A method for suppressing time-varying subsynchronous oscillations in a doubly-fed wind farm based on adaptive wave limiting

Abstract

The present invention belongs to the technical field of subsynchronous oscillation suppression in wind farms, and specifically designs a method for suppressing time-varying subsynchronous oscillations in a doubly-fed wind farm based on adaptive wave limiting. It includes system modeling and analysis, collecting DFIG and power grid parameters, establishing a state space model and converting it into a dq coordinate system; using the RLS algorithm to monitor and analyze the DFIG state in real time, identifying the subsynchronous frequency component; determining the oscillation intensity and range based on the filter output, and formulating a strategy; adjusting the inverter reference current and torque command to suppress the oscillation; stability analysis, and verifying the effectiveness through small disturbance stability analysis and time domain simulation. By adopting data acquisition technology, intelligent algorithms and optimized control strategies, accurate monitoring of subsynchronous frequency components is achieved, an adaptive wave limiting strategy is formulated to control subsynchronous oscillations, and the effectiveness of the control strategy is verified through a comprehensive stability analysis, thereby improving the operating stability and efficiency of the wind farm.

Description

Technical Field

[0001] The present invention belongs to the technical field of subsynchronous oscillation suppression in wind farms, and specifically designs a method for suppressing time-varying subsynchronous oscillation in a doubly-fed wind farm based on adaptive wave limiting. Background Art

[0002] The control strategies in the prior art have defects in dealing with the time-varying characteristics of DFIG and power grid systems. Most control strategies are built based on pre-set fixed parameters and models. Taking the control strategy based on a fixed model as an example, when the operating state of the system changes, such as a sudden increase or decrease in load, and fluctuations in the grid voltage, the electromagnetic characteristics and operating parameters of the DFIG will change accordingly. However, the fixed control strategy cannot adjust its own parameters and control logic in real time according to these changes. For example, when the load increases, the DFIG requires a larger torque to maintain a stable speed, and the characteristics of the subsynchronous oscillation may also change. However, the fixed control strategy cannot adapt to such changes, and cannot effectively adjust the reference current and torque instructions of the inverter to suppress subsynchronous oscillations, thereby affecting the stable operation of the system.

[0003] Incompleteness of the control effect evaluation of the existing technology: The existing technology has the problem of incompleteness in evaluating the suppression effect of the control strategy on subsynchronous oscillation. On the one hand, some evaluation methods only focus on the change of the amplitude of subsynchronous oscillation. For example, the suppression effect is judged by comparing the simple difference of the amplitude of subsynchronous oscillation before and after the implementation of the control strategy. However, the frequency change of subsynchronous oscillation is equally important. The change of frequency may affect the resonance characteristics of the system and the interaction with other equipment. If only the amplitude is considered and the frequency is ignored, the effectiveness of the control strategy may be wrongly evaluated. On the other hand, the existing technology often does not fully consider the stability of the system under different working conditions during the evaluation. The system will face a variety of working conditions in actual operation, such as power grid faults (single-phase short circuit, two-phase short circuit, three-phase short circuit, etc.), DFIG operation under different wind speed conditions, etc. The control strategy must not only effectively suppress subsynchronous oscillation under normal conditions, but also ensure that the system remains stable under various fault conditions. The evaluation of the existing technology in this regard is not comprehensive enough, and it is impossible to accurately judge the actual effect of the control strategy under different working conditions.

[0004] To this end, we propose a method for suppressing time-varying subsynchronous oscillations in a doubly-fed wind farm based on adaptive wave limiting. Summary of the invention

[0005] In view of the deficiencies in the above-mentioned prior art, the purpose of the present invention is to solve the problems existing in the above-mentioned prior art by adopting data acquisition technology, intelligent algorithm and optimized control strategy, to achieve accurate monitoring of subsynchronous frequency components, to formulate an adaptive wave limiting strategy to control subsynchronous oscillations, and to verify the effectiveness of the control strategy through comprehensive stability analysis, so as to improve the operating stability and efficiency of the wind farm.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solutions:

[0007] The method for suppressing time-varying subsynchronous oscillation of a doubly-fed wind farm based on adaptive wave limiting comprises the following steps:

[0008] S1. System modeling and analysis: establish the state space model of DFIG and power grid, and analyze the fault and subsynchronous oscillation (SSR) mechanism;

[0009] S2. Adaptive filter design, design an adaptive filter to monitor and analyze the DFIG status in real time and identify subsynchronous frequency components;

[0010] S3. Formulate a limiting strategy, based on the output of the adaptive filter, formulate a limiting strategy to control subsynchronous oscillations;

[0011] S4. Control strategy implementation, based on the wave limiting strategy formulated in S3, suppresses subsynchronous oscillation by adjusting the reference current and torque command of the inverter;

[0012] S5. Stability analysis, based on the DFIG and power grid responses after the implementation of the control strategy, the effectiveness of the control strategy is verified through small disturbance stability analysis and time domain simulation.

[0013] Furthermore, the S1 includes:

[0014] S11. Collecting parameters of DFIG and power grid, including electrical parameters, mechanical parameters, and topological structure and impedance of the power grid;

[0015] S12. Based on the collected parameters, the state space model of DFIG and the power grid is established. When establishing the model, the electromagnetic characteristics, mechanical characteristics of DFIG and the interaction with the power grid need to be considered to accurately describe the dynamic characteristics of DFIG and the power grid; the state space model is:

[0016] ;

[0017] in, is the state variable vector; Represents the state variable vector Derivative with respect to time; , are the d and q axis components of the stator current, , are the d-axis and q-axis components of the rotor current, is the rotor speed; is the input variable vector, , are the d-axis and q-axis components of the grid voltage; is the output variable vector, which is defined as needed, including stator current, rotor current, power, etc.; , , , is the coefficient matrix, which is determined by the parameters of DFIG and power grid;

[0018] S13. The state space model of DFIG and power grid is converted into a two-phase dq coordinate system by using Park transformation, so that the model can be analyzed and controlled in the rotating coordinate system. In the dq coordinate system, variables such as voltage and current are expressed as a combination of DC and AC quantities, which is convenient for controlling and analyzing the model. The formula of Park transformation is:

[0019] ;

[0020] in, , is the variable in the dq coordinate system, , for Variables in the coordinate system, is the Park transform angle, which is related to the rotor position or speed;

[0021] In the dq coordinate system, the stator voltage equation is expressed as:

[0022] ;

[0023] In the dq coordinate system, the rotor voltage equation is:

[0024] ;

[0025] In the dq coordinate system, the stator current is:

[0026] ;

[0027] In the dq coordinate system, the rotor current is:

[0028] ;

[0029] in, , is the component of the stator voltage in the dq coordinate system; is the stator resistance, is the stator inductance; is the slip rate; is the electrical angular velocity; is the flux generated by the rotor flux in the stator winding; , is the stator current component in the dq coordinate system; , for Stator current components in the coordinate system; is the angle of Park transformation; , is the component of the rotor voltage in the dq coordinate system; is the rotor resistance, is the rotor inductance; , is the rotor current component in the dq coordinate system; , They are Rotor current components in the coordinate system;

[0030] S14. Obtain the fault types that cause subsynchronous oscillation (SSR) under different operating conditions based on the results of model analysis;

[0031] The model is analyzed for various operating conditions, including different load levels, grid voltage changes, generator output adjustments, etc., and the system response under these conditions is observed, especially the voltage and current fluctuations; then, these fluctuations are analyzed to see whether they show the characteristics of subsynchronous oscillations, such as oscillations of specific frequencies, phase relationships, etc.; based on the analysis results, the type of fault that causes the SSR is determined, which includes but is not limited to: grid short-circuit faults, such as single-phase short circuits, two-phase short circuits, or three-phase short circuits; line switching operations, opening and closing of circuit breakers; component failures in the power system, such as transformer failures, capacitor failures, etc.; sudden changes in load, such as starting or stopping of large motors.

[0032] Further, the S2 includes:

[0033] S21. Select the recursive least squares (RLS) adaptive filter algorithm. The RLS algorithm can quickly track the changes of signals and is suitable for tracking subsynchronous frequency components in DFIG and power grid systems because it can adjust the weight of the filter in time according to the changes of the signal, thereby accurately identifying the subsynchronous frequency components;

[0034] S22. Determine the parameters of the filter, which include the filter order, step size, etc. According to the characteristics of the DFIG and the power grid, select the appropriate filter order and step size to ensure that the filter can quickly and accurately track the changes of the subsynchronous frequency components;

[0035] S23. Real-time collection of DFIG current, voltage and other signals as filter input;

[0036] S24. The weight of the filter is continuously updated through the RLS algorithm to adapt to the change of the signal. At each sampling moment, the weight update amount of the filter is calculated according to the input signal and the expected output;

[0037] S25. Perform spectrum analysis on the output signal of the filter to extract information such as the amplitude and phase of the sub-synchronous frequency component, providing a basis for the subsequent formulation of the limiting wave strategy.

[0038] Furthermore, the filter order selection method is as follows: if the sub-synchronous frequency components are mainly concentrated in a lower frequency range, a lower order filter is selected; if there is more high-frequency interference in the system, a higher order filter needs to be selected to suppress the interference.

[0039] Furthermore, the filter step size selection method is: if the power grid system changes dynamically quickly, a larger forgetting factor is selected to improve the convergence speed; if the power grid system has a high stability requirement, a smaller forgetting factor is selected to improve the tracking performance.

[0040] Further, in S24, the method for adjusting the filter weight includes:

[0041] S241. According to the current input signal and the filter weights at the previous moment , calculate the predicted output ;

[0042] S242. Calculation error ,in is the expected output;

[0043] S243. According to the error and input signal , calculate the gain vector , and update the filter weights ;

[0044] in:

[0045] ;

[0046] ;

[0047] ;

[0048] In the formula, is the inverse correlation matrix; For the forgetting factor; is the identity matrix; For input signal The transpose of For input signal The inverse correlation matrix of the previous moment.

[0049] Further, the S3 includes:

[0050] S31. Analyze the sub-synchronous frequency component information output by the adaptive filter, determine the intensity and frequency range of the sub-synchronous oscillation, and calculate the intensity index of the sub-synchronous oscillation by analyzing the amplitude and phase information of the sub-synchronous frequency component output by the filter; Amplitude M It is expressed as: ,in a and b are the real and imaginary parts of the subsynchronous frequency components, respectively, and the frequency range is determined by spectrum analysis;

[0051] S32. Evaluate the severity of subsynchronous oscillation based on the amplitude and phase information of the subsynchronous frequency component; set the threshold , when the amplitude When , it is considered that the subsynchronous oscillation is more serious;

[0052] S33. According to the severity of the subsynchronous oscillation, formulate a corresponding wave limiting strategy and set a threshold to limit the amplitude of the subsynchronous current or voltage. or voltage When the threshold is exceeded, corresponding control measures are taken; expressed as: or When adjusting the inverter parameters or changing the DFIG control mode, represents the subsynchronous current threshold, Indicates the subsynchronous voltage threshold.

[0053] Further, the S4 includes:

[0054] S41. Based on the wave limiting strategy formulated in S3, determine the adjustment method of the reference current and torque command of the inverter, and calculate the adjustment amount of the reference current and torque command according to the intensity and frequency of the sub-synchronous oscillation;

[0055] The adjustment amount of the reference current is calculated according to the following formula:

[0056] ;

[0057] in, is the reference current adjustment amount; is the current adjustment factor; is the subsynchronous current amplitude; is the set limit amplitude;

[0058] The adjustment amount of the torque command is calculated according to the following formula:

[0059] ;

[0060] in, is the torque command adjustment amount; is the subsynchronous current amplitude; is the subsynchronous phase; , and is a coefficient determined according to the characteristics of DFIG and power grid;

[0061] S42. The calculated reference current adjustment value is transmitted through the communication interface And torque command adjustment Transmitted to the inverter to adjust the reference current and torque command;

[0062] S43. During the adjustment process, the current, voltage, speed and other operating data of the DFIG are monitored in real time, and these operating data are transmitted to the control system for analysis, and the operating data satisfies the relevant equations of the DFIG in the dq coordinate system, including the stator voltage equation and the rotor voltage equation;

[0063] S44. According to the change of DFIG state, adjust the reference current and torque command accordingly;

[0064] The reference current adjustment is updated as: ;

[0065] The torque command adjustment amount is updated as: ;

[0066] In the formula, is the reference current adjustment amount; is the torque command adjustment amount; is the updated reference current adjustment amount; is the updated torque command adjustment amount; is the coefficient related to the speed adjustment; is the change in DFIG speed; It is the torque coefficient related to the speed adjustment, which reflects the influence of DFIG speed change on the torque command adjustment amount.

[0067] Further, the S5 includes:

[0068] S51. Characteristic root calculation and stability judgment: Calculate the characteristic root of the model based on the state space model established in S1, and judge the stability of the system under small disturbances according to the distribution of the characteristic root;

[0069] Among them, the characteristic roots are obtained by solving the characteristic equation: Get, where is the characteristic root, is the identity matrix; is the coefficient matrix, which is established based on the dynamic model of DFIG and power grid;

[0070] S52. The stability of DFIG and power grid under small disturbances is determined based on the real part of the characteristic root. If for all characteristic roots , all have the real part of the characteristic root , it means that DFIG and power grid are stable under small disturbances; on the contrary, if the real part of the characteristic root is greater than or equal to 0, the system is unstable;

[0071] S53. Time domain simulation and effect evaluation, simulate the operation of DFIG and power grid under different working conditions, and set corresponding working conditions; calculate the attenuation rate of subsynchronous oscillation amplitude and frequency The rate of change of is used to estimate the control strategy’s suppression effect on subsynchronous oscillations;

[0072] The decay rate of the subsynchronous oscillation amplitude: ;

[0073] Frequency of subsynchronous oscillation amplitude: ;

[0074] The amplitude of the previous synchronous oscillation for the implementation of the control strategy; The amplitude of the next synchronous oscillation after the implementation of the control strategy; The frequency of the previous synchronous oscillation for the control strategy implementation; The frequency of the next synchronous oscillation after the control strategy is implemented;

[0075] S54. Verification and optimization of control strategy: verify the effectiveness of the control strategy based on the results of stability analysis and time domain simulation, and further optimize and improve the control strategy based on the verification results;

[0076] Verify validity:

[0077] The effectiveness of the control strategy is verified based on the results of small disturbance stability analysis and time domain simulation. If the system is stable in the small disturbance stability analysis, and the decay rate of the subsynchronous oscillation amplitude and the rate of change of the frequency in the time domain simulation meet the predetermined requirements, the control strategy is considered to be effective;

[0078] If the control strategy does not meet the effectiveness requirements, the control strategy needs to be further optimized and improved;

[0079] Optimization and Improvement:

[0080] The optimized control strategy is verified again to ensure that the system can remain stable under various operating conditions. It is necessary to repeatedly perform small disturbance stability analysis and time domain simulation, and continuously adjust the relevant parameters in the control strategy until the system meets the requirements of stability and suppression effect.

[0081] In summary, due to the adoption of the above technical solution, the beneficial technical effects of the invention are:

[0082] 1. Accurately monitor subsynchronous frequency components:

[0083] Advantages of adaptive filter: By adopting the recursive least squares (RLS) adaptive filter algorithm, it can track the changes of signals in real time. Unlike traditional fixed filters, it can adjust the weight of the filter in time according to the real-time status of the DFIG and power grid system. When the system is affected by factors such as wind speed changes and power grid failures, and the sub-synchronous frequency component is offset, the adaptive filter can accurately identify the amplitude and phase of the sub-synchronous frequency component, providing an accurate basis for the subsequent control strategy formulation.

[0084] The overall impact of improving monitoring accuracy: Accurate monitoring makes the understanding of subsynchronous oscillations more comprehensive and precise, which helps to formulate more targeted control measures, thereby improving the ability of the entire system to suppress subsynchronous oscillations.

[0085] 2. Adaptive control strategy:

[0086] Adjust instructions according to system changes: formulate a wave limiting strategy based on the output of the adaptive filter, and adjust the reference current and torque instructions of the inverter accordingly. When the system operating state changes, such as load changes or grid voltage fluctuations, the appropriate reference current and torque instruction adjustment can be calculated in real time. When the load increases, by adjusting the reference current and torque instructions, the DFIG can adapt to the new load requirements and effectively suppress subsynchronous oscillations. This adaptive capability ensures that the system can maintain stable operation under various working conditions and improves the reliability and adaptability of the system.

[0087] Adaptability to different working conditions: Whether it is normal operating conditions or facing complex working conditions such as power grid failure (single-phase short circuit, two-phase short circuit, three-phase short circuit, etc.), different wind speed conditions, etc., this technical solution can maintain the stability of the system by dynamically adjusting the control strategy. Compared with the existing fixed parameter control strategy, it can better cope with complex and changeable situations in actual operation and reduce the impact of subsynchronous oscillation on the system.

[0088] 3. Comprehensive control effect evaluation:

[0089] Comprehensive consideration of amplitude and frequency changes: When evaluating the control strategy's suppression effect on subsynchronous oscillations, not only the attenuation rate of the oscillation amplitude is considered, but also the rate of change of the frequency is calculated. Through the comprehensive analysis of these two key indicators, a more comprehensive understanding of the effectiveness of the control strategy can be achieved. If only the amplitude change is focused on, the impact of the frequency change on the system's resonance characteristics may be ignored. By considering both the amplitude and the frequency at the same time, this technical solution can more accurately determine whether the control strategy has truly and effectively suppressed subsynchronous oscillations.

[0090] Stability assessment under different working conditions: Through small disturbance stability analysis and time domain simulation, the stability of the system under various working conditions is evaluated. Ensure that the control strategy can keep the system stable under different working conditions, including power grid failures, load changes, etc. This comprehensive stability assessment makes the technical solution more reliable and can meet the needs of actual engineering applications, avoiding instability of the system under certain working conditions due to improper control strategies.

[0091] In summary, this technical solution effectively solves the shortcomings of existing technologies in suppressing subsynchronous oscillations through advanced data acquisition technology, intelligent algorithms and optimized control strategies, and improves the operating stability and efficiency of wind farms. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Figure 1 It is a flow chart of a method for suppressing time-varying subsynchronous oscillations in a doubly-fed wind farm based on adaptive wave limiting;

[0093] Figure 2 A flow chart of the method for analyzing faults and subsynchronous oscillation (SSR) mechanisms;

[0094] Figure 3 A flow chart of a method for identifying subsynchronous frequency components;

[0095] Figure 4 A flow chart of a method for adjusting filter weights;

[0096] Figure 5 A flow chart of the method for developing a wave-limiting strategy to control subsynchronous oscillations;

[0097] Figure 6 A flow chart of a method for adjusting the reference current and torque command of the inverter to suppress subsynchronous oscillation;

[0098] Figure 7 Flowchart of the method for verifying the effectiveness of the control strategy through small disturbance stability analysis and time domain simulation. DETAILED DESCRIPTION

[0099] In order to make the purpose, technical solution and advantages of the invention more clear, the invention is further described in detail below in combination with the embodiments. It should be understood that the specific embodiments described here are only used to explain the invention and are not used to limit the invention.

[0100] like Figure 1 As shown, the method for suppressing time-varying subsynchronous oscillation of a doubly-fed wind farm based on adaptive wave limiting includes the following steps:

[0101] S1. System modeling and analysis: establish the state space model of DFIG and power grid, and analyze the fault and subsynchronous oscillation (SSR) mechanism;

[0102] S2. Adaptive filter design, design an adaptive filter to monitor and analyze the DFIG status in real time and identify subsynchronous frequency components;

[0103] S3. Formulate a limiting strategy, based on the output of the adaptive filter, formulate a limiting strategy to control subsynchronous oscillations;

[0104] S4. Control strategy implementation, based on the wave limiting strategy formulated in S3, suppresses subsynchronous oscillation by adjusting the reference current and torque command of the inverter;

[0105] S5. Stability analysis, based on the DFIG and power grid responses after the implementation of the control strategy, the effectiveness of the control strategy is verified through small disturbance stability analysis and time domain simulation.

[0106] like Figure 2 As shown, in S1, analyzing the fault and subsynchronous oscillation (SSR) mechanism includes:

[0107] S11. Collect the parameters of DFIG and power grid, including electrical parameters (such as resistance, inductance, capacitance, etc.), mechanical parameters (such as moment of inertia, friction coefficient, etc.), and topological structure and impedance of the power grid;

[0108] S12. Based on the collected parameters, a state space model of DFIG and the power grid is established. When establishing the model, the electromagnetic characteristics, mechanical characteristics of DFIG and the interaction with the power grid need to be considered to accurately describe the dynamic characteristics of DFIG and the power grid; the state space model is:

[0109] ;

[0110] in, is the state variable vector; Represents the state variable vector Derivative with respect to time; , are the d and q axis components of the stator current, , are the d-axis and q-axis components of the rotor current, is the rotor speed; is the input variable vector, , are the d-axis and q-axis components of the grid voltage; is the output variable vector, which is defined as needed, including stator current, rotor current, power, etc.; , , , is the coefficient matrix, which is determined by the parameters of DFIG and power grid;

[0111] S13. The state space model of DFIG and power grid is converted into a two-phase dq coordinate system by using Park transformation, so that the model can be analyzed and controlled in the rotating coordinate system. In the dq coordinate system, variables such as voltage and current are expressed as a combination of DC and AC quantities, which is convenient for controlling and analyzing the model. The formula of Park transformation is:

[0112] ;

[0113] in, , is the variable in the dq coordinate system, , for Variables in the coordinate system, is the Park transform angle, which is related to the rotor position or speed;

[0114] In the dq coordinate system, the stator voltage equation is expressed as:

[0115] ;

[0116] In the dq coordinate system, the rotor voltage equation is:

[0117] ;

[0118] In the dq coordinate system, the stator current is:

[0119] ;

[0120] In the dq coordinate system, the rotor current is:

[0121] ;

[0122] in, , is the component of the stator voltage in the dq coordinate system; is the stator resistance, is the stator inductance; is the slip rate; is the electrical angular velocity; is the flux generated by the rotor flux in the stator winding; , is the stator current component in the dq coordinate system; , for Stator current components in the coordinate system; is the angle of Park transformation; , is the component of the rotor voltage in the dq coordinate system; is the rotor resistance, is the rotor inductance; , is the rotor current component in the dq coordinate system; , They are Rotor current components in the coordinate system;

[0123] S14. Obtain the fault types that cause subsynchronous oscillation (SSR) under different operating conditions based on the results of model analysis;

[0124] By analyzing the model under various operating conditions, including different load levels, grid voltage changes, generator output adjustments, etc., the system response under these conditions is observed, especially the fluctuations in voltage and current; then, it is analyzed whether these fluctuations show the characteristics of subsynchronous oscillations, such as oscillations of specific frequencies, phase relationships, etc.; based on the analysis results, the type of fault that caused the SSR is determined. Possible fault types include but are not limited to: grid short-circuit faults, such as single-phase short circuits, two-phase short circuits, or three-phase short circuits; line switching operations, opening and closing of circuit breakers; component failures in the power system, such as transformer failures, capacitor failures, etc.; sudden changes in load, such as starting or stopping of large motors.

[0125] like Figure 3 As shown, in S2, identifying the secondary synchronization frequency component includes:

[0126] S21. Select the recursive least squares (RLS) adaptive filter algorithm. The RLS algorithm can quickly track the changes of signals and is suitable for tracking subsynchronous frequency components in DFIG and power grid systems because it can adjust the weight of the filter in time according to the changes of signals, thereby accurately identifying subsynchronous frequency components.

[0127] S22. Determine the parameters of the filter, which include the filter order, step size, etc. According to the characteristics of the DFIG and the power grid, select the appropriate filter order and step size to ensure that the filter can quickly and accurately track the changes of the subsynchronous frequency components;

[0128] Analyze the frequency characteristics of DFIG and power grid, determine the approximate range of subsynchronous frequency components, and select the appropriate filter order according to the frequency response characteristics of the system to ensure that the filter can effectively filter out the interference of other frequency components and accurately track the changes of subsynchronous frequency components; the filter order selection method is as follows: if the subsynchronous frequency components are mainly concentrated in the lower frequency range, select a lower order filter; if there are more high-frequency interferences in the system, a higher order filter needs to be selected to suppress the interference;

[0129] The step size of the RLS algorithm is controlled by the forgetting factor. The choice of the forgetting factor will affect the convergence speed and tracking performance of the algorithm. The larger the forgetting factor, the faster the algorithm forgets historical data, the faster the convergence speed, but the tracking performance may decrease; the smaller the forgetting factor, the stronger the algorithm's memory of historical data, the better the tracking performance, but the convergence speed may slow down; Among them, the selection method of the filter step size: if the dynamic changes of the power grid system are fast, choose a larger forgetting factor to increase the convergence speed; if the stability requirements of the power grid system are high, choose a smaller forgetting factor to improve the tracking performance;

[0130] S23. Real-time collection of DFIG current, voltage and other signals as filter input;

[0131] S24. The weight of the filter is continuously updated through the RLS algorithm to adapt to the change of the signal. At each sampling moment, the weight update amount of the filter is calculated according to the input signal and the expected output;

[0132] S25. Perform spectrum analysis on the output signal of the filter to extract information such as the amplitude and phase of the sub-synchronous frequency component, providing a basis for the subsequent formulation of the limiting wave strategy.

[0133] like Figure 4 As shown, in S24, the method for adjusting the filter weight includes:

[0134] S241. According to the current input signal and the filter weights at the previous moment , calculate the predicted output ;

[0135] S242. Calculation error ,in is the expected output;

[0136] S243. According to the error and input signal , calculate the gain vector , and update the filter weights ;

[0137] in:

[0138] ;

[0139] ;

[0140] ;

[0141] In the formula, is the inverse correlation matrix; For the forgetting factor; is the identity matrix; For input signal The transpose of For input signal The inverse correlation matrix of the previous moment.

[0142] By continuously adjusting the weight of the filter, it can accurately identify the changes in the subsynchronous frequency component; at the same time, according to the changes in the DFIG state, such as speed, load, etc., the parameters of the filter are adjusted to improve the performance of the filter; if the speed of the DFIG changes, it will cause the frequency of the subsynchronous frequency component to shift. At this time, the center frequency or bandwidth of the filter is adjusted accordingly to ensure that the filter can accurately track the changes in the subsynchronous frequency component.

[0143] like Figure 5 As shown, in S3, formulating a wave limiting strategy to control sub-synchronous oscillations includes:

[0144] S31. Analyze the sub-synchronous frequency component information output by the adaptive filter, determine the intensity and frequency range of the sub-synchronous oscillation, and calculate the intensity index of the sub-synchronous oscillation by analyzing the amplitude and phase information of the sub-synchronous frequency component output by the filter; Amplitude M It is expressed as: ,in a and b are the real and imaginary parts of the subsynchronous frequency components, respectively, and the frequency range is determined by spectrum analysis;

[0145] S32. Evaluate the severity of subsynchronous oscillation based on the amplitude and phase information of the subsynchronous frequency component; set the threshold , when the amplitude When , it is considered that the subsynchronous oscillation is more serious;

[0146] S33. According to the severity of the subsynchronous oscillation, formulate a corresponding wave limiting strategy and set a threshold to limit the amplitude of the subsynchronous current or voltage. or voltage When the threshold is exceeded, corresponding control measures are taken; expressed as: or When adjusting the inverter parameters or changing the DFIG control mode, represents the subsynchronous current threshold, Indicates the subsynchronous voltage threshold.

[0147] like Figure 6 As shown, in S4, adjusting the reference current and torque command of the inverter to suppress sub-synchronous oscillation includes:

[0148] S41. Based on the wave limiting strategy formulated in S3, determine the adjustment method of the reference current and torque command of the inverter, and calculate the adjustment amount of the reference current and torque command according to the intensity and frequency of the sub-synchronous oscillation;

[0149] The adjustment amount of the reference current is calculated according to the following formula:

[0150] ;

[0151] in, is the reference current adjustment amount; is the current adjustment factor; is the subsynchronous current amplitude; is the set limit amplitude;

[0152] The adjustment amount of the torque command is calculated according to the following formula:

[0153] ;

[0154] in, is the torque command adjustment amount; is the subsynchronous current amplitude; is the subsynchronous phase; , and is a coefficient determined according to the characteristics of DFIG and power grid;

[0155] S42. The calculated reference current adjustment value is transmitted through the communication interface And torque command adjustment Transmitted to the inverter to adjust the reference current and torque command;

[0156] S43. During the adjustment process, the current, voltage, speed and other operating data of the DFIG are monitored in real time, and these operating data are transmitted to the control system for analysis, and the operating data satisfies the relevant equations of the DFIG in the dq coordinate system, including the stator voltage equation and the rotor voltage equation;

[0157] S44. According to the change of DFIG state, adjust the reference current and torque command accordingly;

[0158] in:

[0159] The reference current adjustment is updated as: ;

[0160] The torque command adjustment amount is updated as: ;

[0161] In the formula, is the reference current adjustment amount; is the torque command adjustment amount; is the updated reference current adjustment amount; is the updated torque command adjustment amount; It is a coefficient related to the speed adjustment, which reflects the influence of the DFIG speed change on the reference current adjustment; is the change in DFIG speed; It is the torque coefficient related to the speed adjustment. It reflects the influence of DFIG speed change on the torque command adjustment.

[0162] like Figure 7 As shown, in S5, the effectiveness of the control strategy is verified by small disturbance stability analysis and time domain simulation, including:

[0163] S51. Characteristic root calculation and stability judgment: Calculate the characteristic root of the model based on the state space model established in S1, and judge the stability of the system under small disturbances according to the distribution of the characteristic root;

[0164] Among them, the characteristic roots are obtained by solving the characteristic equation: Get, where is the characteristic root, is the identity matrix; is the coefficient matrix, It is built based on the dynamic model of DFIG and power grid;

[0165] S52. The stability of DFIG and power grid under small disturbances is determined based on the real part of the characteristic root. If for all characteristic roots , all have the real part of the characteristic root , it means that DFIG and power grid are stable under small disturbances; on the contrary, if the real part of the characteristic root is greater than or equal to 0, the system is unstable;

[0166] S53. Time domain simulation and effect evaluation, simulate the operation of DFIG and power grid under different working conditions, and set corresponding working conditions; calculate the attenuation rate of subsynchronous oscillation amplitude and frequency The rate of change of is used to estimate the control strategy’s suppression effect on subsynchronous oscillations;

[0167] The decay rate of the subsynchronous oscillation amplitude: ;

[0168] Frequency of subsynchronous oscillation amplitude: ;

[0169] The amplitude of the previous synchronous oscillation for the implementation of the control strategy; The amplitude of the next synchronous oscillation after the implementation of the control strategy; The frequency of the previous synchronous oscillation for the control strategy implementation; The frequency of the next synchronous oscillation after the control strategy is implemented;

[0170] If the subsynchronous oscillation amplitude decay rate The value of is large (for example, close to ), indicating that the control strategy has a good suppressive effect on the subsynchronous oscillation amplitude, that is, the amplitude of the subsynchronous oscillation is greatly reduced after the control strategy is implemented;

[0171] If the subsynchronous oscillation amplitude decay rate The value of is small (for example, close to ), it means that the control strategy has no obvious effect on the suppression of subsynchronous oscillation amplitude, and the subsynchronous oscillation amplitude has no significant change after the implementation of the control strategy;

[0172] If the subsynchronous oscillation amplitude frequency is large (for example, the absolute value is close to ), indicating that the control strategy has a significant effect on the subsynchronous oscillation frequency, that is, the subsynchronous oscillation frequency has changed significantly after the control strategy is implemented;

[0173] If the subsynchronous oscillation amplitude frequency The value of is small (for example, close to ), it means that the control strategy has little effect on the subsynchronous oscillation frequency, and the subsynchronous oscillation frequency remains basically unchanged after the control strategy is implemented;

[0174] S54. Verification and optimization of control strategy: verify the effectiveness of the control strategy based on the results of stability analysis and time domain simulation, and further optimize and improve the control strategy based on the verification results;

[0175] Verify validity:

[0176] The effectiveness of the control strategy is verified based on the results of small disturbance stability analysis and time domain simulation. If the system is stable in the small disturbance stability analysis (i.e., the real parts of all characteristic roots are less than 0), and the decay rate of the subsynchronous oscillation amplitude and the rate of change of the frequency in the time domain simulation meet the predetermined requirements (e.g., Reach a certain percentage, Within a certain range), the control strategy is considered to be effective;

[0177] If the control strategy does not meet the effectiveness requirements, the control strategy needs to be further optimized and improved;

[0178] Verify the optimized strategy again:

[0179] The optimized control strategy is verified again to ensure that the system can remain stable under various operating conditions. It is necessary to repeatedly perform small disturbance stability analysis and time domain simulation, and continuously adjust the relevant parameters in the control strategy (such as the current adjustment coefficient mentioned in S4). , , and etc.) until the system meets the requirements of stability and suppression effect.

[0180] The above description is a preferred embodiment of the invention and is not intended to limit the invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the invention should be included in the protection scope of the invention.

Claims

1. A method for suppressing time-varying subsynchronous oscillations in a doubly-fed wind farm based on adaptive wave limiting, characterized in that: The following steps are involved: S1. System modeling and analysis: establish the state space model of DFIG and power grid, and analyze the fault and subsynchronous oscillation mechanism; S2. Adaptive filter design, design an adaptive filter to monitor and analyze the DFIG status in real time and identify subsynchronous frequency components; S3. Formulate a limiting strategy, based on the output of the adaptive filter, formulate a limiting strategy to control subsynchronous oscillations; S4. Control strategy implementation, based on the wave limiting strategy formulated in S3, suppresses subsynchronous oscillation by adjusting the reference current and torque command of the inverter; S5. Stability analysis, based on the DFIG and power grid responses after the control strategy is implemented, the effectiveness of the control strategy is verified through small disturbance stability analysis and time domain simulation; The S2 includes: S21. Select the recursive least squares adaptive filter algorithm. The RLS algorithm can quickly track the changes of signals and is suitable for tracking subsynchronous frequency components in DFIG and power grid systems. S22. Determine the parameters of the filter, the parameters of the filter include the filter order and step size, and select the filter order and step size according to the characteristics of the DFIG and the power grid to ensure that the filter can quickly and accurately track the changes of the subsynchronous frequency components; S23. Real-time acquisition of DFIG current and voltage signals as filter input; S24. The weight of the filter is continuously updated through the RLS algorithm to adapt to the change of the signal. At each sampling moment, the weight update amount of the filter is calculated according to the input signal and the expected output; S25. Perform spectrum analysis on the output signal of the filter to extract the amplitude and phase information of the subsynchronous frequency component to provide a basis for the subsequent wave limiting strategy formulation; In S24, the method for adjusting the filter weight includes: S241. According to the current input signal and the filter weights at the previous moment , calculate the predicted output ; S242. Calculation error ,in is the expected output; S243. According to the error and input signal , calculate the gain vector , and update the filter weights ; in: ； ； ； In the formula, is the inverse correlation matrix; For the forgetting factor; is the identity matrix; For input signal The transpose of For input signal The inverse correlation matrix of the previous moment; The S3 includes: S31. Analyze the sub-synchronous frequency component information output by the adaptive filter, determine the intensity and frequency range of the sub-synchronous oscillation, and calculate the intensity index of the sub-synchronous oscillation by analyzing the amplitude and phase information of the sub-synchronous frequency component output by the filter; the amplitude M is expressed as: , where a and b are the real and imaginary parts of the subsynchronous frequency component, respectively, and the frequency range is determined by spectrum analysis; S32. Evaluate the severity of subsynchronous oscillation based on the amplitude and phase information of the subsynchronous frequency component; set the threshold , when the amplitude When , it is considered that the subsynchronous oscillation is more serious; S33. According to the severity of the subsynchronous oscillation, formulate a corresponding wave limiting strategy and set a threshold to limit the amplitude of the subsynchronous current or voltage. or voltage When the threshold is exceeded, corresponding control measures are taken; expressed as: when or When adjusting the inverter parameters or changing the DFIG control mode, represents the subsynchronous current threshold, represents the sub-synchronous voltage threshold; The S4 includes: S41. Based on the wave limiting strategy formulated in S3, determine the adjustment method of the reference current and torque command of the inverter, and calculate the adjustment amount of the reference current and torque command according to the intensity and frequency of the sub-synchronous oscillation; The adjustment amount of the reference current is calculated according to the following formula: ； in, is the reference current adjustment amount; is the current adjustment factor; is the subsynchronous current amplitude; is the set limit amplitude; The adjustment amount of the torque command is calculated according to the following formula: ； in, is the torque command adjustment amount; is the subsynchronous current amplitude; is the subsynchronous phase; , and is a coefficient determined according to the characteristics of DFIG and power grid; S42. The calculated reference current adjustment value is transmitted through the communication interface And torque command adjustment Transmitted to the inverter to adjust the reference current and torque command; S43. During the adjustment process, the current, voltage, and speed operation data of the DFIG are monitored in real time, and these operation data are transmitted to the control system for analysis, and the operation data satisfies the relevant equations of the DFIG in the dq coordinate system, including the stator voltage equation and the rotor voltage equation; S44. According to the change of DFIG state, adjust the reference current and torque command accordingly; The reference current adjustment is updated as: ; The torque command adjustment amount is updated as: ; In the formula, is the reference current adjustment amount; is the torque command adjustment amount; is the updated reference current adjustment amount; is the updated torque command adjustment amount; is the coefficient related to the speed adjustment; is the change in DFIG speed; is the torque coefficient related to speed regulation; The S5 includes: S51. Calculation of characteristic roots and judgment of stability. The characteristic roots of the model are calculated based on the state space model established in S1. The stability of the system under small disturbances is judged according to the distribution of the characteristic roots. The characteristic roots are obtained by solving the characteristic equation: Get, where is the characteristic root, is the identity matrix; is the coefficient matrix; S52. The stability of DFIG and power grid under small disturbances is determined based on the real part of the characteristic root. If for all characteristic roots , all have the real part of the characteristic root , it means that DFIG and power grid are stable under small disturbances; on the contrary, if the real part of the characteristic root is greater than or equal to 0, the system is unstable; S53. Time domain simulation and effect evaluation, simulate the operation of DFIG and power grid under different working conditions, and set corresponding working conditions; calculate the attenuation rate of subsynchronous oscillation amplitude and frequency The rate of change of is used to estimate the control strategy’s suppression effect on subsynchronous oscillations; The decay rate of the subsynchronous oscillation amplitude: ; Frequency of subsynchronous oscillation amplitude: ; The amplitude of the previous synchronous oscillation for the implementation of the control strategy; The amplitude of the next synchronous oscillation after the implementation of the control strategy; The frequency of the previous synchronous oscillation for the control strategy implementation; The frequency of the next synchronous oscillation after the control strategy is implemented; S54. Verification and optimization of control strategy: verify the effectiveness of the control strategy based on the results of stability analysis and time domain simulation, and further optimize and improve the control strategy based on the verification results; Verify validity: The effectiveness of the control strategy is verified based on the results of small disturbance stability analysis and time domain simulation. If the system is stable in the small disturbance stability analysis and the decay rate of the subsynchronous oscillation amplitude and the rate of change of the frequency in the time domain simulation meet the predetermined requirements, the control strategy is considered to be effective. If the control strategy does not meet the effectiveness requirements, the control strategy needs to be further optimized and improved; Optimization and Improvement: The optimized control strategy is verified again to ensure that the system can remain stable under various operating conditions. It is necessary to repeatedly perform small disturbance stability analysis and time domain simulation, and continuously adjust the relevant parameters in the control strategy until the system meets the requirements of stability and suppression effect.

2. The method for suppressing time-varying subsynchronous oscillation of a doubly-fed wind farm based on adaptive wave limiting according to claim 1 is characterized in that: S1 includes: S11. Collecting parameters of the DFIG and the power grid, including electrical parameters, mechanical parameters, and topological structure and impedance information of the power grid; S12. Based on the collected parameters, the state space model of DFIG and power grid is established. When establishing the model, the electromagnetic characteristics, mechanical characteristics of DFIG and the interaction with the power grid need to be considered to accurately describe the dynamic characteristics of DFIG and power grid. The state space model is: ； in, is the state variable vector; Represents the state variable vector Derivative with respect to time; , are the d and q axis components of the stator current, , are the d-axis and q-axis components of the rotor current, is the rotor speed; is the input variable vector, , are the d-axis and q-axis components of the grid voltage; is the output variable vector, including stator current, rotor current, and power; , , , is the coefficient matrix, which is determined by the parameters of DFIG and power grid; S13. The state space model of DFIG and power grid is converted into a two-phase dq coordinate system by applying Park transformation, so that the model can be analyzed and controlled in a rotating coordinate system. In the dq coordinate system, the voltage and current variables are expressed as a combination of DC and AC quantities. The formula of Park transformation is: ； in, , is the variable in the dq coordinate system; , for Variables in coordinate system; is the Park transform angle, which is related to the rotor position or speed; In the dq coordinate system, the stator voltage equation is expressed as: ； In the dq coordinate system, the rotor voltage equation is: ； In the dq coordinate system, the stator current is: ； In the dq coordinate system, the rotor current is: ； in, , is the component of the stator voltage in the dq coordinate system; is the stator resistance, is the stator inductance; is the slip rate; is the electrical angular velocity; is the flux generated by the rotor flux in the stator winding; , is the stator current component in the dq coordinate system; , for Stator current components in the coordinate system; is the angle of Park transformation; , is the component of the rotor voltage in the dq coordinate system; is the rotor resistance, is the rotor inductance; , is the rotor current component in the dq coordinate system; , They are Rotor current components in the coordinate system; S14. Obtaining the fault types that cause subsynchronous oscillations under different operating conditions based on the results of the model analysis; The model is analyzed for various operating conditions, including different load levels, grid voltage changes, generator output adjustments, and the system response under these conditions is observed, as well as the voltage and current fluctuations. Then, these fluctuations are analyzed to see if they exhibit the characteristics of subsynchronous oscillations. Based on the analysis results, the type of fault that causes the SSR is determined, including but not limited to: grid short-circuit faults, line switching operations, opening and closing of circuit breakers, component failures in the power system, and sudden changes in load.

3. The method for suppressing time-varying subsynchronous oscillation of a doubly-fed wind farm based on adaptive wave limiting according to claim 1 is characterized in that: In S22, the filter order selection method is: If the subsynchronous frequency components are mainly concentrated in the lower frequency range, select a lower-order filter; if there are more high-frequency interferences in the system, a higher-order filter is required to suppress the interference.

4. The method for suppressing time-varying subsynchronous oscillation of a doubly-fed wind farm based on adaptive wave limiting according to claim 3 is characterized in that: In S22, the filter step size is selected by: If the power grid system changes dynamically quickly, a larger forgetting factor is selected to increase the convergence speed; if the power grid system has high stability requirements, a smaller forgetting factor is selected to improve the tracking performance.

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