A wind turbine generator frequency modulation method

Abstract

The application relates to a wind turbine frequency modulation method, and belongs to the technical field of wind power generation. The method comprises the following steps: obtaining a real-time operation condition of a wind turbine, and calculating maximum available frequency modulation energy of the wind turbine; dividing a whole frequency modulation process under power system power disturbance into time periods, and constructing a power system frequency response analysis model corresponding to each time period; calculating a corresponding relationship between a frequency minimum point and frequency modulation consumed energy of the whole frequency modulation process based on the power system frequency response analysis model; constructing an optimization model of frequency modulation control parameters, taking the maximum frequency minimum point as an objective function and taking the constraint condition that the frequency modulation consumed energy does not exceed the maximum available frequency modulation energy; solving the optimization model to obtain optimal wind turbine frequency modulation control parameters, and performing frequency modulation control on the wind turbine based on the frequency modulation control parameters. The wind turbine frequency modulation method can effectively improve the system frequency minimum point under power disturbance and optimize the wind power frequency modulation control effect.

Description

Technical Field

[0001] This application belongs to the field of wind power generation technology and relates to a frequency regulation method for wind turbine generators. Background Technology

[0002] As the penetration rate of new energy sources in the power system continues to increase, the equivalent inertia of the power grid and the frequency regulation capability of traditional synchronous generator units are significantly weakened, posing new challenges to system frequency stability. Wind power, as one of the most important forms of new energy, has a huge installed capacity, but its traditional operating mode is usually maximum power point tracking, acting only as a power source without actively responding to changes in grid frequency. This means that a large amount of wind power resources cannot provide effective frequency support when the system needs it. Therefore, designing effective and reliable wind power frequency regulation control strategies to increase appropriate frequency regulation power during power disturbances is of great significance for improving system frequency stability.

[0003] Currently, wind turbines participating in frequency regulation mostly employ integrated inertia control. However, due to the fixed control parameters, it is difficult to fully realize the frequency regulation potential of wind turbines. Therefore, there is an urgent need for a wind turbine frequency regulation method that can effectively raise the minimum system frequency under power disturbances and ensure grid frequency stability. Summary of the Invention

[0004] This application provides a wind turbine frequency regulation method. By constructing a frequency response analytical model in different time periods and constructing an optimization model to solve for the optimal frequency regulation control parameters, it achieves the technical effect of effectively improving the lowest system frequency under power disturbance and optimizing the wind power frequency regulation control effect. It solves the defects of the prior art, such as fixed wind power frequency regulation control parameters, insufficient frequency regulation potential, and poor frequency drop suppression effect.

[0005] This application provides a wind turbine frequency regulation method, comprising: acquiring the real-time operating conditions of the wind turbine and calculating the maximum available frequency regulation energy of the wind turbine; dividing the entire frequency regulation process under power system power disturbance into time periods and constructing an analytical model of the power system frequency response for each time period; based on the analytical model of the power system frequency response, calculating the correspondence between the minimum frequency point and the frequency regulation energy consumption during the entire frequency regulation process; constructing an optimization model of frequency regulation control parameters with maximizing the minimum frequency point as the objective function and the constraint that the frequency regulation energy consumption does not exceed the maximum available frequency regulation energy; solving the optimization model to obtain the optimal wind turbine frequency regulation control parameters, and performing frequency regulation control on the wind turbine based on the frequency regulation control parameters.

[0006] In the embodiments of this application, the method for dividing the entire frequency regulation process under power disturbance of the power system includes: setting a convergence threshold; calculating the lowest system frequency corresponding to each time period number from 1 to n based on the maximum available frequency regulation energy; calculating the absolute value of the difference between the lowest frequency corresponding to the time period number n and the lowest frequency corresponding to the time period number n-1; when the absolute value of the difference is greater than or equal to the convergence threshold, updating the time period number n to n+1, and iteratively executing the step of calculating the difference of the lowest frequency point and comparing the absolute value of the difference; when the absolute value of the difference is less than the convergence threshold, terminating the iteration, and determining the previous time period number n-1 corresponding to the time period number n at the time of termination of the iteration as the optimal time period number for the entire frequency regulation process.

[0007] In the embodiments of this application, the method for constructing the analytical model of the power system frequency response includes: constructing a time-domain rule for time-segmented switching based on the time-segmentation results of the entire frequency regulation process, wherein the time-domain rule includes the droop parameter corresponding to each time period and the switching time node of adjacent time periods; introducing an extended system frequency response model, and establishing a dynamic response differential relationship between the amplitude of the system active power disturbance and the frequency offset based on the extended system frequency response model; determining the frequency response expression corresponding to each time period of the entire frequency regulation process based on the dynamic response differential relationship; and constructing the analytical model of the power system frequency response based on the frequency response expression.

[0008] In the embodiments of this application, the frequency response expressions corresponding to each time period include the frequency response expression for the first time period and the frequency response expression for the i-th time period;

[0009] The frequency response expression for the first time period is: ; In the frequency response expression for the first time period: This represents the frequency offset at time t within the first time period; B The first intermediate value is expressed as: ; C The second intermediate value is expressed as: ; s 1 is the third intermediate value, and the expression for the third intermediate value is: ; s 2 is the fourth intermediate value, and the expression for the fourth intermediate value is: ; X The fifth intermediate value is expressed as follows: ; The frequency response expression for the i-th time period is: ; In the frequency response expression for the i-th time period: Let be the frequency offset at time t within the i-th time period; B i The sixth intermediate value is expressed as follows: ; C i The seventh intermediate value is expressed as follows: ; X i The eighth intermediate value is expressed as follows: ; m The ninth intermediate value is expressed as follows: ; In the expressions for the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth intermediate values, and the frequency response expressions for the first time period and the i-th time period: Δ P The active power disturbance amplitude, α For penetration rate, M It is the inertial constant. T R The reheater time constant is... D The damping coefficient is... R This is the adjustment coefficient. F H This refers to the power percentage of the high-pressure cylinder. e It is a natural constant. k p The droop coefficient is... For the first i The droop coefficient for the time period, For the first i- The droop coefficient for time period 1 t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch For the first i- Frequency offset at the exact moment the time period ends. t The continuous time in the time domain after the active power disturbance occurs.

[0010] In the embodiments of this application, the expression for the lowest frequency point during the entire frequency modulation process is: ; In the expression for the lowest frequency point during the entire frequency modulation process: This represents the lowest frequency point in the first time period; For the first i The lowest frequency point in a given time period; The tenth intermediate value is expressed as follows: ; The eleventh intermediate value is expressed as follows: ; In the expressions for the tenth intermediate value, the eleventh intermediate value, and the expression for the lowest frequency point during the entire frequency modulation process: B The first intermediate value, C This is the second intermediate value. B i The sixth intermediate value, C i The seventh intermediate value, X i The eighth intermediate value, m For the ninth intermediate value, Δ P The active power disturbance amplitude, α For penetration rate, T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first i The droop coefficient for the time period, For the first i- The droop coefficient for time period 1.

[0011] In the embodiments of this application, the expression for the frequency modulation energy consumed in the entire frequency modulation process is: ; In the expression for the frequency modulation energy consumed in the entire frequency modulation process: R 0 is the twelfth intermediate value, and the expression for the twelfth intermediate value is: ; R 1 is the thirteenth intermediate value, and the expression for the thirteenth intermediate value is: ; R 2 is the fourteenth intermediate value, and the expression for the fourteenth intermediate value is: ; The fifteenth intermediate value is expressed as follows: ; The sixteenth intermediate value is expressed as follows: ; In the expressions for the twelfth, thirteenth, fourteenth, and fifteenth intermediate values, and the expression for the frequency modulation energy consumed throughout the frequency modulation process: B The first intermediate value, C This is the second intermediate value. s1 is the third intermediate value. s 2 is the fourth intermediate value. X The fifth intermediate value, C i The seventh intermediate value, X i The eighth intermediate value, m For the ninth intermediate value, Δ P The active power disturbance amplitude, α For penetration rate, e It is a natural constant. T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first one The droop coefficient for the time period, For the first i The droop coefficient for the time period, For the first i- The droop coefficient for time period 1 t 1 represents the transition point between the first and second time periods. t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch t i For the first i Time period and the i+ The switching time point of time period 1.

[0012] In embodiments of this application, the method for constructing an optimization model of frequency modulation control parameters includes: Calculate the lowest frequency point for each time period Through expressions Determine the maximum frequency deviation value throughout the entire frequency modulation process. ; In expression The objective function for constructing the optimization model f ; In expression Construct the constraints for the optimization model; Where n is the number of time periods divided into the entire frequency modulation process. W 0 represents the maximum available frequency regulation energy of the wind turbine. W' This represents the total energy consumed during the entire frequency modulation process. Here is the droop coefficient for each time period. t i These are the switching points for each time period.

[0013] In the embodiments of this application, the method for calculating the maximum available frequency-regulating energy of the wind turbine includes: The preset mapping relationship between wind speed and fan rotor speed, and the preset minimum operating speed of the fan rotor; The real-time wind speed of the wind farm is obtained, and the real-time rotational speed of the wind turbine rotor is calculated based on the preset mapping relationship between wind speed and wind turbine rotor speed. The maximum available frequency regulation energy of the wind turbine is calculated based on the real-time rotational speed of the turbine rotor and the preset minimum operating speed.

[0014] In embodiments of this application, the method for calculating the maximum available frequency-regulating energy of the wind turbine further includes: The preset maximum operating speed of the fan rotor and the preset maximum power tracking zone cut-in wind speed are also specified. v Ⅰ Constant speed zone cut-in wind speed v Ⅱ and the cut-in wind speed in the constant power zone v Ⅲ ; Compare real-time wind speeds at wind farms v Cut-in wind speed with the maximum power tracking zone v Ⅰ Constant speed zone cut-in wind speed v Ⅱ and the cut-in wind speed in the constant power zone v Ⅲ Size between: when v Ⅰ ≤ v < v Ⅱ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v Ⅱ ≤ v < v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v ≥ v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; in, E This represents the maximum available frequency regulation energy of the wind turbine. λ opt The optimal tip speed ratio for wind turbine units. N This refers to the gearbox transmission ratio of the wind turbine unit. R Where is the blade radius of the wind turbine.J The total moment of inertia of the wind turbine rotor. ω min This is the minimum operating speed of the wind turbine rotor. ω max This is the maximum operating speed of the wind turbine rotor.

[0015] In the embodiments of this application, the method for solving the optimization model of the frequency regulation control parameters includes: using the frequency regulation control parameters of the wind turbine generator to be optimized as the position vector of the particles, using the maximum deviation of the power system frequency as the fitness value, and using the maximum available frequency regulation energy as the constraint condition, performing iterative optimization through a particle swarm optimization algorithm to search for the global optimal solution that satisfies the constraint condition; wherein, the frequency regulation control parameters of the wind turbine generator to be optimized include the number of time periods, the duration of each time period, and the droop coefficient of each time period; and outputting the optimal wind turbine generator frequency regulation control parameters corresponding to the global optimal solution.

[0016] The wind turbine frequency regulation method provided in this application has at least the following beneficial effects: 1. Effectively raises the lowest point of the system frequency after power disturbance, reduces the maximum frequency deviation, and avoids a secondary frequency drop when frequency regulation is withdrawn, thus significantly enhancing the frequency stability of the power system.

[0017] 2. Differentiated droop coefficients are used in different time periods to achieve optimal time-domain allocation of frequency regulation power, thereby maximizing the frequency regulation capability of the fan under the same frequency regulation energy consumption.

[0018] 3. The maximum available frequency regulation energy under different operating conditions is accurately calculated based on real-time wind speed and used as a rigid constraint to prevent the rotor speed from exceeding the limit and to ensure that the normal power generation operation of the wind turbine is not affected.

[0019] 4. Introduce a convergence threshold iterative method to determine the optimal number of time segments, balance the frequency modulation control effect with the complexity of engineering implementation, and avoid the drawbacks of too many or too few segments.

[0020] 5. By using the particle swarm optimization algorithm to globally optimize the model, the number of time periods, the time period switching time, and the droop coefficient of each time period can be accurately obtained. The parameters can be directly connected to the wind turbine control logic, making it highly practical for engineering implementation.

[0021] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, it can be implemented according to the contents of the specification. In order to make the above and other objects, features and advantages of this application more apparent, specific embodiments of this application are given below. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram illustrating the principle of the wind turbine frequency regulation method of this application; Figure 2 The equivalent circuit diagram of the two-region system containing wind power used for simulation verification; Figure 3 A comparison curve of the system frequency response characteristics under traditional integrated inertia control and the time-varying coefficient droop control of this application; Figure 4 A comparison curve of the frequency regulation output power of wind turbines under traditional integrated inertia control and time-division variable coefficient droop control as described in this application; Figure 5 A comparison curve of rotor speed variation of wind turbine under traditional integrated inertia control and time-varying coefficient droop control of this application; Figure 6 A comparison curve of frequency response results divided into 3 and 4 time periods; Figure 7 A comparison curve of frequency response results divided into 4 and 5 time periods. Detailed Implementation

[0024] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0025] The prefixes such as "first" and "second" used in this application embodiment are merely for distinguishing different descriptive objects and do not limit the position, order, priority, quantity, or content of the described objects. The use of ordinal numbers and other prefixes used to distinguish descriptive objects in this application embodiment does not constitute a limitation on the described objects. The description of the described objects is given in the claims or the context of the embodiments, and should not constitute unnecessary restrictions due to the use of such prefixes. Furthermore, in the description of this embodiment, unless otherwise stated, "multiple" means two or more.

[0026] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0027] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0028] As the penetration rate of new energy sources in the power system continues to increase, the equivalent inertia of the power grid and the frequency regulation capability of traditional synchronous generator units are significantly weakened, posing new challenges to system frequency stability. Wind power, as one of the most important forms of new energy, has a huge installed capacity, but its traditional operating mode is usually maximum power point tracking, acting only as a power source without actively responding to changes in grid frequency. This means that a large amount of wind power resources cannot provide effective frequency support when the system needs it. Therefore, designing effective and reliable wind power frequency regulation control strategies to increase appropriate frequency regulation power during power disturbances is of great significance for improving system frequency stability.

[0029] Currently, wind turbines participating in frequency regulation mostly adopt integrated inertia control. However, due to the fixed control parameters, it is difficult to fully realize the frequency regulation potential of wind turbines.

[0030] Therefore, as Figure 1 As shown, to address the shortcomings of existing technologies, this specific embodiment discloses a wind turbine frequency regulation method, applicable to new power systems with a high proportion of wind power integration. It aims to solve the problems of fixed wind power frequency regulation control parameters, insufficient frequency regulation potential, and inadequate frequency drop suppression under system power disturbances. The steps are as follows: Obtain the real-time operating conditions of the wind turbine and calculate the maximum available frequency regulation energy of the wind turbine. The entire frequency regulation process under power disturbance of the power system is divided into time periods, and analytical models of the power system frequency response corresponding to each time period are constructed. Based on the analytical model of the power system frequency response, the correspondence between the lowest frequency point and the energy consumed by frequency regulation during the entire frequency regulation process is calculated. An optimization model for frequency modulation control parameters is constructed with the objective function of maximizing the lowest frequency point and the constraint that the frequency modulation energy consumption does not exceed the maximum available frequency modulation energy. Solve the optimization model to obtain the optimal frequency regulation control parameters for the wind turbine, and then perform frequency regulation control on the wind turbine based on the obtained frequency regulation control parameters.

[0031] This method can accurately quantify the maximum available frequency regulation energy of wind turbines under real-time operating conditions. By constructing an accurate analytical model of the system frequency response through time-varying coefficient droop control, and with the goal of maximizing the minimum frequency point and the available frequency regulation energy as a constraint, an optimization model is constructed and the optimal control parameters are solved. Under the premise of ensuring the safe operation of wind turbines, the frequency regulation potential of wind power is fully explored, effectively raising the minimum system frequency point after power disturbance, reducing frequency deviation, and alleviating the problem of secondary frequency drop after frequency regulation is withdrawn. At the same time, it balances the frequency regulation effect with the complexity of engineering implementation, and significantly improves the frequency stability of high proportion of wind power connected to the power system.

[0032] The specific implementation methods for each step of the above-mentioned wind turbine frequency regulation method are as follows: In some embodiments, the method for obtaining the real-time operating conditions of a wind turbine and calculating the maximum available frequency regulation energy of the wind turbine includes: S11. Preset mapping relationship between wind speed and fan rotor speed, preset minimum operating speed of fan rotor. ω min Maximum operating speed ω max Simultaneously, preset the wind speed boundary points of the wind turbine operating range, including the cut-in wind speed for the maximum power tracking zone. v Ⅰ Constant speed zone cut-in wind speed v Ⅱ and the cut-in wind speed in the constant power zone v Ⅲ (i.e., rated wind speed).

[0033] S12. Obtain real-time wind speed at the wind farm v Based on a pre-defined mapping relationship between wind speed and fan rotor speed, the real-time speed of the fan rotor is calculated. ω r .

[0034] Depending on the wind speed, the rotational speed of the wind turbine can be divided into four operating stages, and the rotational speed characteristics of each stage are as follows: Start-up zone: When the real-time wind speed of the fan reaches the cut-in wind speed, but does not reach... v Ⅰ During this stage, the unit speed is constrained to the minimum operating speed. ω min The horizontal plane cannot provide frequency response support, and there is no available frequency modulation energy. Maximum power point tracking (MPPT) zone: when the wind speed meets the requirements. v Ⅰ ≤ v < v Ⅱ When the wind turbine enters the maximum power tracking (MPST) zone, the control system maintains a constant tip speed ratio by adjusting the rotor speed. The formula for calculating the rotor speed is: In the formula, ω r This is the actual mechanical speed of the rotor. λ opt The optimal tip speed ratio for wind turbines. N This refers to the gearbox transmission ratio of the wind turbine unit. v For real-time wind speed, R The radius of the wind turbine blade.

[0035] Constant speed zone: when the wind speed meets the requirements v Ⅱ ≤ v < v Ⅲ When the fan enters the constant speed zone, the rotor speed is calculated using the following formula: ; Constant power zone: when wind speed v ≥ v Ⅲ At this time, the fan enters the constant power region, and the speed remains constant. ω max .

[0036] S13. Based on the real-time rotational speed of the fan rotor and the preset minimum operating speed, calculate the maximum available frequency regulation energy of the fan. The specific calculation rules for each interval are as follows: when v Ⅰ ≤ v < v Ⅱ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v Ⅱ ≤ v < v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v ≥ v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; In the above formulas, E This represents the maximum available frequency regulation energy of the wind turbine. λ opt The optimal tip speed ratio for wind turbines. N This refers to the gearbox transmission ratio of the wind turbine unit. R Where is the blade radius of the wind turbine. J The total moment of inertia of the wind turbine rotor. ω min This is the minimum operating speed of the wind turbine rotor. ω max This refers to the maximum operating speed of the wind turbine rotor. ω 1 represents the rotor speed when the fan just enters the constant speed zone.

[0037] This step can accurately match the frequency regulation capability of the wind turbine under different wind speed conditions, quantify the maximum frequency regulation kinetic energy that can be released within the safe operating range of the wind turbine, and avoid the rotor speed from falling below the safe lower limit during the frequency regulation process, which would cause the unit to disconnect from the grid, thus providing a reliable safety constraint for subsequent frequency regulation control.

[0038] In some embodiments, the specific steps for dividing the entire frequency regulation process under power system disturbances into time periods and determining the optimal number of time periods are as follows: S21. A preset convergence threshold ε is used to balance the frequency modulation effect and control complexity; S22. Based on the calculated maximum available frequency modulation energy, calculate the lowest system frequency corresponding to each time period number from 1 to n. S23. Calculate the absolute value of the difference between the lowest frequency point corresponding to the nth time segment and the lowest frequency point corresponding to the n-1th time segment; and compare the obtained absolute value of the difference with the convergence threshold ε: When the absolute value of the difference is greater than or equal to the convergence threshold ε, the number of time segments n is updated to n+1, and the step of calculating the difference of the lowest frequency point and comparing the absolute value of the difference in step S23 is iteratively executed. When the absolute value of the difference is less than the convergence threshold, the iteration is terminated, and the previous time segment number n-1 corresponding to the time segment number n at the time of termination is determined as the optimal time segment number for the entire frequency modulation process.

[0039] To illustrate step S23: In this embodiment, after iterative calculation, there is a significant difference between the lowest frequency points under the control of three segments and four segments, and the absolute value of the difference is greater than the convergence threshold ε; while the difference between the lowest frequency points of four segments and five segments is small, and the absolute value of the difference is less than the convergence threshold ε. Therefore, the iteration is terminated, and the optimal number of time segments is determined to be 4.

[0040] This step, while ensuring the frequency modulation optimization effect, avoids excessive segmentation leading to redundant control logic and a surge in computational load, achieving the optimal balance between frequency modulation effect and engineering implementation complexity.

[0041] In some embodiments, the specific steps for constructing the analytical model of the power system frequency response for each time period based on the time period division results of the entire frequency regulation process are as follows: S31. Based on the time-segmentation results of the entire frequency modulation process, construct a time-segmented switching variable coefficient droop time-domain rule. The variable coefficient droop time-domain rule includes the droop parameter corresponding to each time segment, the switching time node of adjacent time segments, and the time-domain expression of the variable droop coefficient. k p ( t )for: In the formula: For the first i The droop coefficient for the time period t i For the first i Time period and the i+ The switching time point of time period 1.

[0042] S32. Introduce an extended system frequency response model, and based on the extended system frequency response model, establish a dynamic response differential relationship between the amplitude of the system active power disturbance and the frequency offset.

[0043] The extended system frequency response model introduced is a mature existing analysis model in the field of power system frequency stability analysis, widely used in scenarios involving the quantitative analysis of frequency dynamic characteristics of power systems with wind power. Based on the traditional synchronous machine system frequency response model, this model incorporates the influence of wind power penetration and wind droop control, accurately depicting the dynamic response relationship between frequency offset and disturbance amplitude, and unit frequency regulation parameters under active power disturbances, thus fully reconstructing the full-time-domain evolution of the system frequency.

[0044] The expression for the frequency response model is: In the formula: Δ P The active power disturbance amplitude, Δ f This is the frequency offset. M It is the inertial constant. D The damping coefficient is... R This is the adjustment coefficient. F H This refers to the power percentage of the high-pressure cylinder. T R The reheater time constant is... α This represents the wind power penetration rate.

[0045] Expanding and rearranging the above frequency response model expression, we obtain the second-order differential equation: Solving the characteristic equation yields the two roots of the equation. ,in, .

[0046] S33. Based on the above dynamic response differential relationship, determine the frequency response expressions for each time period of the entire frequency modulation process, including the frequency response expression for the first time period and the expression for the second time period. i The frequency response expression for a time period, where: The frequency response expression for the first time period is: ; In the frequency response expression for the first time period: This represents the frequency offset at time t within the first time period; B The first intermediate value is expressed as: ; C The second intermediate value is expressed as: ; s 1 is the third intermediate value, and the expression for the third intermediate value is: ; s 2 is the fourth intermediate value, and the expression for the fourth intermediate value is: ; X The fifth intermediate value is expressed as follows: ; The frequency response expression for the i-th time period is: ; In the frequency response expression for the i-th time period: Let be the frequency offset at time t within the i-th time period; B i The sixth intermediate value is expressed as follows: ; C i The seventh intermediate value is expressed as follows: ; X i The eighth intermediate value is expressed as follows: ; m The ninth intermediate value is expressed as follows: ; In the expressions for the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth intermediate values, and the frequency response expressions for the first and i-th time periods: Δ P The active power disturbance amplitude, α For penetration rate, M It is the inertial constant. TR The reheater time constant is... D The damping coefficient is... R This is the adjustment coefficient. F H This refers to the power percentage of the high-pressure cylinder. e It is a natural constant. k p The droop coefficient is... For the first i The droop coefficient for the time period, For the first i- The droop coefficient for time period 1 t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch For the first i- Frequency offset at the exact moment the time period ends. t The continuous time in the time domain after the active power disturbance occurs.

[0047] The derivation logic of the frequency response expression for the i-th time period is as follows: for the time domain expression of the frequency response in the interval [ t (i-1)- , t (i-1)+ By integrating, we obtain the relationship between the first derivatives of the frequencies before and after the time period switching. Combining this with the continuity condition that the frequencies are the same at the instant of the time period switching, we solve the problem simultaneously.

[0048] S34. Based on the above frequency response expression, construct an analytical model of the power system frequency response.

[0049] This step can accurately depict the dynamic evolution of system frequency under time-varying coefficient droop control, fully covering the frequency change characteristics of frequency modulation throughout the entire time period, providing an accurate mathematical basis for subsequent calculation of the lowest frequency point and frequency modulation energy, and ensuring the solution accuracy of the optimization model.

[0050] In some embodiments, based on the power system frequency response analytical model, the specific steps for calculating the correspondence between the lowest frequency point and the energy consumed during frequency regulation throughout the entire process are as follows: S41. Differentiate the frequency analytical expression for each time period to obtain the time corresponding to the lowest frequency point for each time period. Substitute the time into the frequency response expression for the corresponding time period to obtain the lowest frequency point for each time period. Thus, the expression for the lowest frequency point throughout the entire frequency modulation process is as follows: ; In the expression for the lowest frequency point during the entire frequency modulation process described above: This represents the lowest frequency point in the first time period; For the first i The lowest frequency point in a given time period; The tenth intermediate value is expressed as follows: ; The eleventh intermediate value is expressed as follows: ; In the expressions for the tenth and eleventh intermediate values, as well as the expression for the lowest frequency point during the entire frequency modulation process: B The first intermediate value mentioned above. C The second intermediate value mentioned above. B i The sixth intermediate value mentioned above, C i The seventh intermediate value mentioned above. X i The eighth intermediate value mentioned above, m For the ninth intermediate value mentioned above, Δ P The active power disturbance amplitude, α For penetration rate, T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first i The droop coefficient for the time period, For the first i- The droop coefficient for time period 1.

[0051] S42. By integrating the power increment under variable coefficient droop control in the time domain, the expression for the frequency modulation energy consumed throughout the frequency modulation process is obtained as follows: ; In the expression for the frequency modulation energy consumed in the entire frequency modulation process described above: R 0 is the twelfth intermediate value, and the expression for the twelfth intermediate value is: ; R 1 is the thirteenth intermediate value, and the expression for the thirteenth intermediate value is: ; R 2 is the fourteenth intermediate value, and the expression for the fourteenth intermediate value is: ; The fifteenth intermediate value is expressed as follows: ; The sixteenth intermediate value is expressed as follows: ; In the expressions for the twelfth, thirteenth, fourteenth, and fifteenth intermediate values, as well as the expression for the frequency modulation energy consumed throughout the entire frequency modulation process: B The first intermediate value mentioned above. CThe second intermediate value mentioned above. s 1 is the third intermediate value mentioned above. s 2 is the fourth intermediate value mentioned above. X The fifth intermediate value mentioned above, C i The seventh intermediate value mentioned above. X i The eighth intermediate value mentioned above, m For the ninth intermediate value mentioned above, Δ P The active power disturbance amplitude, α For penetration rate, e It is a natural constant. T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first one The droop coefficient for the time period, For the first i The droop coefficient for the time period For the first i- The droop coefficient for time period 1 t 1 represents the transition point between the first and second time periods. t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch t i For the first i Time period and the i+ The switching time point of time period 1.

[0052] This step can accurately quantify the frequency modulation effect and energy consumption under different combinations of control parameters, establish the correspondence between control parameters, frequency modulation effect and energy consumption, and provide core input for the construction of subsequent optimization models.

[0053] In some embodiments, the specific steps for constructing an optimization model for frequency modulation control parameters with the objective function of maximizing the lowest frequency point and the constraint that the frequency modulation energy consumption does not exceed the maximum available frequency modulation energy are as follows: S51. Calculate the lowest frequency point for each time period. Through expressions Determine the maximum frequency deviation value throughout the entire frequency modulation process. ; In expression Objective function for constructing the optimization model f In the formula, fThe minimum value of the maximum frequency deviation under variable coefficient droop control is equivalent to maximizing the minimum frequency of the system. In expression Construct the constraints for the optimization model; Where n is the number of time periods divided into the entire frequency modulation process. W 0 represents the maximum available frequency regulation energy of the wind turbine. W' This represents the total energy consumed during the entire frequency modulation process. Here is the droop coefficient for each time period. t i These are the switching points for each time period.

[0054] This step, with the safe operation of the wind turbine as a prerequisite, transforms the frequency regulation parameter tuning into a constrained nonlinear optimization problem. Under the constraint of fixed frequency regulation energy, it achieves the global optimum of frequency regulation effect, fully tapping the potential of wind power frequency regulation.

[0055] In some embodiments, the specific steps for solving the optimization model to obtain the optimal frequency regulation control parameters of the wind turbine, and for performing frequency regulation control on the wind turbine based on the frequency regulation control parameters, are as follows: S61. The frequency regulation control parameters of the wind turbine to be optimized are used as the position vector of the particles. The maximum deviation of the power system frequency is used as the fitness value and the maximum available frequency regulation energy is used as the constraint. The particle swarm optimization algorithm is used to iteratively search for the global optimal solution that satisfies the constraint. The frequency regulation control parameters of the wind turbine to be optimized include the number of time periods, the duration of each time period, and the droop coefficient of each time period.

[0056] The specific computational flow of the particle swarm optimization algorithm is as follows: S611. Algorithm Parameter Initialization: Set Population Size N Maximum number of iterations M max Learning factor c 1. c 2. Maximum value of inertia weight w max and minimum value w min The droop coefficient and segmented time of each time period to be optimized are used as the position of the particle, and the maximum frequency deviation is used as the fitness value. Within the range that meets the constraints, the particle is randomly generated. N The initial position of each particle x i and initial velocity v i ; S612. Initial optimal value setting: Set the initial position of each particle to its current individual historical optimal position. pbest iCalculate the fitness value of all initial particles, and select the position of the particle with the smallest fitness value as the initial global historical best position. gbest Set the current iteration number t =1; S613. Individual Optimal Update: Compare the current fitness values ​​of particles. F ( x i ( t )) and its individual historical best value F ( pbest i ),like F ( x i ( t ))< F ( pbest i If so, then update. pbest i = x i ( t ); S614. Global Optimal Update: Find the optimal solution for the individual with the smallest fitness value in the current population, denoted as... gbest c ,Compare F ( gbest c ) and global historical best value F ( gbest ),like F ( gbest c )< F ( gbest If so, then update. gbest = gbest c ; S615. Inertia Weight and Particle State Update: Inertia weight is updated using a linear decreasing strategy. w The formula is and according to and Update the velocity and position of each particle; where: r 1, r 2 is a random number distributed in [0,1]. S616. Iteration Termination Judgment: Determine if the current iteration count has reached the maximum iteration count; if so, terminate the calculation and output the global optimal position. gbest This is the final optimized combination of control parameters; if it is not achieved, then let... t=t+ 1. Return to step S613 for the next iteration.

[0057] S62. Output the optimal wind turbine frequency regulation control parameters corresponding to the global optimal solution, and inject the optimal number of time periods, duration of each time period, and optimal droop coefficient of each time period into the control logic of the wind turbine converter. When the system experiences active power disturbance, execute time-sharing variable coefficient droop control to provide frequency support for the power grid.

[0058] It should be noted that the switching time points of each time period and the duration of each time period are time-domain parameters that correspond one-to-one and can be linearly converted to each other. The two together determine the time period division results of the entire frequency modulation process, and their core correspondence is as follows: Time domain reference setting: The time zero point of the frequency modulation time domain is set at the moment when the system active power disturbance occurs. t 0=0, with the preset total duration of the entire frequency modulation process as... T Let n be the optimal number of time periods for the entire frequency modulation process. Then there are n consecutive frequency modulation time periods and n-1 time period switching points. Switching time point definition: The switching time point for each time period is an absolute time node within the frequency modulation time domain, denoted as t 1. t 2、…、 t n-1 ,in t i Let i be the switching time point between the i-th time period and the (i+1)-th time period. All switching time points satisfy the timing constraint: 0 = t 0< t 1< t 2<…< t n-1 < t n = T ; Duration definition and conversion relationship: The duration of each time period is the time interval between two adjacent time points, denoted as Δ. T 1. Δ T 2、…、Δ T n Δ, where the duration of the i-th time period is T i = t i -t i-1 That is, the duration of the i-th time period is the time difference between the start node and the end node of that time period.

[0059] Based on the above correspondence, after determining the switching time points of each time period, the duration of each time period can be uniquely calculated; conversely, after determining the duration of each time period, the switching time points of each time period can also be uniquely determined by time-series accumulation. In the process of solving the optimization model of this application, either one of the two can be used as the optimization decision variable, or both can be included in the decision variable system. The above correspondence ensures the consistency and uniqueness of the parameters.

[0060] S63. To verify the effectiveness of this method, such as Figure 2 As shown, a simulation verification is performed using a two-area system with wind power as an example. The system and equipment parameters are as follows: Synchronous generator unit parameters: Rated capacity S G =100MW, rated voltage U N1 =13.8kV, inertial constant M =7, damping coefficient D =2, adjustment coefficient R =0.05, power percentage of high-pressure cylinder F H =0.28, reheater time constant T R =10; Fan parameters: Rated power S W =1.5MW, rated voltage U N2 =0.575kV, rated wind speed v N =12m / s, cut-in wind speed v min =3.5m / s, cutoff wind speed v max =25m / s, blade radius R =37m, maximum wind energy utilization coefficient C pmax =0.4382, wind turbine inertial time constant H w =4s.

[0061] Simulation operating condition settings: System active load P L The capacity is 97MW, and the per-unit rotor speed of the wind turbine during normal operation is 1.2 pu. t A load step Δ is applied at 40s. P =5MW, the duration of wind turbine participation in frequency regulation is T =30s, total simulation time is 100s. The parameters of the particle swarm optimization algorithm are set as follows: population size is 600, maximum number of iterations is 30, learning factors are 1.5 and 1 respectively, and the maximum and minimum values ​​of inertia weight are 0.9 and 0.4 respectively.

[0062] The proposed variable coefficient droop control is compared with traditional integrated inertia control. Given the frequency modulation parameters for integrated inertia control, the following parameters are provided. k d =15、 k p=20, taking the frequency modulation energy consumed under integrated inertia control as the energy constraint of this method, the optimal number of time periods is obtained by particle swarm optimization, which is 4. The optimal frequency modulation control parameters for each time period are: droop coefficient of the first time period k 1 p =40.0972, the time point for switching between the first and second time periods. t 1 = 4.0021, the droop coefficient for the second time period k 2 p =28.4071, the switching point between the second and third time periods. t 2 = 9.4473, the droop coefficient for the third time period k 3 p =18.6501, the time point for switching between the third time period and the third time period. t 3 = 15.8371, the droop coefficient for the third time period k 4 p =11.7331.

[0063] Table 1 shows the maximum deviation of the system frequency at different time periods after the disturbance occurs under the two control strategies: Table 1

[0064] Note: The values ​​in the table represent the maximum deviation of the system frequency from the rated frequency, in Hz. The smaller the value, the smaller the frequency drop and the higher the lowest point of the system frequency.

[0065] Comparison of system frequency response characteristics: such as Figure 3 As shown, the table presents a comparison curve of the system frequency response under traditional integrated inertia control and the variable coefficient droop control of this application. Combined with the data in Table 1, it can be seen that the variable coefficient droop control strategy provided by this application can effectively reduce the maximum frequency drop deviation after system power disturbance and significantly raise the system's minimum frequency point. Simultaneously, at the moment of frequency modulation exit, because the droop coefficient is smaller in the final stage of this strategy, the step change in output power caused by frequency modulation exit is smaller, effectively suppressing the problem of secondary frequency drop after frequency modulation exit. Compared with traditional fixed parameter control, it has a better frequency support effect.

[0066] Comparison of FM output power characteristics: such as Figure 4 As shown, the curves compare the frequency regulation output power of wind turbines under two control strategies. It can be seen that in the initial stage of frequency regulation, the variable coefficient droop control in this application uses a larger droop coefficient, which can quickly increase the frequency regulation output power, providing strong support for the system frequency and effectively suppressing rapid frequency drops. As the frequency regulation process progresses, the droop coefficient gradually decreases, and the frequency regulation output power gradually decreases. The power decrease process in the frequency regulation exit stage is more gradual, avoiding secondary frequency fluctuations caused by sudden power drops, and achieving optimal allocation of frequency regulation power across the entire time domain.

[0067] Comparison of fan rotor speed characteristics: such as Figure 5 As shown, the curves compare the changes in wind turbine rotor speed under two control strategies. It can be seen that under the variable coefficient droop control of this application, the rate of decrease in wind turbine rotor speed gradually slows down as the frequency regulation process progresses, matching the gradual decrease of the droop coefficient and preventing excessively rapid drop in rotor speed. At the end of the frequency regulation process, the wind turbine rotor speeds under both control strategies are consistent, verifying that the total energy consumed by both strategies is exactly the same throughout the frequency regulation process. This demonstrates that under the same frequency regulation energy constraints, this application achieves a superior frequency regulation support effect, fully tapping the frequency regulation potential of wind turbine units.

[0068] Verification of the reasonableness of the number of time periods: such as Figure 6 As shown, this is a comparison of the frequency response results of three-segment and four-segment variable coefficient droop control. It can be seen that there is a significant difference in the minimum frequency points of the two systems; increasing the number of segments can effectively improve the level of the system's minimum frequency point. Figure 7 As shown, this is a comparison of the frequency response results of four-segment and five-segment variable coefficient droop control. It can be seen that the frequency response curves of the two basically overlap, and the difference in the lowest frequency point is minimal, indicating that further increasing the number of segments has little effect on improving the frequency modulation effect. This application introduces a convergence threshold ε to optimize the number of time segments, effectively controlling the complexity of the control strategy while ensuring the frequency modulation effect, thus verifying the rationality of the time segment optimization method provided in this application.

[0069] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be covered. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for frequency regulation of a wind turbine generator set, characterized in that, include: Obtain the real-time operating conditions of the wind turbine and calculate the maximum available frequency regulation energy of the wind turbine. The entire frequency regulation process under power disturbance of the power system is divided into time periods, and analytical models of the power system frequency response corresponding to each time period are constructed. Based on the analytical model of the power system frequency response, the correspondence between the lowest frequency point and the energy consumed by frequency regulation during the entire frequency regulation process is calculated. An optimization model for frequency modulation control parameters is constructed with the objective function of maximizing the lowest frequency point and the constraint that the frequency modulation energy consumption does not exceed the maximum available frequency modulation energy. Solve the optimization model to obtain the optimal frequency regulation control parameters for the wind turbine, and perform frequency regulation control on the wind turbine based on the frequency regulation control parameters.

2. The wind turbine frequency regulation method according to claim 1, characterized in that, The method for dividing the entire frequency regulation process under power disturbances in the power system includes: Preset convergence threshold; Based on the maximum available frequency modulation energy, calculate the lowest system frequency corresponding to each time period number from 1 to n. Calculate the absolute value of the difference between the lowest frequency point corresponding to the nth time period and the lowest frequency point corresponding to the n-1th time period. When the absolute value of the difference is greater than or equal to the convergence threshold, the number of time periods n is updated to n+1, and the steps of calculating the difference of the lowest frequency point and comparing the absolute value of the difference are iteratively executed. When the absolute value of the difference is less than the convergence threshold, the iteration is terminated, and the previous time segment number n-1 corresponding to the time segment number n at the time of termination is determined as the optimal time segment number for the entire frequency modulation process.

3. The wind turbine frequency regulation method according to claim 1, characterized in that, The method for constructing the analytical model of the power system frequency response includes: Based on the time period division results of the entire frequency modulation process, a variable coefficient droop time domain rule for time period switching is constructed. The variable coefficient droop time domain rule includes the droop parameter corresponding to each time period and the switching time node of adjacent time periods. An extended system frequency response model is introduced, and based on the extended system frequency response model, a dynamic response differential relationship between the amplitude of the system active power disturbance and the frequency offset is established. Based on the dynamic response differential relationship, the frequency response expression corresponding to each time period of the entire frequency modulation process is determined; Based on the frequency response expression, construct the analytical model of the power system frequency response.

4. The wind turbine frequency regulation method according to claim 3, characterized in that, The frequency response expressions corresponding to each time period include the frequency response expression for the first time period and the frequency response expression for the i-th time period. The frequency response expression for the first time period is: ; In the frequency response expression for the first time period: This represents the frequency offset at time t within the first time period; B The first intermediate value is expressed as: ; C The second intermediate value is expressed as: ; s 1 is the third intermediate value, and the expression for the third intermediate value is: ; s 2 is the fourth intermediate value, and the expression for the fourth intermediate value is: ; X The fifth intermediate value is expressed as follows: ; The frequency response expression for the i-th time period is: ； In the frequency response expression for the i-th time period: Let be the frequency offset at time t within the i-th time period; B i The sixth intermediate value is expressed as follows: ; C i The seventh intermediate value is expressed as follows: ; X i The eighth intermediate value is expressed as follows: ; m The ninth intermediate value is expressed as follows: ; In the expressions for the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth intermediate values, and the frequency response expressions for the first time period and the i-th time period: Δ P The active power disturbance amplitude, α For penetration rate, M It is the inertial constant. T R The reheater time constant is... D The damping coefficient is... R This is the adjustment coefficient. F H This refers to the power percentage of the high-pressure cylinder. e It is a natural constant. k p The droop coefficient is... For the first i The droop coefficient for the time period For the first i- The droop coefficient for time period 1 t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch For the first i- Frequency offset at the exact moment the time period ends. t The continuous time in the time domain after the active power disturbance occurs.

5. The wind turbine frequency regulation method according to claim 4, characterized in that, The expression for the lowest frequency point during the entire frequency modulation process is: ； In the expression for the lowest frequency point during the entire frequency modulation process: This represents the lowest frequency point in the first time period; For the first i The lowest frequency point in a given time period; The tenth intermediate value is expressed as follows: ; The eleventh intermediate value is expressed as follows: ; In the expressions for the tenth intermediate value, the eleventh intermediate value, and the expression for the lowest frequency point during the entire frequency modulation process: B The first intermediate value, C This is the second intermediate value. B i The sixth intermediate value, C i The seventh intermediate value, X i The eighth intermediate value, m For the ninth intermediate value, Δ P The active power disturbance amplitude, α For penetration rate, T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first i The droop coefficient for the time period For the first i- The droop coefficient for time period 1.

6. The wind turbine frequency regulation method according to claim 5, characterized in that, The expression for the frequency modulation energy consumed in the entire frequency modulation process is: ； In the expression for the frequency modulation energy consumed in the entire frequency modulation process: R 0 is the twelfth intermediate value, and the expression for the twelfth intermediate value is: ; R 1 is the thirteenth intermediate value, and the expression for the thirteenth intermediate value is: ; R 2 is the fourteenth intermediate value, and the expression for the fourteenth intermediate value is: ; The fifteenth intermediate value is expressed as follows: ; The sixteenth intermediate value is expressed as follows: ; In the expressions for the twelfth, thirteenth, fourteenth, and fifteenth intermediate values, and the expression for the frequency modulation energy consumed throughout the frequency modulation process: B The first intermediate value, C This is the second intermediate value. s 1 is the third intermediate value. s 2 is the fourth intermediate value. X The fifth intermediate value, C i The seventh intermediate value, X i The eighth intermediate value, m For the ninth intermediate value, Δ P The active power disturbance amplitude, α For penetration rate, e It is a natural constant. T R The reheater time constant is... For the first i- Frequency offset at the exact moment the time period ends. M It is the inertial constant. For the first one The droop coefficient for the time period For the first i The droop coefficient for the time period For the first i- The droop coefficient for time period 1 t 1 represents the transition point between the first and second time periods. t i 1 is the first i- Time period 1 and the first i The time point for the time period to switch t i For the first i Time period and the i+ The switching time point of time period 1.

7. The wind turbine frequency regulation method according to claim 6, characterized in that, The method for constructing an optimization model of frequency modulation control parameters includes: Calculate the lowest frequency point for each time period Through expressions Determine the maximum frequency deviation value throughout the entire frequency modulation process. ; In expression The objective function for constructing the optimization model f ; In expression Construct the constraints for the optimization model; Where n is the number of time periods divided into the entire frequency modulation process. W 0 represents the maximum available frequency regulation energy of the wind turbine. W' This represents the total energy consumed during the entire frequency modulation process. Here is the droop coefficient for each time period. t i These are the switching points for each time period.

8. The wind turbine frequency regulation method according to claim 1, characterized in that, The method for calculating the maximum available frequency-modulated energy of a wind turbine includes: The preset mapping relationship between wind speed and fan rotor speed, and the preset minimum operating speed of the fan rotor; The real-time wind speed of the wind farm is obtained, and the real-time rotational speed of the wind turbine rotor is calculated based on the preset mapping relationship between wind speed and wind turbine rotor speed. The maximum available frequency regulation energy of the wind turbine is calculated based on the real-time rotational speed of the turbine rotor and the preset minimum operating speed.

9. The wind turbine frequency regulation method according to claim 8, characterized in that, The method for calculating the maximum available frequency-regulating energy of wind turbine generators also includes: The preset maximum operating speed of the fan rotor and the preset maximum power tracking zone cut-in wind speed are also specified. v Ⅰ Constant speed zone cut-in wind speed v Ⅱ and the cut-in wind speed in the constant power zone v Ⅲ ; Compare real-time wind speeds at wind farms v Cut-in wind speed with the maximum power tracking zone v Ⅰ Constant speed zone cut-in wind speed v Ⅱ and the cut-in wind speed in the constant power zone v Ⅲ Size between: when v Ⅰ ≤ v < v Ⅱ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v Ⅱ ≤ v < v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; when v ≥ v Ⅲ At that time, the formula for calculating the maximum available frequency-regulating energy of a wind turbine is: ; in, E This represents the maximum available frequency regulation energy of the wind turbine. λ opt The optimal tip speed ratio for wind turbine units. N This refers to the gearbox transmission ratio of the wind turbine unit. R Where is the blade radius of the wind turbine. J The total moment of inertia of the wind turbine rotor. ω min This is the minimum operating speed of the wind turbine rotor. ω max This is the maximum operating speed of the wind turbine rotor.

10. The wind turbine frequency regulation method according to any one of claims 1-9, characterized in that, The methods for solving the optimization model of the frequency modulation control parameters include: The frequency regulation control parameters of the wind turbine to be optimized are used as the position vector of the particles. The maximum deviation of the power system frequency is used as the fitness value. The maximum available frequency regulation energy is used as the constraint. The particle swarm optimization algorithm is used to iteratively search for the global optimal solution that satisfies the constraint. The frequency regulation control parameters of the wind turbine to be optimized include the number of time periods, the duration of each time period, and the droop coefficient of each time period. Output the optimal frequency control parameters of the wind turbine corresponding to the global optimal solution.

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