CN117239780A - Subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection - Google Patents

Subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection Download PDF

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Publication number
CN117239780A
CN117239780A CN202311219568.8A CN202311219568A CN117239780A CN 117239780 A CN117239780 A CN 117239780A CN 202311219568 A CN202311219568 A CN 202311219568A CN 117239780 A CN117239780 A CN 117239780A
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parameters
offshore wind
wind power
oscillation
mode
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张永峰
林泉
张祯滨
薛飞
徐航
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University of Jinan
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University of Jinan
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Abstract

The application belongs to the technical field of offshore wind power subsynchronous oscillation detection, and particularly relates to a subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection, wherein the subsynchronous oscillation modal parameter identification method comprises the following steps: acquiring grid-connected state parameters of offshore wind power; performing time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component; carrying out Hilbert transformation on the obtained reconstructed single-mode component, and extracting instantaneous parameters of the single-mode component; and identifying the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters, and completing the identification of the modal parameters of the subsynchronous oscillation.

Description

Subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection
Technical Field
The application belongs to the technical field of offshore wind power subsynchronous oscillation detection, and particularly relates to a subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, power systems have gradually developed toward new power systems for generating power from high-ratio power electronic devices and high-ratio new energy, and new energy such as wind power has been rapidly developed. In order to improve the wind energy utilization rate, a large-scale wind farm mostly adopts long-distance transmission. Remote transmission ac transmission systems typically use series compensation capacitors to increase line transfer capability, but energy interaction of the series compensation capacitors with the wind farm tends to cause subsynchronous oscillations (Sub-Synchronous Oscillation, SSO) to occur in the wind farm. The subsynchronous oscillation can cause great damage to the power transmission system in a very short time, so that serious accidents such as damage to the shafting of the fan generator and damage to the transformer are caused. The subsynchronous oscillation phenomenon caused by large-scale wind power grid connection can seriously affect the safe and stable operation of a power system.
When a subsynchronous oscillation fault occurs in a power grid, nonlinear behavior is often shown, and the generated oscillation signal has obvious time-varying characteristics and contains certain noise. Noise signals which are easy to collect and have rich data quantity can be generated by load switching, line parameter adjustment and the like under the normal running state of the power system, and potential subsynchronous oscillation mode information of the power transmission system can be identified from the noise data before subsynchronous oscillation occurs, so that early warning and control support can be provided for the power transmission system. Therefore, how to efficiently and accurately identify the subsynchronous oscillation mode parameters generated in wind power grid connection becomes a key factor affecting the safe and stable operation of the power system.
Disclosure of Invention
In order to solve the problems, the application provides a method and a system for identifying sub-synchronous oscillation modal parameters of offshore wind power grid connection, which are used for representing nonlinear behavior when a sub-synchronous oscillation fault occurs in a power grid, generating an oscillation signal which has obvious time-varying characteristics, extracting the time-varying characteristics of the oscillation signal by time-frequency analysis containing a certain noise combination which can reveal the nonlinear time-varying characteristics of the signal, detecting the sub-synchronous oscillation fault in real time and rapidly and accurately identifying the modal parameters of the sub-synchronous oscillation.
According to some embodiments, the first scheme of the application provides a subsynchronous oscillation modal parameter identification method for offshore wind power grid connection, which adopts the following technical scheme:
a subsynchronous oscillation modal parameter identification method for offshore wind power grid connection comprises the following steps:
acquiring grid-connected state parameters of offshore wind power;
performing time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
carrying out Hilbert transformation on the obtained reconstructed single-mode component, and extracting instantaneous parameters of the single-mode component;
and identifying the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters, and completing the identification of the modal parameters of the subsynchronous oscillation.
As a further technical definition, the acquired grid-connected state parameters of the offshore wind power comprise the output current and the output voltage of the offshore wind power.
As a further technical limitation, the time-frequency processing of the offshore wind power grid-connected state parameters is carried out by adopting short-time Fourier transformation, so that a time-frequency diagram of the offshore wind power grid-connected state parameters is obtained, and the obtained time-frequency diagram comprises a plurality of modal signals and frequency and oscillation changes of each modal signal.
Further, the multi-synchronous compression transformation is utilized to reconstruct signals of offshore wind power grid-connected state parameters, and the multi-modal components are decomposed into single-modal components to obtain reconstructed single-modal components.
As a further technical definition, the process of obtaining the reconstructed unimodal component is: according to the multiple synchronous compression transformation equation, an iteration equation of the instantaneous frequency is obtained; based on the obtained iterative equation of the instantaneous frequency, carrying out independent signal reconstruction on each mode to obtain a reconstructed single-mode component.
As a further technical definition, the instantaneous parameters of the extracted unimodal component include instantaneous amplitude, instantaneous phase and instantaneous frequency.
Further, performing least square fitting on the extracted instantaneous parameters, and fitting the instantaneous amplitude and the instantaneous phase to obtain a damping factor and an oscillation frequency of the subsynchronous oscillation mode signal, thereby completing subsynchronous oscillation mode parameter identification; the identified modal parameters of the subsynchronous oscillation are the damping factor and the oscillation frequency.
According to some embodiments, the second scheme of the application provides a subsynchronous oscillation modal parameter identification system for offshore wind power grid connection, which adopts the following technical scheme:
a subsynchronous oscillation modal parameter identification system for offshore wind grid connection, comprising:
the acquisition module is configured to acquire grid-connected state parameters of offshore wind power;
the reconstruction module is configured to perform time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
an extraction module configured to perform a hilbert transform on the resulting reconstructed unimodal component, extracting instantaneous parameters of the unimodal component;
and the identification module is configured to identify the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters and complete the identification of the modal parameters of the subsynchronous oscillation.
According to some embodiments, a third aspect of the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium having stored thereon a program which, when executed by a processor, performs the steps in a method for identifying sub-synchronous oscillation mode parameters for offshore wind grid integration according to the first aspect of the present application.
According to some embodiments, a fourth aspect of the present application provides an electronic device, which adopts the following technical solutions:
an electronic device comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the processor realizes the steps in the sub-synchronous oscillation mode parameter identification method for offshore wind power grid connection according to the first scheme of the application when executing the program.
Compared with the prior art, the application has the beneficial effects that:
the application combines the multiple synchronous compression transformation and the Hilbert transformation, converts the obtained time domain signal into a complex-form analysis signal, and accurately and conveniently obtains the transient characteristic and the frequency variation of the signal through the analysis signal, thereby identifying the subsynchronous oscillation mode parameters more accurately and rapidly.
The time-frequency analysis method adopted by the application has high resolution and strong noise immunity, overcomes the defects that synchronous compression is sensitive to noise and is not suitable for processing strong frequency modulation signals through multiple synchronous compression transformation, can simultaneously keep high energy aggregation of synchronous compression transformation, overcomes the defect that synchronous extraction transformation cannot perfectly reconstruct signals, and realizes reconstructed signals.
The subsynchronous oscillation modal parameter identification method has the advantages of high accuracy, small calculated amount and high operation speed, can rapidly and accurately realize the subsynchronous oscillation modal parameter identification, is suitable for online application, has great potential in the aspects of subsynchronous oscillation online monitoring and early warning, and improves the safe reliability of operation of the power system with offshore wind power grid connection.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification, illustrate and explain the embodiments and together with the description serve to explain the embodiments.
FIG. 1 is a flowchart of a method for identifying sub-synchronous oscillation mode parameters of offshore wind grid connection in a first embodiment of the application;
FIG. 2 is a general step diagram of a method for identifying sub-synchronous oscillation mode parameters of offshore wind grid connection in a first embodiment of the application;
FIG. 3 is a time-frequency diagram of a numerical example in accordance with a first embodiment of the present application;
FIG. 4 is a modal exploded view of a numerical example in accordance with a first embodiment of the present application;
FIG. 5 is a diagram illustrating an error curve between an original signal and a reconstructed signal according to a first embodiment of the present application;
FIG. 6 is a schematic view of transient parameter extraction of mode 1 according to a first embodiment of the present application;
FIG. 7 is a schematic structural diagram of a wind farm series compensation grid-connected simulation model based on a DFIG in a first embodiment of the present application;
FIG. 8 is a diagram showing waveforms of the subsynchronous oscillation current of case 1 according to the first embodiment of the present application;
fig. 9 is a schematic diagram of a subsynchronous oscillation current waveform of case 2 in the first embodiment of the present application;
FIG. 10 is a diagram showing waveforms of the subsynchronous oscillation current according to the first embodiment of the present application in case 3;
fig. 11 is a structural block diagram of a subsynchronous oscillation mode parameter identification system for offshore wind power grid connection in a second embodiment of the application.
Detailed Description
The application will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Embodiments of the application and features of the embodiments may be combined with each other without conflict.
Example 1
The embodiment of the application introduces a subsynchronous oscillation modal parameter identification method for offshore wind power grid connection.
The method for identifying the subsynchronous oscillation modal parameters of the offshore wind power grid connection shown in fig. 1 and 2 comprises the following steps:
acquiring grid-connected state parameters of offshore wind power;
performing time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
carrying out Hilbert transformation on the obtained reconstructed single-mode component, and extracting instantaneous parameters of the single-mode component;
and identifying the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters, and completing the identification of the modal parameters of the subsynchronous oscillation.
As one or more embodiments, the signals collected by the PMU device are processed in a time-frequency manner by utilizing multiple synchronous compression transformation to obtain a time-frequency diagram of the signals, so that the signals can be clearly seen to contain several modes and the frequency and oscillation change conditions of each mode, and meanwhile, the complex multi-component signals are decomposed into single inherent mode components for subsequent processing.
The principle of the multiple synchronous compression transformation is as follows:
the single component time-varying signal of voltage/current can be modeled as:
wherein A (t) represents the amplitude of the voltage or current signal,representing the phase of the signal. i is an imaginary unit and t is time. Thus, the signal is subjected to a fast fourier transform, STFT, process:
where g (u) is a window function and u is an integral variable.
According to the taylor formula,
A(u)=A(t)
therefore, s (t) can be expressed as: s (u) =a (t) e i(φ(t)+φ′(t)(u-t)) Bringing it into the above formula (2) to obtain:
wherein,fourier transform of g (g), and +.>Where ω is frequency. The two sides of the method can derive t, and the method can obtain:
when G (t, ω) is not equal to 0, the estimated instantaneous frequency of the signal is
The expression for further deriving the synchronous compression transformation is:
wherein δ (g) is a dirichlet function. Based on the thought, by iterating the synchronous compression transformation for a plurality of times, the following multiple synchronous compression transformation equation can be obtained:
introducing a numerical example to simulate a subsynchronous oscillation signal:
after the first step of processing, a clear and high-energy aggregated time-frequency diagram can be obtained, and it can be seen that the signal contains three modes in total, the frequencies are respectively 15Hz, 20Hz and 25Hz, the oscillations of 15Hz and 20Hz are gradually converged, and the oscillations of 25Hz are gradually diverged. In addition, the single-component signal diagram after modal decomposition is shown in fig. 4, so that the complex signal can be accurately decomposed into three independent intrinsic modal components (IMFs).
As one or more embodiments, the method utilizes multiple synchronous compression transformation to reconstruct signals of each inherent modal component so as to eliminate the influence of interference, and clear obstacles for subsequent parameter identification. The specific process of signal reconstruction is as follows:
(1) According to equation (8) above, the iterative equation for the corresponding instantaneous frequency is:
in each iteration, the multiple synchronous compression transform obtains a new frequency that is closer to the real instantaneous frequency of the signal by redistributing the scattered STFT coefficients.
(2) Each mode can be reconstructed by using the time-frequency coefficient of the instantaneous frequency, i.e
Wherein s is k (t) represents the mode after reconstruction of the kth mode, ds represents the reconstruction bandwidth of the SST,representing the instantaneous frequency of the kth modality.
(3) And (3) carrying out independent signal reconstruction on each mode, and then adding the reconstructed modes to obtain a reconstructed signal of the original signal before mode decomposition.
The improvement point of the part is that the reconstruction signal of the original signal is obtained by carrying out signal reconstruction and then summation on each single mode after the mode decomposition of the original signal, and the obtained reconstruction signal is more accurate.
The above reconstruction is performed on the decomposed signal of the formula (9), and then the error between the original signal and the reconstructed signal can be calculated by making a difference between the original signal and the reconstructed signal, and the error curve is shown in fig. 5. The reconstruction error is almost 0, which indicates that perfect reconstruction can be realized, and the superior performance of the multi-synchronous compression transformation in terms of modal decomposition and signal reconstruction is proved.
As one or more embodiments, hilbert transformation is performed on each reconstructed single-mode component, and parameters such as instantaneous frequency, instantaneous amplitude, instantaneous phase and the like of each mode are extracted.
For a time signal X (t), its hilbert transform is:
a conjugate pair Z is formed according to X and Y,
wherein a (t) is the instantaneous amplitude,is of phase and
the instantaneous frequency
As one or more embodiments, least square fitting is performed on the extracted instantaneous parameters, and the frequency and attenuation factors of each modal signal are identified, namely fitting is performed on the instantaneous amplitude and the instantaneous phase, the slope of the straight line after fitting is respectively the attenuation factor and the oscillation frequency of the subsynchronous oscillation modal signal, so as to complete subsynchronous oscillation modal parameter identification.
The least squares fitting process is:
(1) Collecting data: the instantaneous parameters extracted after Hilbert transformation are used as fitting data, wherein time is used as an independent variable, and the instantaneous parameters are used as dependent variables.
(3) Selecting a fitting function: a linear fitting function y=ax+b is selected. Wherein a and b are fitting parameters.
(3) Calculating residual errors: for each data point (x i ,y i ) By substituting it into the fitting function to obtain the predicted value of the instantaneous parameter, the difference between the predicted value and the actual value, i.e. the residual e, is calculated i =y i -(ax i +b). The residual represents the deviation between the fit function prediction and the actual data.
(4) The sum of squares of the residuals for all data points is calculated.
Sum of squares of residuals:where n is the number of data points and this sum of squares is the objective function to be minimized.
(5) Solving parameters: the square difference is calculated with respect to the parameters of the fitting function by mathematical methods such as differentiation, and then the derivative is made to be zero, so that the parameter value is solved, and the parameter minimizing the square difference is found.
Differentiating the slope a to make the derivative zero:the simplification is as follows:differentiating the intercept b to make the derivative zero: />The simplification is as follows: />The values of fitting parameters a and b can be solved by combining the two equations.
(6) Fitting results: after the parameters that minimize the square error are obtained, a best fit function can be obtained that can be used to predict the value of the corresponding factor variable.
Performing Hilbert transform on each modal component of the numerical calculation example (9) and extracting instantaneous parameters (instantaneous amplitude, instantaneous phase and instantaneous frequency) of each mode, then identifying SSO modal parameters (attenuation factors and oscillation frequencies) by least square fitting, wherein the extraction process of the mode 1 is shown in FIG. 6, and comparing the final identification result with a theoretical value as shown in Table 1; the error of the identification result is extremely small, and the effectiveness of the method provided by the embodiment is verified through a numerical example.
Table 1 modal parameter identification results for three methods
Calculation case analysis
Establishing a wind power plant grid-connected simulation model with series capacitance compensation as shown in fig. 7, and simulating three different subsynchronous oscillation faults by changing wind speed and series compensation degree, wherein the series compensation degree of the capacitance is the ratio of capacitance reactance of a series capacitor to line reactance as shown in table 2; the current waveforms of the subsynchronous oscillation signals of case 1, case 2, and case 3 are shown in fig. 8, 9, and 10, respectively.
TABLE 2 three subsynchronous oscillation conditions
The method provided by the embodiment is used for identifying the modal parameters, and the identification result is compared with the Prony method, and the result is shown in Table 3, so that the identification accuracy of the method of the embodiment is high. In addition, the change condition of the oscillation can be judged through identifying the subsynchronous oscillation attenuation factor, so that a conclusion is obtained: the attenuation factor is smaller than 0, the oscillation converges, and attention is not required; the attenuation factor is greater than 0, the oscillation diverges, and timely warning and measures are needed to be taken for suppression. Provides basis for the next step of subsynchronous oscillation on-line detection and alarm.
TABLE 3 identification of modal parameters for synchronous oscillations
Compared with other methods, the time-frequency analysis method used in the embodiment has higher resolution and stronger noise immunity, the multiple synchronous compression conversion overcomes the defects that synchronous compression is sensitive to noise and is not suitable for processing strong frequency modulation signals, simultaneously retains the characteristic of high energy aggregation of synchronous compression conversion, overcomes the defect that synchronous extraction conversion cannot perfectly reconstruct signals, can almost perfectly reconstruct signals, and is a more perfect time-frequency analysis method; the method has the advantages of high identification precision, small calculated amount and high running speed, can realize the modal parameter identification of the subsynchronous oscillation more quickly and accurately, is suitable for online application, and has great potential in the aspects of online monitoring and early warning of the subsynchronous oscillation.
Example two
The second embodiment of the application introduces a subsynchronous oscillation modal parameter identification system for offshore wind power grid connection.
The subsynchronous oscillation modal parameter identification system for offshore wind power grid connection shown in fig. 11 comprises:
the acquisition module is configured to acquire grid-connected state parameters of offshore wind power;
the reconstruction module is configured to perform time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
an extraction module configured to perform a hilbert transform on the resulting reconstructed unimodal component, extracting instantaneous parameters of the unimodal component;
and the identification module is configured to identify the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters and complete the identification of the modal parameters of the subsynchronous oscillation.
The detailed steps are the same as those of the sub-synchronous oscillation mode parameter identification method for offshore wind power grid connection provided in the first embodiment, and are not described herein again.
Example III
The third embodiment of the application provides a computer readable storage medium.
A computer readable storage medium having a program stored thereon, which when executed by a processor, performs the steps in a method for identifying sub-synchronous oscillation mode parameters for offshore wind grid connection according to an embodiment of the present application.
The detailed steps are the same as those of the sub-synchronous oscillation mode parameter identification method for offshore wind power grid connection provided in the first embodiment, and are not described herein again.
Example IV
The fourth embodiment of the application provides electronic equipment.
An electronic device comprises a memory, a processor and a program stored in the memory and capable of running on the processor, wherein the processor realizes the steps in the sub-synchronous oscillation mode parameter identification method for offshore wind power grid connection according to the embodiment of the application when executing the program.
The detailed steps are the same as those of the sub-synchronous oscillation mode parameter identification method for offshore wind power grid connection provided in the first embodiment, and are not described herein again.
The above description is only a preferred embodiment of the present embodiment, and is not intended to limit the present embodiment, and various modifications and variations can be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.

Claims (10)

1. A subsynchronous oscillation modal parameter identification method for offshore wind power grid connection is characterized by comprising the following steps:
acquiring grid-connected state parameters of offshore wind power;
performing time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
carrying out Hilbert transformation on the obtained reconstructed single-mode component, and extracting instantaneous parameters of the single-mode component;
and identifying the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters, and completing the identification of the modal parameters of the subsynchronous oscillation.
2. The method for identifying sub-synchronous oscillation mode parameters for offshore wind power grid connection according to claim 1, wherein the acquired grid-connected state parameters of offshore wind power comprise output current and output voltage of offshore wind power.
3. The method for identifying the subsynchronous oscillation modal parameters of the offshore wind power grid connection as claimed in claim 1, wherein the time-frequency processing of the offshore wind power grid connection state parameters is carried out by short-time Fourier transform, a time-frequency diagram of the offshore wind power grid connection state parameters is obtained, and the obtained time-frequency diagram comprises a plurality of modal signals and frequency and oscillation changes of each modal signal.
4. The method for identifying sub-synchronous oscillation mode parameters of offshore wind power grid connection according to claim 3, wherein the method is characterized in that signal reconstruction of offshore wind power grid connection state parameters is carried out by utilizing multiple synchronous compression transformation, and multi-mode components are decomposed into single-mode components to obtain reconstructed single-mode components.
5. The method for identifying sub-synchronous oscillation mode parameters of offshore wind power grid connection as set forth in claim 1, wherein the process of obtaining the reconstructed single-mode component is as follows: according to the multiple synchronous compression transformation equation, an iteration equation of the instantaneous frequency is obtained; based on the obtained iterative equation of the instantaneous frequency, carrying out independent signal reconstruction on each mode to obtain a reconstructed single-mode component.
6. A method of identifying sub-synchronous oscillation mode parameters for offshore wind grid integration as claimed in claim 1 wherein the extracted instantaneous parameters of the single mode component include instantaneous amplitude, instantaneous phase and instantaneous frequency.
7. The method for identifying the subsynchronous oscillation mode parameters of the offshore wind power grid connection as claimed in claim 6, wherein the extracted instantaneous parameters are subjected to least square fitting, instantaneous amplitude and instantaneous phase are fitted, so that attenuation factors and oscillation frequencies of the subsynchronous oscillation mode signals are obtained, and subsynchronous oscillation mode parameter identification is completed; the identified modal parameters of the subsynchronous oscillation are the damping factor and the oscillation frequency.
8. The utility model provides a sub-synchronous oscillation mode parameter identification system of marine wind power integration which is characterized in that includes:
the acquisition module is configured to acquire grid-connected state parameters of offshore wind power;
the reconstruction module is configured to perform time-frequency processing on the acquired grid-connected state parameters based on multiple synchronous compression transformation to obtain a reconstructed single-mode component;
an extraction module configured to perform a hilbert transform on the resulting reconstructed unimodal component, extracting instantaneous parameters of the unimodal component;
and the identification module is configured to identify the damping factor and the oscillation frequency of the subsynchronous oscillation according to the extracted instantaneous parameters and complete the identification of the modal parameters of the subsynchronous oscillation.
9. A computer readable storage medium having stored thereon a computer program, which when executed by a processor realizes the steps of the sub-synchronous oscillation mode parameter identification method of offshore wind grid connection according to any of claims 1-7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the subsynchronous oscillation mode parameter identification method of offshore wind grid connection as claimed in any of claims 1-7 when executing the program.
CN202311219568.8A 2023-09-20 2023-09-20 Subsynchronous oscillation modal parameter identification method and system for offshore wind power grid connection Pending CN117239780A (en)

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