Fan power smoothing method and device based on non-linear barrier and error compensation

Abstract

This application discloses a wind turbine power smoothing method and device based on nonlinear potential barrier and error compensation, belonging to the field of wind power generation control technology. The technical solution is as follows: A dynamic model of a permanent magnet direct-drive wind power generation system is established; a second-order filter is used to calculate the basic active power reference command, while simultaneously obtaining the maximum power point tracking reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time; a rotor kinetic energy constraint control strategy based on a nonlinear potential barrier function is used to generate a corrected reference power, and a smoothed reference speed command is calculated accordingly; a torque disturbance rejection control algorithm based on an error accumulation compensation observer is used to actively estimate aerodynamic torque disturbances; through the coordination of front-end command correction and back-end active disturbance rejection, comprehensive power smoothing of the wind turbine under complex turbulent conditions is achieved, effectively solving at least the instability of traditional kinetic energy filtering control during sudden wind speed drops and the mechanical shock caused by forced speed switching.

Description

Technical Field

[0001] This application relates to the field of wind power generation control technology, and in particular to a wind turbine power smoothing method and apparatus based on nonlinear potential barrier and error compensation. Background Technology

[0002] With the large-scale development and high-proportion grid connection of wind power generation, the grid connection stability and output power quality of wind turbine units face increasingly stringent requirements. Due to the inherent intermittency and randomness of wind energy, the output power of wind turbine units fluctuates significantly under complex turbulent conditions. This not only reduces the power quality of the grid but also causes frequency deviations and accelerates fatigue damage to key components of the unit. Traditional maximum power point tracking (MPPT) control causes the output power to closely follow wind speed changes, resulting in drastic fluctuations in grid-connected power. Therefore, developing effective wind turbine power smoothing control strategies is urgently needed to improve the grid connection reliability and operational safety of wind power generation systems. Currently, existing technologies for wind turbine power smoothing control under low wind speed and complex turbulent conditions have the following drawbacks: First, simple rotor kinetic energy second-order filtering control carries the risk of stalling when wind speed drops sharply, while traditional fixed lower limit switching strategies can cause mechanical shocks and limit smoothing capabilities; second, traditional PI control and conventional ESO are difficult to achieve zero-steady-error accurate observation and rapid feedforward compensation of aerodynamic torque disturbances, resulting in poor dynamic disturbance rejection performance and robustness of the speed loop.

[0003] Therefore, a control method is needed that can balance power smoothing and system operation stability. This method should be able to smoothly constrain rotor kinetic energy to avoid mechanical shock when the fan speed drops below the MPPT curve, and effectively eliminate the effects of complex aerodynamic torque disturbances. Summary of the Invention

[0004] The embodiments of this application provide a wind turbine power smoothing method and apparatus based on nonlinear potential barrier and error compensation, so as to at least have the technical effect of avoiding the risk of unit stall and mechanical shock when the wind speed drops suddenly.

[0005] To address the aforementioned technical problems, this application provides a wind turbine power smoothing method based on nonlinear potential barriers and error compensation, comprising:

[0006] S1. Establish the dynamic model of the permanent magnet direct-drive wind power generation system;

[0007] S2 uses a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time.

[0008] S3 adopts a rotor kinetic energy constraint control strategy based on nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function. The hyperbolic tangent smoothing function is used to smoothly transform the repulsive force into a compensation term, actively reducing the base active power reference command, and calculating the smooth reference speed command accordingly to avoid mechanical shock and boundary chattering caused by forced switching.

[0009] S4. The torque disturbance rejection control algorithm based on the error accumulation compensation observer is adopted to perform active estimation of aerodynamic torque disturbance: the speed estimation error and error integral term are defined, the error accumulation compensation observer EASO state equation is constructed, and the error integral term is used to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and the total aerodynamic torque disturbance of the fan is estimated.

[0010] S5. Using the deviation between the smooth reference speed command generated in step S3 and the actual speed as the input of the PI controller, a virtual torque command is generated. The total aerodynamic torque disturbance estimated by the observer in step S4 is used to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control under complex turbulent conditions.

[0011] This application also requests a wind turbine power smoothing device based on nonlinear barrier and error compensation, comprising:

[0012] The acquisition unit is configured to acquire various parameters of the permanent magnet direct-drive wind power generation system.

[0013] The first processing unit is configured to use a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time.

[0014] The second processing unit is configured to adopt a rotor kinetic energy constraint control strategy based on a nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function, and the repulsive force is smoothly converted into a compensation term using a hyperbolic tangent smoothing function to actively reduce the base active power reference command, and a smooth reference speed command is calculated accordingly.

[0015] The third processing unit is configured to use a torque disturbance rejection control algorithm based on an error accumulation compensation observer to perform active estimation of aerodynamic torque disturbance: define the speed estimation error and error integral term, construct the error accumulation compensation observer EASO state equation, use the error integral term to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and estimate the total aerodynamic torque disturbance of the fan.

[0016] The active compensation unit is configured to use the deviation between the generated smooth reference speed command and the actual speed as the input of the PI controller to generate a virtual torque command. It then uses the total aerodynamic torque disturbance estimated by the observer to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control.

[0017] This application has the following beneficial effects:

[0018] This application presents a wind turbine power smoothing method based on nonlinear potential barriers and error compensation. By constructing a control architecture that coordinates a nonlinear potential barrier rotor kinetic energy constraint strategy with an error accumulation compensation observer, it achieves full-process optimization from smooth generation of power reference commands to active compensation for torque disturbances. This method addresses the shortcomings of traditional second-order rotor kinetic energy filtering control, which is prone to instability during sudden wind speed drops, and the mechanical shock and boundary chattering caused by the fixed speed lower limit forced switching strategy. It introduces rotor kinetic energy constraint control technology based on a nonlinear potential barrier function, and an error accumulation compensation observer technology designed to overcome the insufficient disturbance rejection capability of conventional speed loop controllers. This achieves efficient smoothing of the output power of direct-drive permanent magnet wind turbines and stable system operation control. By combining the active smoothing correction of the reference power command through front-end nonlinear barrier constraints with the precise feedforward compensation of aerodynamic torque disturbances by the back-end observer, this invention not only effectively avoids the risk of unit stall and mechanical shock when wind speed drops sharply, but also significantly improves the dynamic response speed and robustness of the system to complex aerodynamic disturbances. Furthermore, while maintaining high wind energy capture efficiency, it greatly reduces the grid-connected power fluctuation and transmission chain fatigue load of the unit, providing a reliable solution for high-quality and stable grid connection of wind power generation under complex turbulent conditions. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0020] Figure 1 A flowchart illustrating a method provided in an embodiment of this application;

[0021] Figure 2 A block diagram of rotor kinetic energy constraint control based on a nonlinear barrier function is provided in an embodiment of this application;

[0022] Figure 3 A block diagram of torque disturbance rejection control based on an error accumulation compensation observer provided in an embodiment of this application;

[0023] Figure 4 A turbulent wind speed diagram provided in one embodiment of this application;

[0024] Figure 5The figure shows the simulation results of turbulent wind speed provided for an embodiment of this application.

[0025] Figure 6 This is a structural block diagram of a wind turbine power smoothing device based on nonlinear barrier and error compensation, provided as an embodiment of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] With the large-scale development and high grid connection rate of wind power generation, the grid connection stability and output power quality of wind turbines face increasingly stringent requirements. Due to the inherent intermittency and randomness of wind energy, the output power of wind turbines fluctuates significantly under complex turbulent conditions. This not only reduces the power quality of the grid but also causes frequency deviations and accelerates fatigue damage to key components of the turbine. Traditional maximum power point tracking (MPPT) control causes the output power to closely follow wind speed changes, resulting in drastic fluctuations in grid-connected power. Therefore, developing effective wind turbine power smoothing control strategies is urgently needed to improve the grid connection reliability and operational safety of wind power generation systems.

[0028] In the research of wind turbine power smoothing control, existing technologies mainly revolve around two aspects: rotor kinetic energy control and speed loop disturbance rejection control. In the rotor kinetic energy control stage, utilizing the wind turbine's huge rotational inertia to absorb or release kinetic energy to smooth power is a low-cost and fast-response method. To improve the smoothing effect, existing technologies often introduce second-order digital filters (SOFs) to process power commands. However, second-order filters introduce phase lag, making it difficult for reference power commands to respond promptly when wind speed drops rapidly, easily leading to excessive drops in wind turbine speed or even stall and instability. To prevent instability, the traditional approach is to set a fixed lower speed limit for forced mode switching, but this results in discontinuous speed derivatives, causing severe mechanical shocks to the wind turbine drivetrain and prematurely limiting the speed regulation range, thus weakening the wind turbine's power smoothing potential.

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] This invention provides a wind turbine power smoothing method based on nonlinear potential barriers and error compensation, such as... Figure 1 As shown, it includes the following steps:

[0031] S1. Establish the dynamic model of the permanent magnet direct-drive wind power generation system;

[0032] S2 uses a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time.

[0033] S3 adopts a rotor kinetic energy constraint control strategy based on nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function. The hyperbolic tangent smoothing function is used to smoothly transform the repulsive force into a compensation term, actively reducing the base active power reference command, and calculating the smooth reference speed command accordingly to avoid mechanical shock and boundary chattering caused by forced switching.

[0034] S4. The torque disturbance rejection control algorithm based on the error accumulation compensation observer is adopted to perform active estimation of aerodynamic torque disturbance: the speed estimation error and error integral term are defined, the error accumulation compensation observer EASO state equation is constructed, and the error integral term is used to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and the total aerodynamic torque disturbance of the fan is estimated.

[0035] S5. Using the deviation between the smooth reference speed command generated in step S3 and the actual speed as the input of the PI controller, a virtual torque command is generated. The total aerodynamic torque disturbance estimated by the observer in step S4 is used to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control under complex turbulent conditions.

[0036] It should be noted that a collaborative control architecture integrating nonlinear barrier rotor kinetic energy constraints and error accumulation compensation observers is proposed. By combining a front-end reference power active correction mechanism based on nonlinear barrier with a back-end active disturbance rejection control law based on error accumulation compensation, the entire process optimization from power command smoothing to electromagnetic torque execution is achieved.

[0037] In one embodiment, in step S1, the mechanical power P captured by the wind turbine in the permanent magnet direct-drive wind power generation system w and mechanical torque T w It can be represented as:

[0038]

[0039] In equation (1), air density, The radius of the wind turbine blades. For wind speed, The wind energy utilization coefficient, For the tip speed ratio, The pitch angle is the propeller angle. The influence coefficient of wind speed change rate. d is the rotor angular velocity, t is time, and d is the differential operator;

[0040] Wind energy utilization coefficient It is a key parameter reflecting the aerodynamic conversion efficiency of a wind turbine, and its value depends on the tip speed ratio. and propeller pitch angle The nonlinear coupling relationship is expressed as:

[0041]

[0042] In equation (2), As an intermediate variable, is the fitting coefficient, and E is the Euler number.

[0043] In one embodiment, step S2 specifically involves calculating the basic active power reference command P using a rotor kinetic energy control algorithm incorporating a second-order digital filter. SOF :

[0044]

[0045] In equation (3), P opt To obtain the optimal output power through MPPT control, G SOF Let be the second-order filter transfer function, where a and b are the pole parameters of the filter, c is the zero and gain adjustment parameters of the filter, and s is the Laplace operator.

[0046] Simultaneously obtain MPPT reference speed And calculate the deviation between the actual rotor speed and the MPPT reference speed. for:

[0047]

[0048] In one embodiment, in step S3, a modified reference speed is generated using a rotor kinetic energy constraint control strategy based on a nonlinear potential barrier function. The process is as follows:

[0049] S31, Define the barrier Lyapunov function:

[0050]

[0051] In equation (5), K p For barrier gain, and K p >0.

[0052] The gradient of the barrier function is:

[0053]

[0054] When the speed is lower At this time, the barrier function generates a repulsive force, which is transformed into a compensation term through the control law, actively reducing the reference power and thus guiding the speed to recover.

[0055] S32, introduce a hyperbolic tangent smoothing function to construct the barrier compensation power P. comp :

[0056]

[0057] In equation (7), tanh() is the hyperbolic tangent function. To activate the boundary steepness coefficient.

[0058] S33, obtain the corrected reference power P ref for:

[0059]

[0060] S34, according to equation (8), the smooth reference speed is calculated using the rotor kinetic energy. for:

[0061]

[0062] In equation (9), J is the moment of inertia.

[0063] It should be noted that this paper proposes a rotor kinetic energy constraint control strategy based on a nonlinear barrier function. When the actual turbine speed drops below the MPPT speed curve, a repulsive force is generated by introducing a barrier Lyapunov function, and this force is smoothly transformed into a power compensation term using a hyperbolic tangent function, actively reducing the reference power. This mechanism can guide the speed to recover smoothly, avoiding the mechanical shock and boundary chattering caused by the traditional forced switching of the fixed speed lower limit strategy, and overcoming the phase lag and stall risks caused by relying solely on a second-order filter. Thus, while ensuring that the unit does not deviate from the stable operating region, it maximizes the power smoothing potential of the turbine rotor kinetic energy.

[0064] In one embodiment, the specific implementation process of the Error Accumulation Compensation Observer (EASO) in step S4 is as follows:

[0065] S41, define the total system disturbance f, the velocity estimation error e, and the state variables x1 and x2 as follows:

[0066]

[0067] In equation (10), for The observed values.

[0068] S42, Construct the state equation for the error accumulation compensation observer:

[0069]

[0070] In equation (11), for The observed values, They are respectively The derivative, T is a constant. e For electromagnetic torque, For observer gain, This is the error integral term.

[0071] S42, the observer gain is tuned using the bandwidth parameterization method:

[0072]

[0073] In equation (12), This represents the observer bandwidth.

[0074] It should be noted that the torque disturbance rejection control strategy based on the error accumulation compensation observer is used here. By introducing an integral term for the velocity estimation error into the traditional extended state observer, an error accumulation compensation observer (EASO) is constructed. This design eliminates the unavoidable steady-state estimation error of conventional observers when facing constant or low-frequency aerodynamic disturbances, achieving zero steady-state error and accurate estimation and real-time feedforward compensation of the total aerodynamic torque disturbance experienced by the wind turbine. This completely changes the hysteresis of the passive integral disturbance rejection of traditional PI controllers, significantly improving the dynamic disturbance rejection capability and compensation accuracy of the velocity loop against complex turbulent time-varying disturbances.

[0075] In one embodiment, in step S5, a q-axis current reference command i is generated by combining speed command optimization and torque feedforward compensation. q ref :

[0076]

[0077] In equation (13), u0 represents the actual rotational speed and the reference rotational speed. The deviation is tuned by a PI controller to obtain a virtual torque command, where p is the number of pole pairs. It is a magnetic flux.

[0078] The following is a detailed explanation of this method through a specific example.

[0079] Based on the control strategy (NBC-EASO) adopted according to this invention, wind turbine power output simulation is performed, and the wind turbine simulation parameters used are as follows: , , , , , Rated wind speed 10.5 m / s, rated power 6 MW. Adopting... Figure 4 The turbulent wind shown is simulated and compared with filtered control (VFS) and robust model predictive control (RMPC), and the results are as follows: Figure 5 (a) shows the power output, Figure 5 The rotor speed shown in (b) and Figure 5 (c) shows the aerodynamic torque.

[0080] Depend on Figure 5 As can be seen, under complex turbulent conditions, this invention achieves significant smoothing of power output and effective suppression of torque disturbances through the coordinated control of nonlinear potential barrier rotor kinetic energy constraint and error accumulation compensation observer, and exhibits excellent stability recovery capability when the speed drops. When the wind turbine rotor speed drops below the maximum power point tracking (MPPT) curve, the nonlinear potential barrier constraint can smoothly and actively reduce the reference power, avoiding the risk of system stall and the mechanical shock caused by hard switching.

[0081] Figure 5 (a) shows a comparison of the output power of three control methods under turbulent wind conditions: Although the Filtered Filter Control (VFS) and Robust Model Predictive Control (RMPC) have certain adjustment capabilities, they still have significant power spikes and deep drops when the wind speed changes drastically; while the output power curve of the method proposed in this invention (NBC-EASO) is the most stable, effectively smoothing out peaks and filling valleys, with the smallest fluctuation amplitude. Figure 5 (b) indicates that the present invention allows the fan to operate over a wide range of speeds to fully absorb and release rotor kinetic energy. Figure 5 (c) The local amplification comparison of the aerodynamic torque further verifies that the present invention can significantly weaken high-frequency torque spikes and effectively reduce the mechanical fatigue load of the transmission chain by performing active feedforward compensation through the error accumulation compensation observer.

[0082] The following describes a wind turbine power smoothing device based on nonlinear barrier and error compensation provided in an embodiment of this application.

[0083] Figure 6 This is a structural block diagram of a wind turbine power smoothing device based on nonlinear barrier and error compensation, provided according to an embodiment of this application.

[0084] like Figure 6 As shown, the device includes:

[0085] The acquisition unit is configured to acquire various parameters of the permanent magnet direct-drive wind power generation system.

[0086] The first processing unit is configured to use a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time.

[0087] The second processing unit is configured to adopt a rotor kinetic energy constraint control strategy based on a nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function, and the repulsive force is smoothly converted into a compensation term using a hyperbolic tangent smoothing function to actively reduce the base active power reference command, and a smooth reference speed command is calculated accordingly.

[0088] The third processing unit is configured to use a torque disturbance rejection control algorithm based on an error accumulation compensation observer to perform active estimation of aerodynamic torque disturbance: define the speed estimation error and error integral term, construct the error accumulation compensation observer EASO state equation, use the error integral term to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and estimate the total aerodynamic torque disturbance of the fan.

[0089] The active compensation unit is configured to use the deviation between the generated smooth reference speed command and the actual speed as the input of the PI controller to generate a virtual torque command. It then uses the total aerodynamic torque disturbance estimated by the observer to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control.

[0090] The aforementioned wind turbine power smoothing device based on nonlinear potential barrier and error compensation includes a processor and a memory. The acquisition unit, first processing unit, second processing unit, third processing unit, and active compensation unit are all stored as program units in the memory. The processor executes these program units stored in the memory to achieve the corresponding functions. All of the above modules are located in the same processor; alternatively, the modules may be located in different processors in any combination.

[0091] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and adjusting kernel parameters can address the low accuracy and efficiency of existing coarse registration methods for single-feature roadways.

[0092] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0093] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the aforementioned wind turbine power smoothing method based on nonlinear barrier and error compensation.

[0094] This invention provides a processor for running a program, wherein the program executes the aforementioned wind turbine power smoothing method based on nonlinear potential barrier and error compensation.

[0095] This application also provides an electronic device, which includes: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for executing any of the above-described wind turbine power smoothing methods based on nonlinear barrier and error compensation.

[0096] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0097] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0098] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0099] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0100] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0101] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0102] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0103] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0104] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A wind turbine power smoothing method based on nonlinear potential barrier and error compensation, characterized in that, include: S1. Establish the dynamic model of the permanent magnet direct-drive wind power generation system; S2 uses a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time. S3 adopts a rotor kinetic energy constraint control strategy based on nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function. The hyperbolic tangent smoothing function is used to smoothly transform the repulsive force into a compensation term, actively reducing the base active power reference command, and calculating the smooth reference speed command accordingly to avoid mechanical shock and boundary chattering caused by forced switching. S4. The torque disturbance rejection control algorithm based on the error accumulation compensation observer is adopted to perform active estimation of aerodynamic torque disturbance: the speed estimation error and error integral term are defined, the error accumulation compensation observer EASO state equation is constructed, and the error integral term is used to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and the total aerodynamic torque disturbance of the fan is estimated. S5. Using the deviation between the smooth reference speed command generated in step S3 and the actual speed as the input of the PI controller, a virtual torque command is generated. The total aerodynamic torque disturbance estimated by the observer in step S4 is used to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control.

2. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 1, characterized in that, In step S1, the mechanical power P captured by the wind turbine in the permanent magnet direct-drive wind power generation system w and mechanical torque T w Represented as: In equation (1), air density, The radius of the wind turbine blades. For wind speed, The wind energy utilization coefficient, For the tip speed ratio, The pitch angle is the propeller angle. The influence coefficient of wind speed change rate. d is the rotor angular velocity, t is time, and d is the differential operator; Wind energy utilization coefficient It is a key parameter reflecting the aerodynamic conversion efficiency of a wind turbine, and its value depends on the tip speed ratio. and propeller pitch angle The nonlinear coupling relationship is expressed as: In equation (2), As an intermediate variable, is the fitting coefficient, and E is the Euler number.

3. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 2, characterized in that: Specifically, step S2 involves calculating the basic active power reference command P using a rotor kinetic energy control algorithm incorporating a second-order digital filter. SOF : In equation (3), P opt To obtain the optimal output power through MPPT control, G SOF Let be the second-order filter transfer function, where a and b are the pole parameters of the filter, c is the zero and gain adjustment parameters of the filter, and s is the Laplace operator. Simultaneously obtain MPPT reference speed And calculate the deviation between the actual rotor speed and the MPPT reference speed. for:

4. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 3, characterized in that: In step S3, a rotor kinetic energy constraint control strategy based on a nonlinear potential barrier function is used to generate a corrected reference speed. The process is as follows: S31, Define the barrier Lyapunov function: In equation (5), K p For barrier gain, and K p >0. The gradient of the barrier function is: When the speed is lower At this time, the barrier function generates a repulsive force, which is transformed into a compensation term through the control law, actively reducing the reference power and thus guiding the speed to recover. S32, introduce a hyperbolic tangent smoothing function to construct the barrier compensation power P. comp : In equation (7), tanh() is the hyperbolic tangent function. To activate the boundary steepness coefficient. S33, obtain the corrected reference power P ref for: S34, according to equation (8), the smooth reference speed is calculated using the rotor kinetic energy. for: In equation (9), J is the moment of inertia.

5. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 4, characterized in that: In step S4, the specific implementation process of the Error Accumulation Compensation Observer (EASO) is as follows: S41, define the total system disturbance f, the velocity estimation error e, and the state variables x1 and x2 as follows: In equation (10), for The observed value is given by the formula. S42, Construct the state equation for the error accumulation compensation observer: In equation (11), for The observed values, They are respectively The derivative, T is a constant. e For electromagnetic torque, For observer gain, This is the error integral term. S42, the observer gain is tuned using the bandwidth parameterization method: In equation (12), This represents the observer bandwidth.

6. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 5, characterized in that: In step S5, the q-axis current reference command i is generated by combining speed command optimization and torque feedforward compensation. q ref : In equation (13), u0 represents the actual rotational speed and the reference rotational speed. The deviation is tuned by a PI controller to obtain a virtual torque command, where p is the number of pole pairs. It is a magnetic flux.

7. The wind turbine power smoothing method based on nonlinear potential barrier and error compensation according to claim 1, characterized in that... In step S1, a dynamic model of the permanent magnet direct-drive wind power generation system is established, wherein...

8. A wind turbine power smoothing device based on nonlinear potential barrier and error compensation, characterized in that, include: The acquisition unit is configured to acquire various parameters of the permanent magnet direct-drive wind power generation system. The first processing unit is configured to use a second-order digital filter to calculate the basic active power reference command, while obtaining the maximum power point tracking (MPPT) reference speed and calculating the deviation between the actual speed and the MPPT reference speed in real time. The second processing unit is configured to adopt a rotor kinetic energy constraint control strategy based on a nonlinear barrier function to generate a corrected reference power: when the actual speed of the wind turbine drops below the MPPT reference speed, a repulsive force is generated through the barrier function, and the repulsive force is smoothly converted into a compensation term using a hyperbolic tangent smoothing function to actively reduce the base active power reference command, and a smooth reference speed command is calculated accordingly. The third processing unit is configured to use a torque disturbance rejection control algorithm based on an error accumulation compensation observer to perform active estimation of aerodynamic torque disturbance: define the speed estimation error and error integral term, construct the error accumulation compensation observer EASO state equation, use the error integral term to eliminate the steady-state error caused by constant or low-frequency disturbance in real time, and estimate the total aerodynamic torque disturbance of the fan. The active compensation unit is configured to use the deviation between the generated smooth reference speed command and the actual speed as the input of the PI controller to generate a virtual torque command. It then uses the total aerodynamic torque disturbance estimated by the observer to actively feed forward compensate for the command, generating the final electromagnetic torque reference command and q-axis current reference command, thereby achieving smooth power control.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program is executed, it controls the device containing the computer-readable storage medium to perform the wind turbine power smoothing method based on nonlinear barrier and error compensation as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, It includes: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for performing the wind turbine power smoothing method based on nonlinear barrier and error compensation as described in any one of claims 1 to 7.

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