillation mode corres...

example 2

[0053] The scheme in Example 1 will be further introduced in combination with specific calculation formulas and examples, see the description below for details:

[0054] 201: Utilize the real-time data acquisition function of the PMU device to obtain multi-channel wide-area measurement data, and normalize the measurement data;

[0055] Among them, normalization is the process of standardizing the measurement data. The normalized data is simple and easy to compare, and can fully show the relationship between the standard deviation of the data and retain the original information of the data.

[0056] 202: Introduce APIT-MEMD preprocessing to the PMU measured information in each measurement channel after standardization, where the APIT-MEMD algorithm specifically includes:

[0057] 1) Establish a uniformly distributed direction vector set in the d-dimensional space;

[0058] Among them, mathematically, the (d-1)-dimensional hypersphere belongs to the d-dimensional space, and a d...

example 3

[0109] In the following, combined with specific examples, aiming at the power system oscillation mode identification method based on the APIT-MEMD algorithm proposed in the embodiment of the present invention, this example takes the 16-machine 68-node system as an example to carry out simulation analysis and verification. The topology of the 16-machine 68-node system Figure such as image 3 As shown, see the description below:

[0110] In this calculation example, a three-phase short-circuit fault is set between bus 46 and bus 49, and the fault is set to occur in 0.1s and cut off in 0.2s. Taking G1 as the reference machine, the rotor angle signals of other generator sets relative to G1 are used as signals to be identified. The 16 generators generate a total of 15 sets of relative rotor angle signals, and the sampling frequency is 0.01s. Figure 4 It is the swing curve of the rotor angle of each generator set relative to G1 after a fault occurs. Since the signal tends to be s...

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Abstract

The invention discloses an APIT-MEMD (Adaptive-projection intrinsically transformed multivariate empirical mode decomposition)-based electric power system low-frequency oscillation mode identificationmethod. The APIT-MEMD-based electric power system low-frequency oscillation mode identification method includes the steps: decomposing a multi-component wide-area actual measurement signal s(t) by means of APIT-MEMD, and extracting a set of IMFs (intrinsic mode functions) representing different oscillation frequencies; introducing a Teager energy operator to calculate the energy value of the IMFcomponents, sorting the energy values in the same measurement channel according to the magnitude of the energy values, and selecting the IMF component strongly correlated with the dominant oscillationmode; and estimating the instantaneous oscillation frequency and the instantaneous damping ratio of the dominant oscillation mode corresponding to the strongly correlated IMF component by Hilbert-Huang transform, and averaging the instantaneous oscillation frequency and the instantaneous damping ratio respectively, thereby realizing the identification of the dominant oscillation mode of the powersystem. The APIT-MEMD-based electric power system low-frequency oscillation mode identification method realizes the identification of the low-frequency oscillation mode of the power system based on the actually measured data of the PMU (Phasor Measurement Unit), and improves the identification precision.

Description

technical field [0001] The present invention relates to the field of power systems, in particular to a method for identifying low-frequency oscillation modes of power systems based on Adaptive-projection intrinsically transformed multivariate empirical modedecomposition (APIT-MEMD). Background technique [0002] With the continuous expansion of the scale of interconnected power grids in large regions, the large-scale grid connection of high-penetration renewable energy, and the operation of my country's power system is getting closer and closer to its stable limit operation, the low-frequency oscillation problem of the power system has become a threat to the safe and stable operation of the power grid. important reason for [1-2] . Therefore, identifying the dominant oscillation mode of low-frequency oscillation is of great practical significance to the safety and stability of power systems. At present, the low frequency oscillation mode identification methods of power syste...

Claims

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Application Information

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IPC IPC(8): H02J3/24
CPCH02J3/24Y04S10/22Y02E40/70Y02E60/00
Inventor 姜涛殷祥翔陈厚合李雪李国庆张儒峰张嵩王长江李曙光李本新李晓辉
Owner NORTHEAST DIANLI UNIVERSITY
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