Method, system and device for controlling active power of wind turbine generator and medium

Abstract

The invention relates to the technical field of variable-speed wind turbine generator control, and discloses a wind turbine generator active power control method, system and device and a medium, and the method comprises the steps: S1, calculating a normalized power tracking error and a power tracking error variable quantity; s2, designing a fuzzy controller based on S1, and dynamically updating filtering parameters; s3, designing a double-stage control architecture based on the filtering parameters updated in S2; s4, based on the double-stage control architecture designed in the S3, designing a kinetic energy utilization coefficient, and redefining a rotating speed tracking error; and S5, based on the torque reference values generated in S3 and S4, a final torque reference value is generated through a torque controller, and power control is achieved in cooperation with a pitch angle controller. The method can fully coordinate the response characteristic difference of the variable pitch and torque execution mechanisms of the wind turbine generator, effectively improves the power tracking performance, and reduces the load of the variable pitch system.

Description

Technical Field

[0001] This application relates to the technical field of variable-speed wind turbine control, and particularly to a control method, system, device and medium for the active power of a wind turbine. Background Art

[0002] With the increasing severity of fossil fuel shortages and environmental pollution problems, the development of clean and sustainable energy has become a global consensus. As an important renewable energy source, wind energy has developed rapidly due to its clean and environmentally friendly characteristics. However, with the continuous increase in the penetration rate of wind power, its inherent intermittency and volatility are likely to cause the grid frequency and voltage deviations to exceed the allowable range, posing a severe challenge to the safe and stable operation of the power system. Active Power Control (APC) is a key means to solve this problem, enabling the wind power generation system to provide important ancillary services for the power grid. Through APC technology, wind turbines can respond to grid dispatching commands in real time and effectively maintain the power balance of the power system.

[0003] As an effective APC method, the Pitch Angle Control (PAC) strategy feeds the power tracking error back to the pitch angle controller, controls the power output of the wind turbine by adjusting the pitch angle, and realizes the tracking of active power. This method has a wide speed regulation range. At the same time, the torque control loop maintains the rotor speed at the optimal operating point according to the optimal power curve. However, limited by the mechanical characteristics of the pitch bearing and servo motor, the response speed of the pitch system is relatively slow. To improve the power tracking performance, frequent pitch actions are required, which will significantly increase the mechanical load of the pitch system and shorten the service life of the equipment.

[0004] To address this problem, researchers have proposed an APC strategy based on active disturbance rejection control. This method improves the power tracking performance and reduces the pitch system load through the collaborative design of active disturbance rejection control based on error and multi-objective optimization. However, the above studies have all ignored the differences in the response speeds of different actuators of wind turbines. Generally speaking, the response speed of the torque control loop of modern large-scale wind turbines is faster than that of the pitch control loop, and the reasonable coordination of the two will effectively improve the control performance. When only relying on the pitch system for power tracking, its slow dynamic response speed will not only affect the power tracking accuracy but also reduce the effect of optimizing the pitch system load. Summary of the Invention

[0005] The technical problem to be solved by this application is to overcome the deficiencies of the prior art. This application provides a control method, system, device and medium for the active power of a wind turbine, which can fully coordinate the response characteristic differences between the pitch and torque actuators of the wind turbine, effectively improve the power tracking performance and reduce the pitch system load.

[0006] To achieve the above object, a first aspect of the present application provides a method for controlling the active power of a wind turbine, including the following steps: S1. Under turbulent wind conditions, calculate the normalized power tracking error and the change in power tracking error based on the active power command issued by the wind farm control center; S2. Design a fuzzy controller based on S1 to dynamically update the filtering parameters : Take the and obtained in S1 as the inputs of the fuzzy controller, define the linguistic variables using triangular membership functions, and construct the input-output fuzzy sets; according to the obtained input-output fuzzy sets, establish a fuzzy rule base through a fuzzy inference mechanism to dynamically adjust the filtering parameters ; S3. Based on the filtering parameters updated in S2 , design a two-stage control architecture: Decompose the power tracking error into a low-frequency component and a high-frequency component. Design a pitch angle controller for the low-frequency component to generate a pitch angle reference value, which is responded by the pitch system; design a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, which is responded by the torque system; S4. Based on the two-stage control architecture designed in S3, design a kinetic energy utilization coefficient, redefine the speed tracking error , generate a torque reference value based on the speed tracking error through the torque controller, and use the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; S5. Based on the torque reference values generated in S3 and S4, generate a final torque reference value through the torque controller, and cooperate with the pitch angle controller to achieve power control.

[0007] Optionally, in S1, calculating the normalized power tracking error and the change in power tracking error based on the active power command issued by the wind farm control center includes: Under turbulent wind conditions, calculate the power tracking error based on the active power command issued by the wind farm control center , which is expressed as: ; where is the actual output power of the wind turbine unit; According to the obtained power tracking error, with the sampling period as the interval, calculate the change in power tracking error , expressed as: ; Among them, represents the power tracking error at the current moment, is the power tracking error at the previous moment; Design the input scaling factors and , and respectively normalize the obtained power tracking error and the change in power tracking error , expressed as: ; ; Among them, and are the normalized power tracking error and the change in power tracking error respectively.

[0008] Optionally, in S2, design a fuzzy controller based on S1 to dynamically update the filtering parameter ; including: Take the power tracking error and the change in power tracking error as the input of the fuzzy controller, and the filtering parameter as the output of the fuzzy controller. Use triangular membership functions to define linguistic variables, and the linguistic variables include NB, NS, ZO, PS, and PB. Construct input-output fuzzy sets to achieve fuzzification; According to the obtained input-output fuzzy sets, use the Sugeno-type fuzzy inference mechanism to establish a fuzzy rule base containing N rules to dynamically adjust the filtering parameter , expressed as: ; Among them, is the output scaling factor, and are the weight and output value of the i-th rule respectively, N and are the total number of rules in the fuzzy rule base and the index number of the current rule respectively, is the reference value of the filtering parameter.

[0009] Optionally, in S3, design a two-stage control architecture based on the filtering parameter updated in S2; including: Utilize the obtained filtering parameter , a two-stage control architecture is designed. The error signal is decomposed into a low-frequency component and a high-frequency component through complementary high-pass and low-pass filters, which are respectively expressed as: ; ; Among them, represents the low-frequency component, represents the high-frequency component, and represent the complementary high-pass filter and low-pass filter, which are respectively designed as and , where is the Laplace operator; The obtained low-frequency component is responded by the pitch system. A pitch angle controller is designed and the PI control method is adopted, which is expressed as: ; Among them, is the pitch angle reference value, and are respectively the proportional and integral gains of the pitch angle controller The obtained high-frequency component is responded by the torque system. A torque controller is designed and the PI control method is adopted, which is expressed as: ; Among them, is the torque reference value based on the high-frequency component, and are respectively the proportional and integral gains of the torque controller based on the high-frequency component.

[0010] Optionally, based on the two-stage control architecture designed in S4, a kinetic energy utilization coefficient is designed, and the speed tracking error is redefined. A torque reference value based on the speed tracking error is generated through the torque controller, and the kinetic energy stored in the rotor is used to eliminate the power deviation between the actual output power and the active power command ; including: Based on the two-stage architecture, a kinetic energy utilization coefficient is further designed, the speed tracking error is redefined, and the kinetic energy stored in the rotor is used to eliminate the power deviation between the output power and . The PI control method is adopted, which is expressed as: ; Among them, represents the speed tracking error, represents the rotor speed, represents the optimal speed, is the control gain coefficient, is the torque reference value based on the rotational speed tracking error, and are the proportional and integral gains of the torque controller based on the rotational speed tracking error, respectively; wherein, the kinetic energy utilization coefficient is designed as: ; wherein, is a positive constant, represents the power tracking error.

[0011] Optionally, the torque reference value generated based on S3 and S4 in S5 generates the final torque reference value through the torque controller, and cooperates with the pitch angle controller to achieve power control; including: the finally designed torque controller is expressed as: ; wherein, is the comprehensive torque reference value, represents the torque reference value based on the high-frequency component, represents the torque reference value based on the rotational speed tracking error.

[0012] To achieve the above object, the second aspect of the present application provides a control system for the active power of a wind turbine, and the control system includes: a calculation unit, and the power error calculation unit is used to calculate the normalized power tracking error and the power tracking error variation according to the active power instruction issued by the wind farm control center ; a dynamic adjustment unit, and the dynamic adjustment unit designs a fuzzy controller based on the calculation unit to dynamically update the filtering parameter : taking the and obtained by the calculation unit as the input of the fuzzy controller, defining the linguistic variable by using the triangular membership function, and constructing the input and output fuzzy sets; according to the obtained input and output fuzzy sets, establishing a fuzzy rule base through the fuzzy inference mechanism to dynamically adjust the filtering parameter ; a frequency domain decomposition unit, and the frequency domain decomposition unit designs a two-stage control architecture based on the filtering parameter updated by the dynamic adjustment unit: decomposing the power tracking error into a low-frequency component and a high-frequency component, designing a pitch angle controller for the low-frequency component to generate a pitch angle reference value, and the pitch system responds; designing a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, and the torque system responds; Kinetic energy regulation unit, which designs a kinetic energy utilization coefficient based on the two-stage control architecture designed by the frequency domain decomposition unit and redefines the speed tracking error , generates a torque reference value based on the speed tracking error through a torque controller, and utilizes the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; Torque cooperative control unit, which generates a final torque reference value through a torque controller based on the torque reference values generated by the frequency domain decomposition unit and the kinetic energy regulation unit, and cooperates with the pitch angle controller to achieve power control.

[0013] To achieve the above object, a third aspect of the present application provides a control device for the active power of a wind turbine, including a processor and a memory. A computer program is stored on the memory, and when the computer program is executed by the processor, the method described above is implemented.

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

[0015] After adopting the above technical solutions, the present application has the following beneficial effects compared with the prior art: In view of the fact that the traditional PAC method fails to effectively coordinate the dynamic response characteristic differences between the pitch system and the torque system during power tracking, resulting in a significant increase in the load of the pitch system, the present application designs a method for controlling the active power of a wind turbine. Based on the adaptive filtering parameters, a two-stage control architecture is constructed, and the error signal is decomposed into high-frequency and low-frequency components to be responded by the torque system and the pitch system respectively, realizing the coordinated cooperation of different actuators and improving the power tracking performance. In view of the fact that the traditional PAC method makes insufficient use of the rotor kinetic energy during power tracking, the present application designs a kinetic energy utilization coefficient and redefines the speed tracking error, realizing the efficient utilization of the rotor kinetic energy during power tracking and effectively reducing the load of the pitch system.

[0016] The following further describes in detail the specific implementation manners of the present application with reference to the accompanying drawings. Description of the Drawings

[0017] The accompanying drawings, as a part of the present application, are used to provide a further understanding of the present application. The schematic embodiments and descriptions thereof of the present application are used to explain the present application, but do not constitute an improper limitation to the present application. Obviously, the accompanying drawings in the following description are only some embodiments, and those of ordinary skill in the art can obtain other drawings according to these drawings without creative efforts.

[0018] In the accompanying drawings: Figure 1Schematic diagram of the steps of the active power control method for a wind turbine in this specific embodiment; Figure 2 Design flow chart of the active power control method for a wind turbine in this specific embodiment; Figure 3 System framework diagram of the active power control method for a wind turbine in this specific embodiment; Figure 4 Actual input wind speed diagram of the active power control method for a wind turbine in this specific embodiment; Figure 5 Wind turbine speed comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 6 Pitch angle comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 7 Pitch angle change rate comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 8 Power generation comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 9 Electromagnetic torque comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 10 Lateral moment of blade root comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 11 Longitudinal moment of blade root comparison diagram between the traditional PAC method and the method in this specific embodiment; Figure 12 Membership function of the normalized power tracking error in this specific embodiment; Figure 13 Membership function of the change amount of the normalized power tracking error in this specific embodiment. Specific embodiment

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments in conjunction with the accompanying drawings in the embodiments of this application. The following embodiments are used to illustrate this application but do not limit the scope of this application.

[0020] This embodiment provides a method for controlling the active power of a wind turbine, including the following steps: S1. Under turbulent wind conditions, according to the active power command issued by the wind farm control center , calculate the normalized power tracking error and the change amount of the power tracking error ; S2. Design a fuzzy controller based on S1 to dynamically update the filtering parameters : Take the and obtained in S1 as the inputs of the fuzzy controller, define the linguistic variables using triangular membership functions, and construct the input-output fuzzy sets; based on the obtained input-output fuzzy sets, establish a fuzzy rule base through a fuzzy inference mechanism to dynamically adjust the filtering parameters ; S3. Based on the filtering parameters updated in S2 , design a two-stage control architecture: Decompose the power tracking error into a low-frequency component and a high-frequency component. Design a pitch angle controller for the low-frequency component to generate a pitch angle reference value, which is responded by the pitch system; design a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, which is responded by the torque system; S4. Based on the two-stage control architecture designed in S3, design a kinetic energy utilization coefficient and redefine the speed tracking error , generate a torque reference value based on the speed tracking error through the torque controller, and use the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; S5. Based on the torque reference values generated in S3 and S4, generate a final torque reference value through the torque controller, and cooperate with the pitch angle controller to achieve power control.

[0021] It should be noted that in this embodiment, the execution subject of the visual question answering method is the active power control device of the wind turbine generator set, and this device can be an electronic device, a component in the electronic device, an integrated circuit, or a chip. The electronic device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted electronic device, a wearable device, etc., and the non-mobile electronic device can be a server and a personal computer, etc. This application does not make specific limitations. Hereinafter, taking the execution subject as the server as an example, the active power control method of the wind turbine generator set in this embodiment will be described.

[0022] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of this application, "a plurality" means two or more, unless otherwise specifically defined.

[0023] In a feasible implementation, in S1, according to the active power command issued by the wind farm control center , calculate the normalized power tracking error and the change in power tracking error ; including: Under turbulent wind conditions, use the turbulent wind with a time of 600 s and an average wind speed of 11 m / s as the input of the OpenFAST wind power technology simulation platform, and according to the active power command issued by the wind farm control center , calculate the power tracking error , expressed as: ; Among them, is the actual output power of the fan unit; According to the obtained power tracking error , at the sampling period as the interval, calculate the change in power tracking error , expressed as: ; Among them, represents the power tracking error at the current moment, is the power tracking error at the previous moment; Design the input scale factor and , and respectively normalize the obtained power tracking error and the change in power tracking error , expressed as: ; ; Among them, and are the normalized power tracking error and the change in power tracking error respectively.

[0024] In a realizable embodiment, in S2, a fuzzy controller is designed based on S1 to dynamically update the filtering parameters ; including: Use the power tracking error and the change in power tracking error as the input of the fuzzy controller, and the filtering parameter as the output of the fuzzy controller. Use the triangular membership function to define the linguistic variables, and the linguistic variables include NB, NS, ZO, PS, and PB. Construct the input-output fuzzy set to achieve the fuzzification process; According to the obtained input-output fuzzy set, use the Sugeno-type fuzzy inference mechanism to establish a fuzzy rule base containing N rules to dynamically adjust the filtering parameter , expressed as: ; Among them, is the output scale factor, and are respectively the weight and output value of the th rule, N and are respectively the total number of rules in the fuzzy rule base and the index number of the current rule, is the reference value of the filtering parameter.

[0025] In practical applications, the fuzzy rule base established in S2 is shown in Table 1: Table 1: Fuzzy Rule Base

[0026] Specifically, the fuzzy rule base is expressed as: Rule 1: If is NB and is NB then is PS; Rule 2: If is NB and is NS then is PS; Rule 3: If is NS and is NB then is ZO; Rule i: If is PB and is PB then is NS; Among them, N is the total number of rules in the fuzzy rule base, i is the index number of the current rule, is the reference value of the filtering parameter, and are respectively the normalized power tracking error and the change in power tracking error.

[0027] In an implementable embodiment, considering the dynamic response characteristic differences between the pitch system and the torque system actuators of the wind turbine, the filtering parameter updated based on S2 in S3 is used to design a two-stage control architecture; including: Using the obtained filtering parameter ; ; Among them, represents the low-frequency component, represents the high-frequency component, and represent complementary high-pass and low-pass filters, respectively designed as and , where is the Laplacian operator; The obtained low-frequency component is responded by the pitch system, and a pitch angle controller is designed, adopting the PI control method, expressed as: ; Among them, is the pitch angle reference value, and are the proportional and integral gains of the pitch angle controller respectively The obtained high-frequency component is responded by the torque system, and a torque controller is designed, adopting the PI control method, expressed as: ; Among them, is the torque reference value based on the high-frequency component, and are the proportional and integral gains of the torque controller based on the high-frequency component respectively.

[0028] In an achievable implementation, for the two-stage control architecture designed based on S3 in S4, the kinetic energy utilization coefficient is designed, and the speed tracking error is redefined , and a torque reference value based on the speed tracking error is generated through the torque controller, and the kinetic energy stored in the rotor is used to eliminate the power deviation between the actual output power and the active power command ; including: Based on the two-stage architecture, the kinetic energy utilization coefficient is further designed, the speed tracking error is redefined, and the kinetic energy stored in the rotor is used to eliminate the power deviation between the output power and , adopting the PI control method, expressed as: ; Among them, represents the speed tracking error, represents the rotor speed, represents the optimal speed, is the control gain coefficient, is the torque reference value based on the speed tracking error, and are the proportional and integral gains of the torque controller based on the speed tracking error respectively; Among them, the kinetic energy utilization coefficient is designed as: ; Among them, is a positive constant, represents the power tracking error.

[0029] In an achievable implementation, based on the torque reference value generated in S3 and S4 in S5, the final torque reference value is generated through the torque controller, and power control is achieved in coordination with the pitch angle controller; including: The finally designed torque controller is expressed as: ; Among them, is the comprehensive torque reference value, represents the torque reference value based on the high-frequency component, represents the torque reference value based on the speed tracking error.

[0030] It should be noted that under the designed two-stage control architecture and the action of the kinetic energy utilization coefficient in this embodiment, the dynamic response characteristic differences between the pitch system and the torque system can be effectively coordinated, and the rotor kinetic energy can be fully utilized to eliminate the power deviation. It is simple and easy to implement, and while improving the power tracking performance, it reduces the load of the pitch system.

[0031] In this embodiment, the wind power technology development software OpenFAST simulation platform is used to verify the effectiveness of the method in this embodiment. In this embodiment, a 5MW three-blade horizontal axis variable-speed wind turbine model is used, and the main parameters are shown in Table 2: Table 2: Main parameters of the 5MW three-blade horizontal axis variable-speed wind turbine model

[0032] To quantitatively compare the control effects of the active power control method of the wind turbine proposed in this embodiment and the traditional PAC method, it is necessary to explain the evaluation index of the pitch angle load. In actual operation, frequent adjustment of the pitch angle will significantly increase the mechanical load of the pitch system and shorten the service life of the key components of the unit. Therefore, this embodiment introduces pitch fatigue (PF) as the evaluation index of the pitch system, which is expressed as: ; Among them, represents the pitch angle of the wind turbine, with the unit of , is the total operating time of the unit, k represents the current moment, represents the pitch angle at the next moment, and thus the unit of the above index is , which reflects the change amount of the pitch angle per second on average within seconds during the operation period of the unit, can better evaluate the load condition of the pitch system. At the same time, to more comprehensively evaluate the effectiveness of the proposed method, this embodiment also uses the Damage Equivalent Load (DEL) as an index to measure the load magnitudes of the drive train and the blade root.

[0033] Figure 6 is the pitch angle comparison diagram. After calculation, the total pitch angle adjustment amount of the traditional PAC method is 218.07 , and the total pitch angle adjustment amount of the method proposed in this embodiment is 140.94 , a reduction of 35.37%.

[0034] Figure 7 is the pitch angle change rate comparison diagram. After calculation, the pitch system load evaluation index PF of the traditional PAC method is 0.3635 , and the pitch system load evaluation index PF of the method proposed in this embodiment is 0.2349 , a reduction of 35.37%.

[0035] Figure 8 is the generated power comparison diagram. After calculation, the root mean square deviation of the power of the traditional PAC method is 58.11 kw, and the root mean square deviation of the power of the method proposed in this embodiment is 49.99 kw, a reduction of 13.97%.

[0036] Figure 9 is the electromagnetic torque comparison diagram. After calculation, the DEL of the drive train of the traditional PAC method is 5.704 kN-m, and the DEL of the drive train of the method proposed in this embodiment is 5.604 kN-m, a reduction of 1.8%.

[0037] Figure 10 is the blade root lateral moment comparison diagram. After calculation, the DEL of the traditional PAC method in the blade root lateral moment is 8665.22 kN-m, and the equivalent fatigue load of the method proposed in this embodiment in the blade root lateral moment is 8642.65 kN-m, a reduction of 0.26%.

[0038] Figure 11 is the blade root longitudinal moment comparison diagram. After calculation, the DEL of the traditional PAC method in the blade root longitudinal moment is 7505.75 kN-m, and the equivalent fatigue load of the method proposed in this embodiment in the blade root longitudinal moment is 7183.65 kN-m, a reduction of 4.29%.

[0039] Figure 12 and Figure 13 are the normalized power tracking error and the change amount of the power tracking error respectively Schematic diagram of membership function

[0040] Based on the same inventive concept, the present application also provides a control system for the active power of a wind turbine. The control system includes: A calculation unit. The power error calculation unit is used to calculate the normalized power tracking error and the change amount of the power tracking error according to the active power command issued by the wind farm control center ; A dynamic adjustment unit. The dynamic adjustment unit designs a fuzzy controller based on the calculation unit and dynamically updates the filtering parameters : Using the and obtained by the calculation unit as the inputs of the fuzzy controller, defining linguistic variables using triangular membership functions, and constructing input-output fuzzy sets; according to the obtained input-output fuzzy sets, establishing a fuzzy rule base through a fuzzy inference mechanism to dynamically adjust the filtering parameters ; A frequency domain decomposition unit. The frequency domain decomposition unit designs a two-stage control architecture based on the filtering parameters updated by the dynamic adjustment unit : Decomposing the power tracking error into a low-frequency component and a high-frequency component, designing a pitch angle controller for the low-frequency component to generate a pitch angle reference value, which is responded by the pitch system; designing a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, which is responded by the torque system; A kinetic energy regulation unit. The kinetic energy regulation unit designs a kinetic energy utilization coefficient based on the two-stage control architecture designed by the frequency domain decomposition unit, redefines the speed tracking error , generating a torque reference value based on the speed tracking error through the torque controller, and using the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; A torque cooperative control unit. The torque cooperative control unit generates a final torque reference value through the torque controller based on the torque reference values generated by the frequency domain decomposition unit and the kinetic energy regulation unit, and cooperates with the pitch angle controller to achieve power control.

[0041] Based on the same inventive concept, the present application also provides a control device for the active power of a wind turbine, including a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the control method for the active power of the wind turbine as described above is implemented.

[0042] Based on the same inventive concept, the present application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the control method for the active power of a wind turbine as described above.

[0043] The program product for implementing the above method in the present application may be a portable compact disc read-only memory and includes program code, and may 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, the readable storage medium may be any tangible medium that contains or stores a program, and this program may be used by or in combination with an instruction execution system, device, or component.

[0044] It should be noted that the computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium may also be any readable medium other than the readable storage medium, and this readable medium may send, propagate, or transmit a program for use by or in combination with an instruction execution system, device, or component. The program code contained on the readable storage medium may be transmitted by any appropriate medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0045] The above are only the preferred embodiments of the present application, and do not impose any formal limitations on the present application. Although the present application has been disclosed above with the preferred embodiments, it is not intended to limit the present application. Any person skilled in the art of the present application, without departing from the scope of the technical solution of the present application, may make some modifications or decorations using the technical content prompted above to form equivalent embodiments of equivalent changes. The implementation schemes in the above embodiments may also be further combined or replaced. However, as long as the content does not depart from the technical solution of the present application, any simple modification, equivalent change, and decoration made to the above embodiments according to the technical essence of the present application still fall within the scope of the present application's solution.

Claims

1. A method for controlling the active power of a wind turbine, characterized in that, It includes the following steps: S1. Under turbulent wind conditions, calculate the normalized power tracking error and the change in power tracking error according to the active power command issued by the wind farm control center ; S2. Design a fuzzy controller based on S1 and dynamically update the filtering parameters : The and obtained by S1 are used as the inputs of the fuzzy controller. Triangular membership functions are used to define the linguistic variables, and the input and output fuzzy sets are constructed. Based on the obtained input and output fuzzy sets, a fuzzy rule base is established through a fuzzy inference mechanism to dynamically adjust the filtering parameters. ; S3. Filter parameters updated based on S2 , design a two-stage control architecture: Decompose the power tracking error into a low-frequency component and a high-frequency component. Design a pitch angle controller for the low-frequency component to generate a pitch angle reference value, which is responded by the pitch system; design a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, which is responded by the torque system; S4. Based on the two-stage control architecture designed in S3, design the kinetic energy utilization coefficient and redefine the speed tracking error , generate a torque reference value based on the speed tracking error through the torque controller, and utilize the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; S5. Based on the torque reference values generated in S3 and S4, a final torque reference value is generated through a torque controller, and power control is achieved in cooperation with a pitch angle controller.

2. The method according to claim 1, wherein In S1, according to the active power command issued by the wind farm control center , calculate the normalized power tracking error and the change in power tracking error ; including: Under turbulent wind conditions, calculate the power tracking error according to the active power command issued by the wind farm control center , which is expressed as : ； Among them, is the actual output power of the fan unit; According to the obtained power tracking error , at intervals of the sampling period , calculate the change in the power tracking error , expressed as: ； Among them, represents the power tracking error at the current moment, is the power tracking error at the previous moment; Design input scale factor and , respectively, normalize the obtained power tracking error and the change in power tracking error as follows: ； ； Among them, and are the normalized power tracking error and the change in the power tracking error, respectively.

3. The method according to claim 1, wherein Design a fuzzy controller based on S1 in S2 to dynamically update the filtering parameters ; including: Take the power tracking error and the change in power tracking error as the inputs of the fuzzy controller, and the filtering parameter as the output of the fuzzy controller. Define the linguistic variables using triangular membership functions. The linguistic variables include NB, NS, ZO, PS, and PB, where NB represents negative large, NS represents negative small, ZO represents zero, PS represents positive small, and PB represents positive large. Construct the input-output fuzzy sets to achieve the fuzzification process; According to the obtained input-output fuzzy sets, a Sugeno-type fuzzy inference mechanism is adopted to establish a fuzzy rule base containing N rules and dynamically adjust the filtering parameters. , which is expressed as: ； Among them, is the output scale factor, and are the weight and output value of the i-th rule respectively, N and are the total number of rules in the fuzzy rule base and the index number of the current rule respectively, is the reference value of the filtering parameter.

4. The method according to claim 1, wherein Filter parameters updated based on S2 in S3 , a two-stage control architecture is designed; It includes: Using the obtained filtering parameters , a two-stage control architecture is designed. The error signal is decomposed into a low-frequency component and a high-frequency component through complementary high-pass and low-pass filters, which are respectively expressed as: ； ； Among them, represents the low-frequency component, represents the high-frequency component, and represent complementary high-pass and low-pass filters, respectively designed as and , where is the Laplacian operator; The obtained low-frequency component is responded by a pitch system, a pitch angle controller is designed, and a PI control method is adopted, which is expressed as: ； wherein, is the pitch angle reference value, and are the proportional and integral gains of the pitch angle controller respectively The obtained high-frequency component is responded by a torque system, a torque controller is designed, and a PI control method is adopted, which is expressed as: ； wherein, is the torque reference value based on the high-frequency component, and are the proportional and integral gains of the torque controller based on the high-frequency component, respectively.

5. The method according to claim 3, characterized in that Based on the dual-stage control architecture designed in S3 in S4, design the kinetic energy utilization coefficient and redefine the speed tracking error , generate a torque reference value based on the speed tracking error through the torque controller, and utilize the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; including: Based on the two-stage architecture, the kinetic energy utilization coefficient is further designed , and the rotational speed tracking error is redefined , and the kinetic energy stored in the rotor is used to eliminate the power deviation between the output power and the rated power, and the PI control method is adopted, which is expressed as: ； Among them, represents the rotational speed tracking error, represents the rotor speed, represents the optimal speed, is the control gain coefficient, is the torque reference value based on the rotational speed tracking error, and are the proportional and integral gains of the torque controller based on the rotational speed tracking error respectively; Among them, the kinetic energy utilization coefficient is designed as: ； Among them, is a positive constant, represents the power tracking error.

6. The method according to claim 1, wherein In S5, based on the torque reference values generated in S3 and S4, a final torque reference value is generated through a torque controller, and power control is achieved in cooperation with a pitch angle controller; it includes: the finally designed torque controller is expressed as: ； Among them, is the comprehensive torque reference value, represents the torque reference value based on the high-frequency component, represents the torque reference value based on the speed tracking error.

7. The control system for the active power of a wind turbine, characterized in that, The control system includes: A calculation unit, and the power error calculation unit is configured to calculate a normalized power tracking error and a change amount of the power tracking error according to an active power command issued by a wind farm control center ; A dynamic adjustment unit, which designs a fuzzy controller based on a computing unit and dynamically updates filtering parameters : The and obtained by the computing unit are used as inputs of the fuzzy controller. Triangular membership functions are used to define linguistic variables, and input and output fuzzy sets are constructed. According to the obtained input and output fuzzy sets, a fuzzy rule base is established through a fuzzy inference mechanism to dynamically adjust filtering parameters ; A frequency-domain decomposition unit, which is based on the filtering parameters updated by the dynamic adjustment unit , designs a two-stage control architecture: decomposes the power tracking error into a low-frequency component and a high-frequency component, designs a pitch angle controller for the low-frequency component to generate a pitch angle reference value, which is responded by the pitch system; designs a torque controller for the high-frequency component to generate a torque reference value based on the high-frequency component, which is responded by the torque system; Kinetic energy regulation unit, which designs a kinetic energy utilization coefficient and redefines the speed tracking error based on the two-stage control architecture designed by the frequency domain decomposition unit , generates a torque reference value based on the speed tracking error through a torque controller, and uses the kinetic energy stored in the rotor to eliminate the power deviation between the actual output power and the active power command ; A torque cooperative control unit, which, based on the torque reference values generated by a frequency domain decomposition unit and a kinetic energy regulation unit, generates a final torque reference value through a torque controller, and achieves power control in cooperation with a pitch angle controller.

8. A control device for the active power of a wind turbine, characterized in that, It includes a processor and a memory, and a computer program is stored on the memory. When the computer program is executed by the processor, the method described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it is used to implement the method described in any one of claims 1-6.

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