Wind turbine generator frequency support control method and device based on comprehensive gain coefficient

Abstract

The invention relates to the technical field of variable-speed wind turbine generator control, and discloses a wind turbine generator frequency support control method and device based on a comprehensive gain coefficient, and the method comprises the steps: S1, frequency support: designing at least one frequency support control mode, and designing an inertia response coefficient in the frequency support control mode; s2, rotating speed recovery: at least designing a rotating speed recovery strategy, and designing a rotating speed recovery coefficient based on fuzzy logic in the rotating speed recovery strategy; and S3, designing a comprehensive gain coefficient according to the inertia response coefficient and the rotating speed recovery coefficient, redefining a rotating speed tracking error based on the comprehensive gain coefficient, and generating a generator torque instruction by adopting a PI control mode based on the rotating speed tracking error. The rotor kinetic energy is fully utilized to provide frequency support, meanwhile, the risk that the wind turbine generator is unstable due to excessive speed reduction is avoided, the frequency supporting capacity of the wind turbine generator is fully excavated, and frequency secondary drop is effectively avoided while the lowest point of the frequency is remarkably increased.

Description

Technical Field

[0001] The present application belongs to the technical field of variable-speed wind turbine control, and in particular relates to a method and device for controlling frequency support of a wind turbine based on a comprehensive gain coefficient. Background Art

[0002] As the scale of large-scale wind farms connected to the grid continues to expand, the proportion of synchronous generators in the grid is gradually decreasing. The inherent intermittent and uncertain nature of wind power poses a serious challenge to grid frequency stability. To maintain frequency stability in grids with high wind power penetration, modern large-scale wind farms urgently need to provide fast frequency response ancillary services.

[0003] To enable wind farms to have frequency support capabilities, existing methods mainly introduce additional power control loops into the wind turbine control system that use the grid frequency deviation and its derivative as input signals. This allows the wind turbine to provide short-term power support by adjusting the rotor kinetic energy when the grid frequency fluctuates, in order to quickly stabilize the grid frequency. However, this additional control strategy will weaken the frequency support capability of the unit. To solve this problem, researchers proposed an optimized power point tracking control strategy. By adjusting the MPPT operating curve of the wind turbine according to the real-time grid frequency deviation, the active power output of the unit is adjusted. However, this method does not fully consider the speed operating status of the unit, and the frequency support potential is not fully utilized.

[0004] Furthermore, during the frequency support phase, the utilization of rotor kinetic energy causes the wind turbine speed to deviate from the optimal speed corresponding to the MPPT mode. To ensure the economic benefits of the wind farm and the stable operation of the wind turbines, speed recovery control is necessary. However, while the traditional speed recovery method of directly switching to MPPT operation mode can quickly restore the speed, it can cause a sudden change in active power, leading to a serious secondary frequency drop, posing a new threat to system safety. Therefore, how to prevent secondary frequency drops while providing effective frequency support has become a key technical challenge that urgently needs to be solved. Summary of the Invention

[0005] The technical problem to be solved by the present application is to overcome the shortcomings of the existing technology. The present application provides a frequency support control method and device for a wind turbine based on a comprehensive gain coefficient. The method designs an inertia response coefficient according to the operating state of the unit speed and flexibly adjusts the frequency support capability. The speed recovery coefficient is dynamically updated based on the speed, frequency deviation and its change rate. The inertia response coefficient and the speed recovery coefficient are used to construct a comprehensive gain coefficient. By redefining the speed tracking error, efficient utilization of the rotor kinetic energy is achieved. The method is simple and easy to implement, and can effectively avoid secondary frequency drops while significantly improving the lowest frequency point.

[0006] To achieve the above objectives, the present application provides, in a first aspect, a wind turbine frequency support control method based on a comprehensive gain coefficient, comprising: S1. Frequency support: Design at least one frequency support control mode, and Design the inertia response coefficient in the frequency support control mode , design inertia response coefficient Consider the operating status of the wind turbine speed; S2, speed recovery: Design at least one speed recovery strategy, and In the speed recovery strategy, the speed recovery coefficient is designed based on fuzzy logic. , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; S3, according to the inertia response coefficient and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

[0007] Preferably, S1 includes designing a frequency support trigger mechanism, specifically based on the absolute value of the frequency deviation and activation threshold The size relationship between them makes the control mode switch between MPPT mode and frequency support control mode, which is expressed as: ; in, The activation threshold for the frequency support control mode is set when the absolute value of the frequency deviation is Less than the activation threshold When the wind farm operates in MPPT mode; when the absolute value of the frequency deviation is Exceeding the activation threshold When , the wind farm switches to the frequency support control mode.

[0008] Preferably, the operating status in S1 is the wind turbine speed, minimum speed and speed safety value, inertia response coefficient Expressed as: ; in, is a positive constant, 、 and They are speed, minimum speed and speed safety value respectively.

[0009] Preferably, S2 includes a design speed recovery switching mechanism, specifically: like , indicating that the wind turbines are still capable of increasing their output, giving priority to maintaining frequency support; if , speed recovery is required to avoid low speed and restore power generation potential, among which, is the unit output power, is the initial power.

[0010] Preferably, S2 includes defining language variables using triangular membership functions, including negative large NB, negative small NS, zero ZO, positive small PS and positive large PB, constructing input and output fuzzy sets, using Sugeno type fuzzy reasoning mechanism to establish a fuzzy rule base, and dynamically updating the speed recovery coefficient , expressed as: ; in, is the output scale factor, is the total number of rules, and are the weight and output value of the i-th rule respectively, and i is the index number of the rule.

[0011] Preferably, the comprehensive gain coefficient is designed in S3 , expressed as: ; in, is an integral symbol, which is used to achieve a smooth transition from the frequency support control mode to the speed recovery mode. It is the activation flag of the speed recovery stage. When the activation conditions of the speed recovery mode are met, ,otherwise .

[0012] Preferably, the speed tracking error in S3 Expressed as: ; in, represents the optimal speed, is the control gain coefficient.

[0013] To achieve the above-mentioned purpose, the second aspect of the present application provides a wind turbine frequency support control device based on a comprehensive gain coefficient, the control device comprising: A frequency support unit; configured to design at least one frequency support control mode, and Design the inertia response coefficient in the frequency support control mode , design inertia response coefficient Consider the operating status of the wind turbine speed; A speed recovery unit; configured to design at least one speed recovery strategy, and In the speed recovery strategy, the speed recovery coefficient is designed based on fuzzy logic. , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; Control unit; used to respond to inertia coefficients and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

[0014] To achieve the above-mentioned purpose, the third aspect of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, is used to implement the method described above.

[0015] After adopting the above technical solution, this application has the following beneficial effects compared with the prior art: In this application, an inertia response coefficient is designed based on the operating status of the wind turbine speed, fully utilizing the rotor kinetic energy to provide frequency support while avoiding the risk of wind turbine instability caused by excessive deceleration. On this basis, a fuzzy controller is designed based on the wind turbine speed, frequency deviation, and the rate of change of the frequency deviation. The speed recovery coefficient is dynamically updated. Finally, a comprehensive gain coefficient is constructed by combining the inertia response coefficient and the speed recovery coefficient. The speed tracking error is redefined, fully tapping the frequency support capability of the wind turbine, effectively avoiding secondary frequency drops while significantly increasing the lowest frequency point.

[0016] The specific implementation methods of the present application are further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are part of this application and are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application but do not constitute an undue limitation of this application. Obviously, the drawings described below are only some embodiments. For those of ordinary skill in the art, other drawings can be derived from these drawings without inventive effort.

[0018] In the attached figure: Figure 1 This is a schematic diagram of the steps of the wind turbine frequency support control method in this specific implementation method; Figure 2 This is a design flow chart of the wind turbine frequency support control method in this specific implementation method; Figure 3 This is a system framework diagram of the wind turbine frequency support control method in this specific implementation; Figure 4 Schematic diagram comparing the frequency response curves of the wind turbine frequency support control method in this specific implementation and the traditional method; Figure 5 Schematic diagram showing a comparison between the speed of a wind turbine frequency support control method in this embodiment and a traditional method; Figure 6 Schematic diagram showing the comparison of active power between the wind turbine frequency support control method in this specific implementation and the traditional method; Figure 7 Schematic diagram of the membership function of the speed of the wind turbine frequency support control method in this specific implementation; Figure 8 Schematic diagram of the membership function of the normalized frequency deviation of the wind turbine frequency support control method in this specific implementation manner; Figure 9 Schematic diagram of the membership function of the normalized frequency deviation change rate of the wind turbine frequency support control method in this specific implementation. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application but are not used to limit the scope of the present application.

[0020] See Figure 1 、 Figure 2 and Figure 3 The present application provides a wind turbine frequency support control method based on a comprehensive gain coefficient, comprising: S1. Frequency support: Design at least one frequency support control mode and design the inertia response coefficient under the frequency support control mode. , design inertia response coefficient Consider the operating status of the wind turbine speed; S2. Speed ​​recovery: Design at least one speed recovery strategy and design a speed recovery coefficient based on fuzzy logic in the speed recovery strategy. , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; S3, according to the inertia response coefficient and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

[0021] It should be noted that the execution subject of the control method in this embodiment is a wind turbine frequency support control device, which can be an electronic device, a component in an electronic device, an integrated circuit, or a chip. The electronic device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, etc., and the non-mobile electronic device can be a server and a personal computer, etc., which are not specifically limited in this application. The following describes the wind turbine frequency support control method in this embodiment by taking the execution subject as an example of a server.

[0022] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, the meaning of "plurality" is two or more, unless otherwise clearly specified.

[0023] See Figure 2 and Figure 3 Based on the three-machine nine-node power system simulation platform, a power system model including wind farms is constructed to collect grid frequency signals in real time. , calculate the frequency deviation value , the expression is: ; in, is the rated frequency of the grid.

[0024] See Figure 2 , according to the frequency deviation value obtained by S1 , design the frequency support trigger mechanism, specifically based on the absolute value of the frequency deviation and activation threshold The size relationship between them makes the control mode switch between MPPT mode and frequency support control mode, which is expressed as: ; in, Activate the threshold for frequency support control mode; when the absolute value of the frequency deviation Less than the activation threshold When the wind farm operates in MPPT mode; when the absolute value of the frequency deviation is Exceeding the activation threshold When , the wind farm switches to the frequency support control mode.

[0025] See Figure 1 and Figure 2 In the frequency support control mode designed by S2, the operating state of the wind turbine speed is fully considered, and the inertia response coefficient is designed. , the expression is: ; in, is a positive constant, 、 and They are speed, minimum speed and speed safety value respectively.

[0026] It should be noted that this embodiment automatically adjusts the support strength according to the real-time rotation speed of the wind turbine, fully taps the frequency support capacity of the turbine, and effectively avoids the risk of turbine instability caused by excessive deceleration.

[0027] See Figure 2 , S2 includes the design speed recovery switching mechanism, specifically: if , indicating that the wind turbines are still able to increase their output, giving priority to maintaining frequency support; if , speed recovery is required to avoid low speed and restore power generation potential, among which, is the unit output power, is the initial power.

[0028] Please continue to see Figure 2 , based on the designed speed recovery switching mechanism, design the speed recovery strategy and calculate the frequency change rate , and respectively and After normalization, the expression is: ; ; in, and are the normalized frequency deviation and frequency deviation change rate, and is the input scale factor.

[0029] See Figure 2 and Figure 3 , the normalized frequency deviation obtained is , the absolute value of the normalized frequency change rate and real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the triangular membership function is used to define the language variables, including negative large NB, negative small NS, zero ZO, positive small PS and positive large PB, to construct the input and output fuzzy sets, and the Sugeno type fuzzy inference mechanism is used to establish the fuzzy rule base to dynamically update the speed recovery coefficient. , the expression is: ; in, is the output scale factor, is the total number of rules, and are the weight and output value of the i-th rule respectively.

[0030] It is worth noting that the speed recovery coefficient is dynamically updated based on the real-time status of the wind turbine speed, frequency deviation and its deviation change rate as the input of the fuzzy controller, which effectively realizes the rapid recovery of the speed and the smooth transition to the MPPT mode, thereby improving the power generation stability of the unit.

[0031] It should be noted that the fuzzy rule design principle is: if the frequency deviation is large and the frequency recovery is slow, the speed recovery speed should be slowed down to prevent a secondary frequency drop; if the frequency deviation is small and the frequency recovery rate is fast, the speed recovery speed should be accelerated to ensure the economic benefits of the wind farm and system stability. At the same time, as the speed gradually approaches the optimal speed in MPPT mode, the speed recovery speed will be slowed down to achieve a smooth transition to MPPT mode. The large and slow speeds referred to here are compared with their corresponding preset values, which are set according to the actual needs of technicians in this field.

[0032] The established fuzzy rule table is shown in Table 1: Table 1: Fuzzy rules table

[0033] See Figure 2 and Figure 3 , combined with the inertia response coefficient obtained by S1 and S2 to obtain the speed recovery coefficient , design comprehensive gain coefficient , the expression is: ; in, is an integral symbol, which is used to achieve a smooth transition from the frequency support control mode to the speed recovery mode. It is the activation flag of the speed recovery stage. When the activation conditions of the speed recovery mode are met, ,otherwise .

[0034] Please continue to see Figure 2 and Figure 3 , according to the comprehensive gain coefficient obtained in S3 , redefine the speed tracking error , fully utilizing the rotor kinetic energy to provide frequency support while preventing the speed from falling below the lower speed limit. The expression is: ; in, represents the optimal speed, is the control gain coefficient;

[0035] It should be noted that frequency support and speed recovery are achieved by charging and discharging the rotor kinetic energy according to the frequency deviation. Compared with the additional power control loop design adopted in the prior art, this embodiment effectively reduces the weakening of the frequency support capability of the unit caused by the additional control loop.

[0036] Use PI control method to generate generator torque command , the expression is: ; in, and are the proportional coefficient and the integral coefficient respectively.

[0037] See Figure 2 、 Figure 3 and Figure 4-Figure 9 In order to quantitatively compare the frequency support effects of the wind turbine frequency support control method proposed in this application and the existing traditional methods, this embodiment uses the lowest frequency point as an indicator to measure the frequency support capability.

[0038] See Figure 2This embodiment uses an improved IEEE 9-bus power system simulation platform to verify the effectiveness of the method of this embodiment. In this embodiment, a wind farm consisting of 27 doubly fed wind turbines with a rated power of 1.5MW is used to replace the traditional synchronous generator SG3, and the wind speed is set to 9m / s. The relevant parameters are set as follows:

[0039] See Figure 4 、 Figure 5 and Figure 6 The method of this embodiment is compared in detail with the MPPT strategy, method 1, method 2 and method 3. It should be noted that method 1 is a speed recovery method that first adopts the method proposed in this embodiment and then directly switches to the MPPT operation mode. Method 2 is a method that only adopts the method proposed in this embodiment. Method 3 is a frequency support control method using a fixed coefficient.

[0040] See Figure 2 First, a power system model including a wind farm was built based on the IEEE 9-bus power system simulation platform. The grid frequency signal was collected in real time and the frequency deviation value was calculated. A frequency support trigger mechanism was then designed based on the frequency deviation value. When the absolute value of the frequency deviation was less than the activation threshold, the wind farm operated in MPPT mode. When the absolute value of the frequency deviation exceeded the activation threshold, the wind farm switched to frequency support control mode. Under frequency support control mode, an inertia response coefficient was designed to fully exploit the frequency support capability of the unit. Furthermore, a speed recovery switching mechanism was designed based on the relationship between the unit's output power and initial power. The speed, frequency deviation, and frequency deviation change rate were normalized to eliminate dimensional effects. A fuzzy controller was designed based on the normalized results to dynamically update the speed recovery coefficient. Finally, a comprehensive gain coefficient was constructed by combining the speed recovery coefficient and the inertia response coefficient. The speed tracking error was redefined, and a PI control method was used to generate the generator torque command based on the speed tracking error, effectively improving the frequency stability of the power system.

[0041] See Figure 3 First, under the frequency support control mode, the inertia response coefficient is designed based on the wind turbine's speed state during operation to fully exploit the wind turbine's frequency support capability. Subsequently, a fuzzy controller is designed based on the speed, frequency deviation, and the frequency deviation change rate to dynamically update the speed recovery coefficient. Finally, a comprehensive gain coefficient is constructed by combining the speed recovery coefficient and the inertia response coefficient. The speed tracking error is redefined, and a PI control method is used to generate the generator torque command based on the speed tracking error. This significantly increases the lowest frequency point while effectively preventing secondary frequency drops.

[0042] See Figure 4At 50 seconds, the system load increased by 20MW, causing a grid underfrequency event. Calculations show that the lowest frequency points for the MPPT mode, Method 3, and the method proposed in this example are 49.77Hz, 49.85Hz, and 49.89Hz, respectively. The results show that the method proposed in this example provides the best frequency support compared to the other methods.

[0043] See Figure 5 When a low-frequency event occurs in the power grid, the method proposed in this embodiment can quickly restore the speed to the optimal speed in the MPPT mode and effectively avoid a secondary frequency drop.

[0044] See Figure 6 When a low-frequency event occurs in the power grid, the method proposed in this embodiment can fully utilize the rotor kinetic energy to increase the active power output of the unit and help the system suppress frequency drops.

[0045] Based on the same inventive concept, the present application also provides a wind turbine frequency support control device based on a comprehensive gain coefficient, which includes the following components: Frequency support unit; used to design at least one frequency support control mode and design inertia response coefficient in the frequency support control mode , design inertia response coefficient Consider the operating status of the wind turbine speed; A speed recovery unit; used to design at least one speed recovery strategy and to design a speed recovery coefficient in the speed recovery strategy based on fuzzy logic , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; Control unit; used to respond to inertia coefficients and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

[0046] Based on the same inventive concept, the present application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method described above is implemented.

[0047] The program product of the present application for implementing the above-mentioned method may be a portable compact disk read-only memory and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present application is not limited thereto. In the present application, a readable storage medium may be any tangible medium containing or storing a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0048] It should be noted that a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0049] The above is only a preferred embodiment of the present application and does not constitute any form of limitation to the present application. Although the present application has been disclosed as above with preferred embodiments, it is not intended to limit the present application. Any technician familiar with the present application can make some changes or modifications to equivalent embodiments with equivalent changes using the technical content suggested above without departing from the scope of the technical solution of the present application. The implementation schemes in the above embodiments can also be further combined or replaced. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present application that do not depart from the content of the technical solution of the present application still fall within the scope of the solution of the present application.

Claims

1. A wind turbine frequency support control method based on a comprehensive gain coefficient, characterized in that: include: S1. Frequency support: Design at least one frequency support control mode, and Design the inertia response coefficient in the frequency support control mode , design inertia response coefficient Consider the operating status of the wind turbine speed; S2, speed recovery: Design at least one speed recovery strategy, and In the speed recovery strategy, the speed recovery coefficient is designed based on fuzzy logic. , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; S3, according to the inertia response coefficient and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

2. The method according to claim 1, characterized in that S1 includes the design of frequency support trigger mechanism, specifically: according to the absolute value of frequency deviation and activation threshold The size relationship between them makes the control mode switch between MPPT mode and frequency support control mode, which is expressed as: ； in, The activation threshold for the frequency support control mode is set when the absolute value of the frequency deviation is Less than the activation threshold When the wind farm operates in MPPT mode; when the absolute value of the frequency deviation is Exceeding the activation threshold When , the wind farm switches to the frequency support control mode.

3. The method according to claim 1, characterized in that The operating status in S1 is the wind turbine speed, minimum speed and speed safety value, inertia response coefficient Expressed as: ； in, is a positive constant, 、 and They are speed, minimum speed and speed safety value respectively.

4. The method according to claim 1, wherein S2 includes the design speed recovery switching mechanism, specifically: like , indicating that the wind turbines are still capable of increasing their output, giving priority to maintaining frequency support; if , speed recovery is required to avoid low speed and restore power generation potential, among which, is the unit output power, is the initial power.

5. The method according to claim 2, characterized in that S2 includes using triangular membership functions to define language variables, including negative large NB, negative small NS, zero ZO, positive small PS and positive large PB, constructing input and output fuzzy sets, using Sugeno type fuzzy reasoning mechanism to establish fuzzy rule base, and dynamically updating speed recovery coefficient , expressed as: ； in, is the output scale factor, is the total number of rules, and are the weight and output value of the i-th rule respectively, and i is the index number of the rule.

6. The method according to claim 1, characterized in that Design comprehensive gain coefficient in S3 , expressed as: ； in, is an integral symbol, which is used to achieve a smooth transition from the frequency support control mode to the speed recovery mode. It is the activation flag of the speed recovery stage. When the activation conditions of the speed recovery mode are met, ,otherwise .

7. The method according to claim 4, characterized in that S3 speed tracking error Expressed as: ； in, represents the optimal speed, is the control gain coefficient.

8. A wind turbine frequency support control device based on a comprehensive gain coefficient, characterized in that: The control device comprises: A frequency support unit; configured to design at least one frequency support control mode, and Design the inertia response coefficient in the frequency support control mode , design inertia response coefficient Consider the operating status of the wind turbine speed; A speed recovery unit; configured to design at least one speed recovery strategy, and In the speed recovery strategy, the speed recovery coefficient is designed based on fuzzy logic. , specifically the normalized frequency deviation , frequency deviation change rate and the real-time speed of wind turbines As the input of the fuzzy controller, the speed recovery coefficient As the output of the fuzzy controller, the speed recovery coefficient is dynamically updated , to achieve rapid recovery of wind turbine speed; Control unit; used to respond to inertia coefficients and speed recovery coefficient Design comprehensive gain coefficient , based on the comprehensive gain coefficient Redefining speed tracking error , based on the speed tracking error Use PI control method to generate generator torque command .

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the method according to any one of claims 1 to 7.

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