A new energy station wide frequency oscillation online early warning method based on virtual split ratio

Abstract

The application discloses a new energy station wide frequency oscillation online early warning method based on a virtual shunt ratio, and belongs to the technical field of power system stability analysis and control. The method comprises the following steps: injecting a harmonic small disturbance signal into a current or voltage sampling value of a new energy converter, synchronously recording a static var generator (SVG) branch current waveform and extracting a disturbance component, and calculating a virtual shunt ratio; obtaining wide frequency band data through frequency sweeping and obtaining a domain expression of the virtual shunt ratio by using vector fitting; solving the zero point of the expression to obtain station characteristic roots, and judging and warning an oscillation risk according to the position of the characteristic roots on a complex plane. The application does not need to obtain control parameters and line parameters of the new energy converter in the station, and does not need a high-power disturbance source, thereby solving the problems of high parameter dependency, difficult modeling and large calculation amount of the existing method, and realizing rapid online early warning of the wide frequency oscillation risk in the full "black box" state of the new energy station.

Description

Technical Field

[0001] This invention relates to the field of power system stability analysis and control technology, and in particular to an online early warning method for broadband oscillations in new energy power plants based on virtual shunt ratio. The proposed "virtual shunt ratio" is used to quickly assess the small-signal stability (impedance stability) of new energy power plants such as wind power and photovoltaic power plants online, thereby enabling early warning of broadband oscillation risks in new energy power plants. Background Technology

[0002] As the penetration rate of new energy sources in the power grid continues to increase, the broadband oscillation problem caused by the connection of new energy power plants such as wind power and photovoltaic power to weak power grids is becoming increasingly prominent. In order to ensure the safe and stable operation of the power grid, it is crucial to assess and warn of the broadband oscillation risk of new energy power plants in a timely and effective manner.

[0003] In existing technologies, the main methods for assessing broadband oscillation risks at new energy power plants include the following four:

[0004] Method 1: Hardware-in-the-loop simulation test.

[0005] Existing literature (such as "Risk Assessment of Sub / Supersynchronous Oscillations in Wind Power Based on Hardware-in-the-Loop Testing" published by Ma Ningning et al. in the Proceedings of the CSEE, Vol. 42, No. 15, 2022) discloses the simulation and analysis of sub / supersynchronous oscillation instability of actual wind turbines connected to the grid by establishing an electromagnetic transient simulation model of actual wind / photovoltaic units or building a hardware-in-the-loop testing platform for controllers, and testing and assessing the potential sub / supersynchronous oscillation risks of wind turbines before grid connection.

[0006] The drawbacks of this method are that the hardware-in-the-loop test platform is cumbersome to build, cannot fully simulate the characteristics of actual new energy power stations, and cannot achieve online assessment of oscillation risks.

[0007] Method 2: Impedance modeling and analysis.

[0008] Existing literature (such as "A Risk Assessment Method for New Energy Grid-Connected Oscillation Based on Frequency Domain Impedance" published by Xiong Xinyao et al. in High Voltage Engineering, Vol. 50, No. 08, 2024) discloses the establishment of an impedance model for wind power / photovoltaic new energy power plants based on known and detailed control parameters and circuit parameters. Combined with the impedance models of circuit components such as transmission lines and transformers, an equivalent impedance model of the power grid is obtained. Impedance stability analysis is carried out on the impedance model of the new energy power plant and the equivalent impedance model of the power grid to identify the oscillation and instability risk of the new energy power plant.

[0009] The drawback of this method is that the actual wind power / photovoltaic unit controller is a "black box", so it is difficult to obtain the control parameters and circuit parameters of the new energy power station, and thus it is impossible to perform impedance theory modeling and impedance stability analysis.

[0010] Method 3: Generalized short-circuit ratio assessment.

[0011] Existing literature (such as Xin Huanhai et al.'s "Estimation of the Capacity Ratio of Grid-type and Grid-following Converters to Improve the Stability of New Energy Power Stations" published in the Proceedings of the Chinese Society for Electrical Engineering, Vol. 44, No. 14, 2024) discloses that the small-signal stability of new energy power stations is evaluated by the "generalized short-circuit ratio", and that the small-signal stability of new energy power stations is improved by configuring grid-type converters of a certain capacity in the power station.

[0012] The drawback of this method is that the definition and calculation of the "generalized short-circuit ratio" are relatively complex, and the actual calculation process is cumbersome.

[0013] Method 4: Data-model fusion driven.

[0014] Existing literature (such as "Online Identification and Stability Assessment of Broadband Impedance of New Energy Power Stations Based on Data-Model Fusion Driven" published by Rao Yiming et al. in the Proceedings of the Chinese Society for Electrical Engineering, Vol. 44, No. 07, 2024) discloses a data-driven method to obtain the broadband impedance of each new energy unit offline, then aggregate the impedance of the new energy power station according to the topology and line parameters, and finally perform online analysis of the small-signal stability of the new energy power station based on the Nyquist criterion.

[0015] The drawback of this method is that offline training of the broadband impedance of each new energy unit requires measuring the impedance characteristics of the new energy unit at a large number of operating points to establish a training dataset, and actually obtaining this training data is time-consuming and laborious.

[0016] In summary, most existing technologies require access to actual control parameters or data-driven offline training to establish impedance models for wind / solar power units, then perform impedance aggregation to obtain the impedance characteristics of the power plant, and finally conduct oscillation risk analysis based on stability criteria. However, the control parameters of actual power plants are difficult to obtain (the controller is a "black box"), making the construction of impedance models for wind / solar power units difficult and time-consuming. Furthermore, the drift of circuit parameters such as transformers and lines in the power plant introduces errors in impedance aggregation, potentially leading to misjudgments of stability results.

[0017] Therefore, there is an urgent need for a practical, simple, and easy-to-implement online early warning method for broadband oscillations in new energy power plants. This method should overcome the dependence of existing technologies on actual power plant parameters, eliminate the need for prior knowledge of the control parameters of new energy units and the line parameters of the power plant, and avoid the time-consuming and laborious process of modeling / measuring the impedance characteristics of each new energy unit and performing impedance aggregation calculations. It should be able to quickly identify the oscillation risks existing in new energy power plants online and provide early warnings. Summary of the Invention

[0018] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art, which relies on detailed model parameters, is cumbersome in calculation, and is difficult to evaluate online, and to provide a broadband oscillation online early warning method for new energy power plants based on virtual split ratio.

[0019] To achieve the above objectives, this invention provides an online early warning method for broadband oscillations in renewable energy power plants based on virtual shunt ratio, comprising the following steps:

[0020] S1. Inject a virtual disturbance signal into the current or voltage sampling value of the first converter in the new energy power station;

[0021] S2. Record the current waveform of the second equipment branch in the new energy power station, and extract the disturbance current component with the same frequency as the virtual disturbance signal.

[0022] S3. Calculate the virtual shunt ratio at the current disturbance frequency based on the injected virtual disturbance signal and the extracted disturbance current component.

[0023] S4. Change the disturbance frequency and repeat steps S1-S3 to obtain the virtual shunt ratio value over a wide frequency range.

[0024] S5. Use vector fitting to fit the obtained virtual shunt ratio values ​​within the wide frequency range as... Domain expression ;

[0025] S6, Solve the above Domain expression The zero point is used to obtain the characteristic roots of the new energy power station;

[0026] S7. Based on the position of the characteristic roots on the complex plane, determine the stability of the new energy power station, and issue an early warning if there is a risk of oscillation.

[0027] Furthermore, in step S1, the first converter is a grid-connected voltage source converter (VSC) in the new energy power station.

[0028] Furthermore, in step S2, the second device is a static var generator (SVG).

[0029] Further, in step S1, the virtual disturbance signal is a three-phase sinusoidal signal with an amplitude of a preset value (approximately 5% of the steady-state value of the converter output current or voltage) and a frequency of... .

[0030] Further, in step S3, the virtual shunt ratio is calculated as follows: virtual shunt ratio = value of injected virtual disturbance signal / value of disturbance current component of extracted second device branch.

[0031] Furthermore, the virtual split ratio of Domain expression It includes the Nyquist criterion factor related to the stability of renewable energy power plants and the power grid; when renewable energy power plants tend to oscillate and become unstable, the Nyquist criterion factor approaches zero, leading to... Approaching zero.

[0032] Furthermore, the specific criteria for determining stability based on the position of the eigenvalues ​​in the complex plane in step S7 are as follows:

[0033] If the eigenvalues ​​are located in the left half of the complex plane and far from the imaginary axis, then the new energy power station is determined to be in a small-signal stable state.

[0034] If the characteristic roots are located near the imaginary axis or in the right half of the complex plane, it is determined that the new energy power station has a risk of broadband oscillation and an early warning is issued.

[0035] Furthermore, when the virtual disturbance signal is a pulse wave or a binary sequence broadband signal, after injecting the broadband signal, the broadband disturbance current component can be directly extracted from the response signal without performing the frequency sweeping step of changing the disturbance frequency in step S4.

[0036] Furthermore, the method also includes an alternative implementation: injecting a virtual current disturbance signal into the current sampling value of the static var generator (SVG), and extracting the disturbance current component in the new energy converter branch to calculate the virtual shunt ratio, with the remaining steps remaining unchanged.

[0037] Therefore, the present invention, employing the above-described structure, provides an online early warning method for broadband oscillations in renewable energy power plants based on virtual shunt ratios, which has the following beneficial effects:

[0038] (1) The present invention uses a perturbation frequency of The small current disturbance signal sine wave is injected into the current sampling value of the new energy converter, which does not require a high-power actual disturbance source, making it easy to operate and low in cost.

[0039] (2) The implementation of this invention does not require control parameters of new energy units and line parameters of the station, nor does it require measuring the impedance of each new energy unit one by one. It is time-saving, simple in steps and requires less calculation.

[0040] (3) This invention can identify the oscillation mode of a new energy power station by using the virtual shunt ratio in the completely "black box" state of the new energy power station, and realize the rapid early warning of the oscillation risk of the new energy power station.

[0041] (4) Simulation results show that the trend of the characteristic roots calculated by the present invention with the change of grid inductance is completely consistent with the actual stability state, and can accurately identify the stable and critical stable states of new energy power plants.

[0042] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention;

[0044] Figure 2 This is a schematic diagram illustrating the implementation of the present invention in a new energy power station;

[0045] Figure 3 This is a diagram illustrating the effect of the present invention in achieving oscillation early warning by calculating the characteristic roots of new energy power plants through virtual diversion ratio. Detailed Implementation

[0046] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0047] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0048] Example 1

[0049] This invention provides an online early warning method for broadband oscillations in renewable energy power plants based on virtual shunt ratio, comprising the following steps:

[0050] S1. Inject a virtual disturbance signal into the current or voltage sampling value of the first converter in the new energy power station;

[0051] S2. Record the current waveform of the second equipment branch in the new energy power station, and extract the disturbance current component with the same frequency as the virtual disturbance signal.

[0052] S3. Calculate the virtual shunt ratio at the current disturbance frequency based on the injected virtual disturbance signal and the extracted disturbance current component.

[0053] S4. Change the disturbance frequency and repeat steps S1-S3 to obtain the virtual shunt ratio value over a wide frequency range.

[0054] S5. Use vector fitting to fit the obtained virtual shunt ratio values ​​within the wide frequency range as... Domain expression ;

[0055] S6, Solve the above Domain expression The zero point is used to obtain the characteristic roots of the new energy power station;

[0056] S7. Based on the position of the characteristic roots on the complex plane, determine the stability of the new energy power station, and issue an early warning if there is a risk of oscillation.

[0057] See Figure 2 This embodiment uses a renewable energy power station containing two grid-connected voltage-source converters (VSCs) and one static var generator (SVG) as an example. VSC1 and VSC2 represent renewable energy units such as wind power and solar power.

[0058] The specific implementation steps of the online early warning method for broadband oscillations in renewable energy power plants based on virtual current split ratio of this invention are as follows:

[0059] Step 1: Inject virtual perturbation (Step S1)

[0060] First, a disturbance frequency of 1000 Hz is superimposed on the three-phase current sampling values ​​of the new energy converter VSC1. The three-phase sine wave is used as a virtual current disturbance signal. The injection here is a superposition of signal levels, which does not require high-power physical equipment.

[0061] In virtual current disturbance signal Under the excitation, the output disturbance response equation of the new energy converter VSC1 is:

[0062] (1);

[0063] in, This represents the disturbance current output by converter VSC1. This indicates the disturbance voltage at the VSC1 port. This represents the equivalent admittance of VSC1. Related to the control of VSC1.

[0064] Step 2: Establishing the circuit equations

[0065] Based on the topology of the VSC1 branch of the converter, the following equation can be obtained:

[0066] (2);

[0067] in, This indicates the disturbance voltage at the busbar of the new energy power station. The line admittance of the VSC1 branch of the converter.

[0068] Furthermore, based on circuit principles, the circuit equations for the converter VSC2 branch, the SVG branch, and the grid branch can be obtained:

[0069] (3);

[0070] in, , , These are the disturbance currents of the VSC2 branch of the converter, the SVG branch, and the grid branch, respectively. For the equivalent admittance of SVG, It is the equivalent admittance of the power grid.

[0071] Step 3: Derive the virtual split ratio

[0072] Based on equations (1)-(3), and combined with the disturbance current relationship of each branch. (i.e., Kirchhoff's Current Law), through derivation, the expression for the disturbance current of the SVG branch can be obtained as follows:

[0073] (4);

[0074] in, , Let represent the total admittance of the VSC1 and VSC2 branches of the converter, respectively. Then equation (4) can be simplified to:

[0075] (5);

[0076] Define virtual split ratio For the injected virtual current perturbation Disturbance current of SVG branch The ratio, that is:

[0077] (6);

[0078] Step 4: Principles of Stability Analysis

[0079] In equation (6), This is the Nyquist criterion expression for the aggregate admittance of a renewable energy power plant versus its grid impedance. When... The Nyquist curve is about to encircle At this time, there is a risk of broadband oscillation between the new energy power station and the power grid. The value will approach 0.

[0080] Similarly, This is the Nyquist criterion expression between the converter VSC1 admittance and its line impedance. When the Nyquist curve is about to encircle the point (-1, j0), branch 1 within the new energy power station is at risk of broadband oscillation. The value will also approach 0.

[0081] Therefore, when the system tends to be unstable, the numerator in equation (6) tends to be 0, i.e., the virtual split ratio. It approaches 0.

[0082] Step 5: Online Early Warning Implementation Process

[0083] See Figure 1 The specific online early warning steps are as follows:

[0084] Initialize perturbation frequency And amplitude.

[0085] S100, Inject a disturbance frequency of [frequency value] into the current sampling value of the new energy converter VSC1. The virtual current disturbance signal.

[0086] S200: Record the current waveform of the SVG branch and extract the perturbation frequency using signal processing methods (such as FFT). The disturbance current value below .

[0087] S300, Calculate at the disturbance frequency The value of the virtual split ratio .

[0088] S400: Determine if the wideband calculation is complete (i.e., whether the preset frequency range has been scanned). If not, change the perturbation frequency. If yes, return to step S1; otherwise, proceed to the next step.

[0089] S500 uses vector fitting to fit the discrete virtual shunt ratio values ​​obtained from frequency sweep into a specific s-domain expression. .

[0090] S600, Order Solve for the zeros of the equation to obtain the characteristic roots. .

[0091] S700, Provide early warning based on the location of characteristic roots:

[0092] If the characteristic root Located in the left half-plane and far from the imaginary axis ( and The relatively large value indicates that the new energy power station has a stable small signal.

[0093] If the characteristic root Located near the imaginary axis or even in the right half-plane This indicates that the new energy power station has a wide-frequency oscillation risk under this operating condition, and oscillation risk warning is required.

[0094] Example verification

[0095] See Figure 3 , build Figure 2 The simulation model of the new energy power station shown was used for verification. Three operating conditions were set with grid inductance of 44mH, 49mH and 54mH.

[0096] Simulation results show:

[0097] The power station is in a stable state when the grid inductance is 44mH. The characteristic roots calculated by this invention are located in the left half-plane and far from the imaginary axis.

[0098] When the grid inductance is 49mH, the power station is in a critically stable state. The characteristic roots calculated by this invention approach the imaginary axis, indicating a risk of oscillation and instability in the power station.

[0099] The above results and Figure 3 The simulation waveforms shown are completely consistent, verifying the effectiveness of the present invention.

[0100] Other embodiments (alternatives)

[0101] Changing the type of injected disturbance signal: In addition to sine waves, wideband signals such as pulse waves and binary sequences can also be used. In this case, since the injected signal itself contains wideband components, disturbance current components at multiple frequencies can be directly extracted from a single response without the need for a frequency sweep step to change the disturbance frequency, further improving the speed.

[0102] Change the injection and measurement location: A virtual current disturbance signal can be injected into the current sampling value of the SVG to calculate the disturbance current generated by the new energy converter branch (such as VSC1), thereby calculating the virtual shunt ratio. The remaining calculation steps are the same.

[0103] Change the disturbance injection amount: A virtual voltage disturbance can be injected into the voltage sampling value of the new energy converter, and the rest of the calculation steps are the same.

[0104] Example 2

[0105] The present invention provides an online early warning method for broadband oscillations in new energy power plants based on virtual shunt ratio, which also includes an alternative implementation method: injecting virtual current disturbance signals into the current sampling values ​​of the static var generator (SVG), and extracting the disturbance current components in the new energy converter branch to calculate the virtual shunt ratio, with the remaining steps remaining unchanged.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for online early warning of broadband oscillations in renewable energy power plants based on virtual shunt ratio, characterized in that, Includes the following steps: S1. Inject a virtual disturbance signal into the current or voltage sampling value of the first converter in the new energy power station; S2. Record the current waveform of the second equipment branch in the new energy power station, and extract the disturbance current component with the same frequency as the virtual disturbance signal. S3. Calculate the virtual shunt ratio at the current disturbance frequency based on the injected virtual disturbance signal and the extracted disturbance current component. S4. Change the disturbance frequency and repeat steps S1-S3 to obtain the virtual shunt ratio value over a wide frequency range. S5. Use vector fitting to fit the obtained virtual shunt ratio values ​​within the wide frequency range as... Domain expression ; S6, Solve the above Domain expression The zero point is used to obtain the characteristic roots of the new energy power station; S7. Determine the stability of the new energy power station based on the position of the characteristic roots on the complex plane, and issue an early warning if there is a risk of oscillation. In step S1, the first converter is a grid-connected voltage source type new energy converter (VSC) within the new energy power station. In step S2, the second device is a static var generator (SVG). In step S3, the formula for calculating the virtual shunt ratio is: Virtual shunt ratio = Value of injected virtual disturbance signal / Value of disturbance current component of extracted second device branch.

2. The online early warning method for broadband oscillations in new energy power plants based on virtual split ratio according to claim 1, characterized in that, In step S1, the virtual disturbance signal is a three-phase sine wave signal with an amplitude of a preset value and a frequency of [value missing]. .

3. The method for online early warning of broadband oscillations in new energy power plants based on virtual split ratio according to claim 1, characterized in that, The virtual split ratio Domain expression It includes the Nyquist criterion factor related to the stability of renewable energy power plants and the power grid; when renewable energy power plants tend to oscillate and become unstable, the Nyquist criterion factor approaches zero, leading to... Approaching zero.

4. The method for online early warning of broadband oscillations in new energy power plants based on virtual split ratio according to claim 1, characterized in that, The specific criteria for determining stability based on the position of the eigenvalues ​​in the complex plane in step S7 are as follows: If the eigenvalues ​​are located in the left half of the complex plane and far from the imaginary axis, then the new energy power station is determined to be in a small-signal stable state. If the characteristic roots are located near the imaginary axis or in the right half of the complex plane, it is determined that the new energy power station has a risk of broadband oscillation and an early warning is issued.

5. The method for online early warning of broadband oscillations in new energy power plants based on virtual current split ratio according to claim 1, characterized in that, The virtual disturbance signal is a pulse wave or a binary sequence broadband signal; when a broadband signal is injected, the broadband disturbance current component is directly extracted from the response signal, without the need for the frequency sweeping step of changing the disturbance frequency in step S4.

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