Wind turbine active power control method, system, device and medium

Abstract

The present application relates to the technical field of variable-speed wind turbine control, and discloses a method, system, device, and medium for controlling the active power of a wind turbine. The method comprises the following steps: S1, calculating the normalized power tracking error and the power tracking error variation; S2, designing a fuzzy controller based on S1, and dynamically updating the filter parameters; S3, designing a two-stage control architecture based on the filter parameters updated in S2; S4, designing a kinetic energy utilization coefficient based on the two-stage control architecture designed in S3, and redefining the speed tracking error; S5, generating a final torque reference value through a torque controller based on the torque reference value generated in S3 and S4, and coordinating with the pitch angle controller to achieve power control. The present application can fully coordinate the response characteristic differences between the wind turbine pitch and torque actuators, effectively improving the power tracking performance and reducing the load on the pitch system.

Description

Technical Field

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

[0002] With fossil fuel shortages and environmental pollution becoming increasingly serious, the development of clean and sustainable energy has become a global consensus. Wind power, as an important renewable energy source, has rapidly grown due to its clean and environmentally friendly characteristics. However, as wind power penetration continues to increase, its inherent intermittent and volatile nature can easily cause grid frequency and voltage deviations to exceed allowable ranges, posing a serious challenge to the safe and stable operation of the power system. Active Power Control (APC) is a key solution to this problem, enabling wind power systems to provide important ancillary services to the power grid. Through APC technology, wind turbines can respond to grid dispatch commands in real time, effectively maintaining power balance in the power system.

[0003] As an effective APC method, the Pitch Angle Control (PAC) strategy feeds back the power tracking error to the pitch angle controller, controlling the wind turbine's power output by adjusting the pitch angle to achieve active power tracking. This method has a wide speed regulation range. Meanwhile, the torque control loop maintains the rotor speed at the optimal operating point based on the optimal power curve. However, due to the mechanical characteristics of the pitch bearing and servo motor, the response speed of the pitch system is relatively slow. To improve power tracking performance, frequent pitch changes are required, which significantly increases the mechanical load on the pitch system and shortens the equipment's service life.

[0004] To address this issue, researchers have proposed an APC strategy based on active disturbance rejection control (APC). This approach improves power tracking performance and reduces pitch system loads through the collaborative design of error-based active disturbance rejection control and multi-objective optimization. However, the aforementioned studies have all ignored the differences in response speeds among different actuators in wind turbines. Generally speaking, the torque control loop of modern large wind turbines responds faster than the pitch control loop, and proper coordination of the two will effectively improve control performance. When relying solely on the pitch system for power tracking, its slower dynamic response speed not only affects the power tracking accuracy but also reduces the effectiveness of pitch system load optimization. Summary of the Invention

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

[0006] To achieve the above objectives, the present application provides, in a first aspect, a method for controlling the active power of a wind turbine generator system, comprising the following steps:

[0007] 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 power tracking error variation ;

[0008] S2, design a fuzzy controller based on S1 and dynamically update the filter parameters :

[0009] S1 obtains and As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets; based on the obtained input and output fuzzy sets, the fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameters. ;

[0010] S3, filter parameters updated based on S2 , design a two-stage control architecture:

[0011] The power tracking error Decomposing the low-frequency component 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 to 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 to by the torque system;

[0012] S4, based on the dual-stage control architecture designed in S3, designs the kinetic energy utilization coefficient and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0013] S5. Based on the torque reference values ​​generated by S3 and S4, a final torque reference value is generated by the torque controller, and power control is achieved in coordination with the pitch angle controller.

[0014] Optionally, S1 is based on the active power instruction issued by the wind farm control center , calculate the normalized power tracking error and power tracking error variation ;include:

[0015] Under turbulent wind conditions, according to the active power instructions issued by the wind farm control center , calculate the power tracking error , expressed as:

[0016] ;

[0017] in, is the actual output power of the fan unit;

[0018] According to the power tracking error obtained, the sampling period For the interval, calculate the change in power tracking error , expressed as:

[0019] ;

[0020] in, represents the power tracking error at the current moment, is the power tracking error at the previous moment;

[0021] Design Input Scale Factor and , respectively, the power tracking error and power tracking error variation After normalization, it is expressed as:

[0022] ;

[0023] ;

[0024] in, and are the normalized power tracking error and the change in power tracking error, respectively.

[0025] Optionally, a fuzzy controller is designed in S2 based on S1 to dynamically update the filter parameters. ;include:

[0026] The power tracking error and power tracking error variation As the input of the fuzzy controller, the filter parameters As the output of the fuzzy controller, a triangular membership function is used to define linguistic variables, including NB, NS, ZO, PS and PB, to construct input and output fuzzy sets and realize fuzzy processing;

[0027] According to the obtained input and output fuzzy sets, the Sugeno type fuzzy reasoning mechanism is used to establish a fuzzy rule base containing N rules and dynamically adjust the filtering parameters. , expressed as:

[0028] ;

[0029] in, is the output scale factor, and are the weight and output value of the i-th rule, N and are 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.

[0030] Optionally, filter parameters updated in S3 based on S2 , design a two-stage control architecture; including:

[0031] Using the obtained filter parameters , a two-stage control architecture is designed, and the error signal is decomposed into low-frequency and high-frequency components through complementary high-pass and low-pass filters, which are expressed as:

[0032] ;

[0033] ;

[0034] in, represents the low-frequency component, represents the high frequency component, and Denotes complementary high-pass and low-pass filters, designed as and ,in, is the Laplace operator;

[0035] The obtained low-frequency component is responded by the pitch system, and the pitch angle controller is designed using the PI control method, which is expressed as:

[0036] ;

[0037] in, is the pitch angle reference value, and are the proportional and integral gains of the pitch angle controller, respectively

[0038] The obtained high-frequency component is responded by the torque system, and the torque controller is designed using the PI control method, which is expressed as:

[0039] ;

[0040] in, 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.

[0041] Optional, S4 is based on the dual-stage control architecture designed in S3, designs the kinetic energy utilization coefficient, and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0042] Based on the dual-stage architecture, the kinetic energy utilization coefficient is further designed , redefine the speed tracking error , using the kinetic energy stored in the rotor to eliminate the output power and The power deviation between the two is controlled by PI, which is expressed as:

[0043] ;

[0044] in, Indicates 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;

[0045] Among them, the kinetic energy utilization coefficient Designed to:

[0046] ;

[0047] in, is a positive constant, Represents the power tracking error.

[0048] Optionally, in S5, based on the torque reference values ​​generated in S3 and S4, a final torque reference value is generated by a torque controller, and power control is achieved in collaboration with a pitch angle controller; including: the final designed torque controller is expressed as:

[0049] ;

[0050] in, is the comprehensive torque reference value, Indicates the torque reference value based on high frequency components, Indicates the torque reference value based on the speed tracking error.

[0051] To achieve the above-mentioned object, the second aspect of the present application provides a control system for active power of a wind turbine generator set, the control system comprising:

[0052] The power error calculation unit is used to calculate the active power instruction issued by the wind farm control center. , calculate the normalized power tracking error and power tracking error variation ;

[0053] Dynamic adjustment unit, which designs a fuzzy controller based on the calculation unit and dynamically updates the filter parameters :Get the calculation unit and As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets; based on the obtained input and output fuzzy sets, the fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameters. ;

[0054] A frequency domain decomposition unit, wherein the frequency domain decomposition unit is based on the filter parameters updated by the dynamic adjustment unit , design a two-stage control architecture: the power tracking error Decomposing the low-frequency component 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 to 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 to by the torque system;

[0055] Kinetic energy regulation unit, which is based on a two-stage control architecture designed by the frequency domain decomposition unit, designs the kinetic energy utilization coefficient, and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0056] The torque cooperative control unit generates a final torque reference value through a torque controller based on the torque reference value generated by the frequency domain decomposition unit and the kinetic energy regulation unit, and cooperates with the pitch angle controller to achieve power control.

[0057] To achieve the above-mentioned purpose, the third aspect of the present application provides a wind turbine active power control device, comprising a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method described above is implemented.

[0058] To achieve the above-mentioned objectives, the fourth 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.

[0059] After adopting the above technical solution, this application has the following beneficial effects compared with the prior art:

[0060] In response to the current situation where traditional PAC methods fail to effectively coordinate the differences in dynamic response characteristics between the pitch system and the torque system in power tracking, resulting in a significant increase in the load on the pitch system, this application designs an active power control method for wind turbines, constructs a two-stage control architecture based on adaptive filtering parameters, decomposes the error signal into high-frequency and low-frequency components, which are responded to by the torque system and the pitch system respectively, to achieve coordination between different actuators and improve power tracking performance; in response to the current situation where traditional PAC methods do not make sufficient use of the rotor kinetic energy in power tracking, a kinetic energy utilization coefficient is designed and the speed tracking error is redefined to achieve efficient utilization of the rotor kinetic energy in power tracking and effectively reduce the load on the pitch system.

[0061] 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

[0062] 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.

[0063] In the attached figure:

[0064] Figure 1 Schematic diagram of the steps of the method for controlling the active power of a wind turbine generator set in this specific implementation manner;

[0065] Figure 2 is a design flow chart of a method for controlling active power of a wind turbine generator set in this specific implementation manner;

[0066] Figure 3 This is a system framework diagram of the method for controlling the active power of a wind turbine generator set in this specific implementation manner;

[0067] Figure 4 This is a diagram of actual input wind speed of the method for controlling active power of a wind turbine generator system in this specific embodiment;

[0068] Figure 5 A comparison chart of the wind wheel speeds of the traditional PAC method and the method in this specific embodiment;

[0069] Figure 6 A comparison diagram of pitch angles between the conventional PAC method and the method in this embodiment;

[0070] Figure 7: is a comparison diagram of the pitch angle change rate of the traditional PAC method and the method in this specific embodiment;

[0071] Figure 8 This is a comparison chart of power generation between the traditional PAC method and the method in this specific embodiment;

[0072] Figure 9 A comparison diagram of electromagnetic torques between the conventional PAC method and the method in this specific embodiment;

[0073] Figure 10 A comparison diagram of the lateral moment at the blade root of the traditional PAC method and the method in this specific embodiment;

[0074] Figure 11 A comparison diagram of the longitudinal moment at the blade root of the traditional PAC method and the method in this specific embodiment;

[0075] Figure 12 is the membership function of the normalized power tracking error in this specific implementation manner;

[0076] Figure 13 is the membership function of the normalized power tracking error variation in this specific implementation. DETAILED DESCRIPTION

[0077] 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.

[0078] This embodiment provides a method for controlling the active power of a wind turbine generator system, comprising the following steps:

[0079] 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 power tracking error variation ;

[0080] S2, design a fuzzy controller based on S1 and dynamically update the filter parameters :

[0081] S1 obtains and As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets; based on the obtained input and output fuzzy sets, the fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameters. ;

[0082] S3, filter parameters updated based on S2 , design a two-stage control architecture:

[0083] The power tracking error Decomposing the low-frequency component 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 to 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 to by the torque system;

[0084] S4, based on the dual-stage control architecture designed in S3, designs the kinetic energy utilization coefficient and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0085] S5. Based on the torque reference values ​​generated by S3 and S4, a final torque reference value is generated by the torque controller, and power control is achieved in coordination with the pitch angle controller.

[0086] It should be noted that the execution subject of the visual question answering method in this embodiment is a wind turbine active power 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 active power control method in this embodiment by taking the execution subject as an example of a server.

[0087] 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.

[0088] In one achievable implementation, in S1, according to the active power instruction issued by the wind farm control center , calculate the normalized power tracking error and power tracking error variation ;include:

[0089] Under turbulent wind conditions, a turbulent wind with a duration of 600s and an average wind speed of 11m / s is used as the input of the OpenFAST wind power technology simulation platform. According to the active power command issued by the wind farm control center, , calculate the power tracking error , expressed as:

[0090] ;

[0091] in, is the actual output power of the fan unit;

[0092] According to the power tracking error , with a sampling period of For the interval, calculate the change in power tracking error , expressed as:

[0093] ;

[0094] in, represents the power tracking error at the current moment, is the power tracking error at the previous moment;

[0095] Design Input Scale Factor and , respectively, the power tracking error and power tracking error variation After normalization, it is expressed as:

[0096] ;

[0097] ;

[0098] in, and are the normalized power tracking error and the change in power tracking error, respectively.

[0099] In a feasible implementation, S2 designs a fuzzy controller based on S1 to dynamically update the filter parameters ;include:

[0100] The power tracking error and power tracking error variation As the input of the fuzzy controller, the filter parameters As the output of the fuzzy controller, a triangular membership function is used to define linguistic variables, including NB, NS, ZO, PS and PB, to construct input and output fuzzy sets and realize fuzzy processing;

[0101] According to the obtained input and output fuzzy sets, the Sugeno type fuzzy reasoning mechanism is used to establish a fuzzy rule base containing N rules and dynamically adjust the filtering parameters. , expressed as:

[0102] ;

[0103] in, is the output scale factor, and Respectively The weights and output values ​​of the rules, N and are 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.

[0104] In practical applications, the fuzzy rule base established in S2 is shown in Table 1:

[0105] Table 1: Fuzzy rule base

[0106]

[0107] Specifically, the fuzzy rule base is expressed as:

[0108] Rule 1: If is NB and is NB then is PS;

[0109] Rule 2: If is NB and is NS then is PS;

[0110] Rule 3: If is NS and is NB then is ZO;

[0111] Rule i: If is PB and is PB then is NS;

[0112] Where 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 the normalized power tracking error and the change in power tracking error, respectively.

[0113] In a feasible implementation, considering the difference in dynamic response characteristics between the wind turbine pitch system and the torque system actuator, the filter parameters updated in S3 based on S2 are , design a two-stage control architecture; including:

[0114] Using the obtained filter parameters , a two-stage control architecture is designed, and the error signal is decomposed into low-frequency and high-frequency components through complementary high-pass and low-pass filters, which are expressed as:

[0115] ;

[0116] ;

[0117] in, represents the low-frequency component, represents the high frequency component, and Denotes complementary high-pass and low-pass filters, designed as and ,in, is the Laplace operator;

[0118] The obtained low-frequency component is responded by the pitch system, and the pitch angle controller is designed using the PI control method, which is expressed as:

[0119] ;

[0120] in, is the pitch angle reference value, and are the proportional and integral gains of the pitch angle controller, respectively

[0121] The obtained high-frequency component is responded by the torque system, and the torque controller is designed using the PI control method, which is expressed as:

[0122] ;

[0123] in, 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.

[0124] In a feasible implementation, S4 is based on the two-stage control architecture designed in S3, designs the kinetic energy utilization coefficient, and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0125] Based on the dual-stage architecture, the kinetic energy utilization coefficient is further designed , redefine the speed tracking error , using the kinetic energy stored in the rotor to eliminate the output power and The power deviation between the two is controlled by PI, which is expressed as:

[0126] ;

[0127] in, Indicates 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;

[0128] Among them, the kinetic energy utilization coefficient Designed to:

[0129] ;

[0130] in, is a positive constant, Represents the power tracking error.

[0131] In one feasible implementation, in S5, based on the torque reference values ​​generated in S3 and S4, a final torque reference value is generated by a torque controller, and power control is achieved in coordination with a pitch angle controller; including: the final designed torque controller is expressed as:

[0132] ;

[0133] in, is the comprehensive torque reference value, Indicates the torque reference value based on high frequency components, Indicates the torque reference value based on the speed tracking error.

[0134] It should be noted that, under the designed two-stage control architecture and kinetic energy utilization coefficient, this embodiment can effectively coordinate the differences in dynamic response characteristics of the variable pitch system and the torque system, and make full use of the rotor kinetic energy to eliminate power deviation. It is simple and easy to implement, and can reduce the load of the variable pitch system while improving the power tracking performance.

[0135] This embodiment uses the OpenFAST simulation platform, a wind power technology development software, to verify the effectiveness of the method of this embodiment. This embodiment uses a 5MW three-blade horizontal axis variable speed wind turbine model, and the main parameters are shown in Table 2:

[0136] Table 2: Main parameters of the 5MW three-blade horizontal axis variable speed wind turbine model

[0137]

[0138] To quantitatively compare the control effectiveness of the wind turbine active power control method proposed in this embodiment with the traditional PAC method, it is necessary to explain the evaluation index of the pitch angle load. In actual operation, frequent pitch angle adjustment will significantly increase the mechanical load of the variable pitch system and shorten the service life of key components of the unit. Therefore, this embodiment introduces pitch fatigue (PF) as an evaluation index of the pitch system, expressed as:

[0139] ;

[0140] in, Represents the pitch angle of the wind turbine generator set, in units of , is the total operating time of the unit, k represents the current moment, Represents the pitch angle at the next moment, so the unit of the above index is , which reflects the period of time during which the unit is in operation The average change in pitch angle per second within seconds can better evaluate the load condition of the pitch system. At the same time, in order to more comprehensively evaluate the effectiveness of the proposed method, this embodiment also uses the damage equivalent load (DEL) as an indicator to measure the magnitude of the transmission chain and blade root load.

[0141] Figure 6 The figure is a comparison chart of pitch angle. According to calculation, the total amount of pitch angle adjustment of the traditional PAC method is 218.07 The total amount of pitch angle adjustment in the method proposed in this embodiment is 140.94 , a decrease of 35.37%.

[0142] Figure 7 The figure below is a comparison of the pitch angle change rate. After calculation, the pitch system load evaluation index PF of the traditional PAC method is 0.3635. The pitch system load evaluation index PF of the method proposed in this embodiment is 0.2349 , a decrease of 35.37%.

[0143] Figure 8 The power generation comparison chart is shown in Figure 2. Calculations show that the RMS power deviation of the traditional PAC method is 58.11 kW, while the RMS power deviation of the method proposed in this embodiment is 49.99 kW, a reduction of 13.97%.

[0144] Figure 9The electromagnetic torque comparison chart is shown in Figure 2. Calculations show that the DEL of the transmission chain using the traditional PAC method is 5.704 kN-m, while the DEL of the transmission chain using the method proposed in this embodiment is 5.604 kN-m, a decrease of 1.8%.

[0145] Figure 10 Figure 2 shows a comparison of blade root lateral moments. Calculated DEL for the conventional PAC method at the blade root lateral moment is 8665.22 kN-m. The equivalent fatigue load for the proposed method at the blade root lateral moment is 8642.65 kN-m, a 0.26% reduction.

[0146] Figure 11 The figure below shows a comparison of the longitudinal moment at the blade root. The calculated DEL for the traditional PAC method at the blade root longitudinal moment is 7505.75 kN-m. The equivalent fatigue load for the proposed method at the blade root longitudinal moment is 7183.65 kN-m, a 4.29% reduction.

[0147] Figure 12 and Figure 13 are the normalized power tracking errors and power tracking error variation Schematic diagram of the membership function.

[0148] Based on the same inventive concept, the present application also provides a wind turbine active power control system, the control system comprising:

[0149] Calculation unit, power error calculation unit is used to calculate the active power instruction issued by the wind farm control center , calculate the normalized power tracking error and power tracking error variation ;

[0150] Dynamic adjustment unit, which designs fuzzy controller based on calculation unit and dynamically updates filter parameters :Get the calculation unit and As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets; based on the obtained input and output fuzzy sets, the fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameters. ;

[0151] Frequency domain decomposition unit, the frequency domain decomposition unit is based on the filter parameters updated by the dynamic adjustment unit , design a two-stage control architecture: the power tracking error Decompose into low-frequency components and high-frequency components, design a pitch angle controller for the low-frequency components, generate a pitch angle reference value, and the pitch system responds; design a torque controller for the high-frequency components, generate a torque reference value based on the high-frequency components, and the torque system responds;

[0152] Kinetic energy regulation unit, the kinetic energy regulation unit is based on the dual-stage control architecture designed by the frequency domain decomposition unit, designs the kinetic energy utilization coefficient, and redefines the speed tracking error The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the actual output power and active power command. Power deviation between

[0153] The torque cooperative control unit generates a final torque reference value through a torque controller based on the torque reference value generated by the frequency domain decomposition unit and the kinetic energy regulation unit, and cooperates with the pitch angle controller to achieve power control.

[0154] Based on the same inventive concept, the present application also provides a device for controlling the active power of a wind turbine generator set, comprising a processor and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, the method for controlling the active power of the wind turbine generator set as described above is implemented.

[0155] 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 for controlling the active power of a wind turbine generator set as described above is implemented.

[0156] 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.

[0157] 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.

[0158] 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 method for controlling active power of a wind turbine generator system, characterized in that: The following steps are involved: S1. Under turbulent wind conditions, according to the active power instruction P issued by the wind farm control center ref , calculate the normalized power tracking error e pref and power tracking error variation Δe pref ; S2. Design a fuzzy controller based on S1 and dynamically update the filter parameter τ: The e obtained by S1 pref and Δe pref As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets. Based on the obtained input and output fuzzy sets, a fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameter τ. S3, based on the updated filter parameter τ in S2, designs a two-stage control architecture: The power tracking error e p Decomposing the low-frequency component 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 to 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 to by the torque system; S4, based on the dual-stage control architecture designed in S3, designs the kinetic energy utilization coefficient and redefines the speed tracking error e r The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the difference between the actual output power and the active power command P ref Power deviation between S5. Based on the torque reference values ​​generated by S3 and S4, a final torque reference value is generated by the torque controller, and power control is achieved in coordination with the pitch angle controller.

2. The method according to claim 1, characterized in that In S1, the active power command P is issued by the wind farm control center. ref , calculate the normalized power tracking error e pref and power tracking error variation Δe pref ; include: Under turbulent wind conditions, according to the active power command P issued by the wind farm control center, ref , calculate the power tracking error e p , expressed as: e p =P g -P ref ; Among them, P g is the actual output power of the fan unit; According to the obtained power tracking error e p , with a sampling period of T s For the interval, calculate the power tracking error change Δe p , expressed as: Δe p =e p (k)-e q (k-1); Among them, e p (k) represents the power tracking error at the current moment, e p (k-1) is the power tracking error at the previous moment; Design Input Scale Factor and The power tracking error e is obtained respectively p and power tracking error variation Δe p After normalization, it is expressed as: Among them, e pref and Δe pref are the normalized power tracking error and the change in power tracking error, respectively.

3. The method according to claim 1, characterized in that In S2, a fuzzy controller is designed based on S1 to dynamically update the filter parameter τ; this includes: The power tracking error e pref and power tracking error variation Δe pref As the input of the fuzzy controller, the filter parameter τ is used as the output of the fuzzy controller, and the triangular membership function is used to define the language variables, which 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, to construct the input and output fuzzy sets and realize fuzzification processing; According to the obtained input and output fuzzy sets, the Sugeno type fuzzy inference mechanism is used to establish a fuzzy rule base containing N rules, and the filtering parameter τ is dynamically adjusted, which is expressed as: Among them, K τ is the output scale factor, W i and D i are the weight and output value of the i-th rule, N and i are the total number of rules in the fuzzy rule base and the index number of the current rule, respectively. ref is the reference value of the filtering parameter.

4. The method according to claim 1, wherein In S3, based on the updated filter parameter τ in S2, a two-stage control architecture is designed, including: Using the obtained filter parameter τ, a two-stage control architecture is designed to decompose the error signal into low-frequency and high-frequency components through complementary high-pass and low-pass filters, which are expressed as: e low =e p G l (s) yes high =e p G h (s) Among them, e low Represents the low-frequency component, e high Represents high-frequency components, G h (s) and G l (s) represents a complementary high-pass filter and a low-pass filter, which are designed as and Where s is the Laplace operator; The obtained low-frequency component is responded by the pitch system, and the pitch angle controller is designed using the PI control method, which is expressed as: β ref =K p1 is low +K i1 ∫e low 4 Among them, β ref is the pitch angle reference value, K p1 and K d1 are the proportional and integral gains of the pitch angle controller, respectively The obtained high-frequency component is responded by the torque system, and the torque controller is designed using the PI control method, which is expressed as: T g1ref =K p2 e high +K l2 ∫e high ; Among them, T e1ref is the torque reference value based on high frequency components, K p2 and K 12 are the proportional and integral gains of the torque controller based on the high frequency component.

5. The method according to claim 3, characterized in that S4 is based on the dual-stage control architecture designed in S3, designs the kinetic energy utilization coefficient, and redefines the speed tracking error e r The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the difference between the actual output power and the active power command P ref Power deviation between Based on the dual-stage architecture, the kinetic energy utilization coefficient K is further designed and the speed tracking error e is redefined. r , using the kinetic energy stored in the rotor to eliminate the difference between the output power and P ref The power deviation between the two is controlled by PI, which is expressed as: T g2ref =K p3 e r +K I3 ∫e r ; Among them, e r =ω r -Kω opt represents the speed tracking error, ω r represents the rotor speed, Indicates the optimal speed, K opt is the control gain coefficient, T g2ref is the torque reference value based on the speed tracking error, K p3 and K I3 are the proportional and integral gains of the torque controller based on the speed tracking error; Among them, the kinetic energy utilization coefficient K is designed as: in, is a positive constant, e p Represents the power tracking error.

6. The method according to claim 1, characterized in that In S5, based on the torque reference values ​​generated by S3 and S4, the final torque reference value is generated by the torque controller, and the power control is realized in coordination with the pitch angle controller. The final designed torque controller is expressed as: T gref =T g1ref +T g2ref ; Among them, T gref is the comprehensive torque reference value, Tx 1ref Represents the torque reference value based on high frequency components, T g2ref Indicates the torque reference value based on the speed tracking error.

7. The control system of active power of wind turbine is characterized by: The control system includes: The power error calculation unit is used to calculate the active power instruction P issued by the wind farm control center. ref , calculate the normalized power tracking error s pref and power tracking error variation Δe pref ; The dynamic adjustment unit designs a fuzzy controller based on the calculation unit and dynamically updates the filter parameter τ: the e obtained by the calculation unit is pref and Δe pref As the input of the fuzzy controller, the triangular membership function is used to define the language variables and construct the input and output fuzzy sets. Based on the obtained input and output fuzzy sets, a fuzzy rule base is established through the fuzzy reasoning mechanism to dynamically adjust the filter parameter τ. The frequency domain decomposition unit designs a two-stage control architecture based on the filter parameter τ updated by the dynamic adjustment unit: the power tracking error e p Decomposing the low-frequency component 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 to 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 to by the torque system; Kinetic energy regulation unit, which is based on a two-stage control architecture designed by the frequency domain decomposition unit, designs the kinetic energy utilization coefficient, and redefines the speed tracking error e r The torque controller generates a torque reference value based on the speed tracking error, and uses the kinetic energy stored in the rotor to eliminate the difference between the actual output power and the active power command P ref Power deviation between The torque cooperative control unit generates a final torque reference value through a torque controller based on the torque reference value generated by the frequency domain decomposition unit and the kinetic energy regulation unit, and cooperates with the pitch angle controller to achieve power control.

8. A wind turbine active power control device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

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 6.

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