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Method for identification of low-frequency oscillation mode of electric power system based on Hilbert-Hung and MEMD

A low-frequency oscillation and identification method technology, applied in system integration technology, information technology support system, reducing/preventing power oscillation, etc., can solve problems such as inability to realize multi-channel cooperative identification

Pending Publication Date: 2019-08-16
STATE GRID LIAONING ELECTRIC POWER RES INST +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can effectively identify the dominant oscillation mode from the measured information of the PMU, but the EMD algorithm can only realize single-channel identification, and the identification result is limited to the input signal in the measurement channel, and cannot realize multi-channel collaborative identification

Method used

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  • Method for identification of low-frequency oscillation mode of electric power system based on Hilbert-Hung and MEMD
  • Method for identification of low-frequency oscillation mode of electric power system based on Hilbert-Hung and MEMD
  • Method for identification of low-frequency oscillation mode of electric power system based on Hilbert-Hung and MEMD

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0120] A method for identifying low-frequency oscillation modes of power systems based on Hilbert-Hung and MEMD, comprising the following steps:

[0121] Utilize the real-time data acquisition function of PMU equipment, upload the measurement information of transmission lines and busbar nodes in the actual power grid to the data concentration unit (phasor data concentrator, PDC), and then extract key information for mode identification, where the measurement information includes power generation The rotor angle signal of the machine, the active power in the tie line, the frequency, the speed, and the bus voltage.

[0122] 101: Introduce the MEMD algorithm to preprocess the multivariate PMU measurement information, and obtain the IMF signals representing different oscillation modes in each measurement channel;

[0123] 102: Use the Teager energy operator to estimate the relative energy of the IMF signal in each channel, and identify the key IMF signal containing the dominant os...

Embodiment 2

[0128] The scheme in embodiment 1 is further introduced below in conjunction with specific calculation formulas and examples, see the following description for details:

[0129] 201: Obtain the state measurement information of the power system from the PMU, and standardize the state measurement information;

[0130] Among them, standardization is a process of calculating standard scores. The standardized data is simple and easy to compare, and can fully demonstrate the relationship between the standard deviations of the data and retain the original information of the data.

[0131] 202: The standardized generator rotor angle signal is used as the input signal to be identified, and the MEMD method is introduced to preprocess the multivariate measurement signal to obtain multi-channel IMF signals representing different frequency scales.

[0132] First, a uniformly distributed direction vector set is established in the d-dimensional space, and the multivariate measurement informa...

Embodiment 3

[0223] Below in conjunction with specific experimental data, the scheme in embodiment 1 and 2 is carried out feasibility verification, see the following description for details:

[0224] This example takes the 16-machine 68-node system as an example for simulation analysis. The 16-machine 68-node test system is as follows: image 3 shown.

[0225] In order to verify the feasibility of the method proposed in this paper, the time-domain simulation analysis is carried out through the PSS / E simulation software. The fault setting is that a three-phase short-circuit fault occurs between the bus 46 and the bus 49 in 0.1s, and the fault is removed in 0.2s. Taking generator G1 as a reference machine, the rotor angle signals of other generator sets relative to generator G1 are used as measurement signals. There are 15 sets of relative rotor angle signals for 16 generators, and the sampling time is 0.01s. Figure 4 It is the swing curve of the rotor angle of each generator set relative ...

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Abstract

The invention belongs to the technical field of electrical engineering, and particularly relates to the Hilbert-Hung and the MEMD. The method comprises the steps of: uploading measurement informationof a transmission circuit and a bus node in an actual power grid to a data concentration unit by adopting the real-time data collection function of a PWU device, and extracting key information for mode identification. The method provided by the invention can achieve rapid, accurate and efficient identification for the dominant oscillation mode of the electric power system based on the actually measured information of the PWU, the Teager energy operator criterion is introduced to screen out the key IMF components containing the dominant oscillation mode so as to avoid the influence of noise components in PMU actual measurement data on an identification result; and moreover, the oscillation frequency and the damping ratio change curve are observed by adopting the features of the Hilbert-Hungto track the instant oscillation frequency and the instant damping ratio of the dominant oscillation mode to obtain the mean value of the instant oscillation parameters and estimate the oscillation parameters of the dominant oscillation mode.

Description

technical field [0001] The invention belongs to the field of electrical engineering, in particular to a method for identifying low-frequency oscillation modes of power systems based on Hilbert-Hung and MEMD. Background technique [0002] With the continuous expansion of the grid scale, the gradual formation of ultra-long-distance AC-DC hybrid network architecture, the integration of large-capacity renewable energy into the grid, and the operation of the power system is getting closer to its stable operating limit, the low-frequency oscillation problem of the power system induced by weak damping It is one of the important factors that threaten the safe and stable operation of the system. Therefore, it is of great academic and engineering research value to quickly and accurately identify the dominant oscillation mode of the system for power system security and stability assessment. [0003] At present, the low-frequency oscillation identification methods of power systems main...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/24
CPCH02J3/24H02J3/002H02J2203/20Y04S10/22Y02E40/70Y02E60/00
Inventor 葛维春张艳军葛延峰李斌高凯张建詹克明谢强周志唐俊刺冯占稳张建志姜涛王长江孙志鑫
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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