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Electric system low-frequency oscillation mode distinguishing method based on multi-element empirical mode decomposition

An empirical mode decomposition and power system technology, applied in the field of power systems, can solve the problems that multiple channel oscillation modes are difficult to calibrate and cannot reflect the system oscillation relationship well

Active Publication Date: 2019-05-21
STATE GRID LIAONING ELECTRIC POWER RES INST +2
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  • Summary
  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that the traditional empirical mode decomposition identification method is difficult to calibrate the oscillation modes between multiple channels and cannot well reflect the oscillation relationship between regions in the entire system,

Method used

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  • Electric system low-frequency oscillation mode distinguishing method based on multi-element empirical mode decomposition
  • Electric system low-frequency oscillation mode distinguishing method based on multi-element empirical mode decomposition
  • Electric system low-frequency oscillation mode distinguishing method based on multi-element empirical mode decomposition

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Embodiment 1

[0106] A method for identifying low-frequency oscillation modes of power systems based on multivariate empirical mode decomposition in the present invention, see figure 1 , the method includes the following steps:

[0107] 101: Through the improved algorithm based on multivariate empirical mode decomposition, the initial oscillation signal in the power system is decomposed and processed, and multiple eigenmode function components containing different oscillation modes of the system are obtained;

[0108] 102: Using the fast response capability of the Teager energy operator, calculate the relative energy value of each eigenmode function component at the sampling point;

[0109] 103: Integrate and sum the relative energy values ​​of each eigenmode function component at all sampling points to obtain the relative energy of the entire eigenmode function component, and use the energy as the basis for judging to screen out the ones that can reflect the real oscillation of the system ...

Embodiment 2

[0126] The scheme in embodiment 1 is further introduced below in conjunction with specific calculation formulas and examples, see the following description for details:

[0127] 201: Obtain the wide-area measurement information of the power system from the wide-area measurement system, a technical term known to those skilled in the art, and will not repeat it here, and connect the inter-regional connection lines after the low-frequency oscillation of the multi-machine system The active power oscillation signal is used as the multi-channel input signal to be identified, and multivariate empirical mode decomposition is performed on it, including:

[0128] 1) The multi-channel signal is projected in multiple directions in the multi-dimensional space. The selection method of the projection direction vector set is equal-angle sampling. Since the high-dimensional space is invisible, this section takes the three-dimensional space as an example, and multi- The distribution of the proj...

Embodiment 3

[0206] The following combined with specific examples, Figure 4-Figure 10 , and Table 1-Table 2, carry out feasibility verification to the scheme in embodiment 1 and 2, see the following description for details:

[0207] This example takes the dominant oscillation mode identification of the 16-machine 68-node test system as an example to verify the effectiveness of Embodiments 1 and 2 of the present invention. The 16-machine 68-node test system is as follows: Figure 4 shown.

[0208] The fault set in this example is an inter-area three-phase short-circuit fault between node 1 and node 2. The fault occurrence time is 0.1s after the start of the simulation, and the fault lasts for 0.1s. After 0.1s, the circuit breaker on the node 1 side trips. After 0.12s, the circuit breaker on node 2 side tripped. In this example, the active power on the connection line between each area in the 68-node test system is selected as the identification object, the sampling frequency is 100Hz, an...

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Abstract

The invention relates to the field of the electric system, and especially relates to an electric system low-frequency oscillation mode distinguishing method based on multi-element empirical mode decomposition. The method comprises the following steps: performing pre-decomposition processing on a low-frequency oscillation signal in an electric system by using an improvement algorithm based on multi-element empirical mode decomposition, and computing a relative energy value of each eigenmode function component by utilizing quick response capacity of the Teager energy operator, and taking the energy as the judgment evidence to screen out a leading oscillation mode capable of reflecting the real oscillation condition of the system, and rejecting a virtual noise part; and finally computing an oscillation mode parameter corresponding to the leading oscillation mode through a forecast error method, namely frequency and damping ratio, thereby accomplishing the distinguishing of the leading oscillation mode of the electric system. Through the method disclosed by the invention, the leading oscillation mode of the electric system based on the wide area measurement information can be quickly,accurately and efficiently distinguished.

Description

technical field [0001] The invention relates to the field of power systems, in particular to a method for identifying low-frequency oscillation modes of power systems based on multivariate empirical mode decomposition. Background technique [0002] In recent years, the interconnection scale of regional power grids has continued to expand, large-capacity long-distance AC and DC transmission has continued to increase, and large-scale access to renewable energy has made inter-regional low-frequency oscillations become one of the important factors that limit the transmission capacity of interconnected grids and threaten the safe and stable operation of power grids. one. Therefore, it is of great practical significance and engineering practical value to study the low-frequency oscillation identification method of power system under the background of national grid connection and large-scale access of renewable energy. [0003] At present, the dynamic stability analysis methods of...

Claims

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Application Information

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IPC IPC(8): H02J3/24
CPCY02E60/00
Inventor 葛维春张艳军高凯屈超刘爱民孔剑虹刘劲松李斌张建李正文赵鹏姜涛王长江孙志鑫梁旭昱
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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