Variable pitch control method, device, equipment and product for floating type wind turbine generator

Abstract

The invention relates to the technical field of wind power generation, and discloses a variable-pitch control method, device, equipment and product for a floating type wind turbine generator. A wind turbine generator model is constructed by comprehensively considering multiple factors such as aerodynamics, hydrodynamics and mooring dynamics, and a gain scheduling control model is introduced into a preset PI control method; the method can adapt to different working conditions, effectively overcomes the limitation of the traditional PID control in the complex dynamic environment of the floating wind turbine generator, reduces the power fluctuation, and reduces the structure resonance risk. A preset platform pitching value is introduced into expert PID control, and Kohmann coordinate transformation is combined, so that the negative damping problem of a unified variable-pitch floating type fan is solved, and accurate distribution of control signals is realized. And finally, through the control combination of unified variable pitch and independent variable pitch, the pitching amplitude is reduced, the blade load is reduced, the stability and safety of the floating type wind turbine generator are remarkably improved, and reliable operation of the generator is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, specifically to a method, device, equipment, and product for pitch control of a floating wind turbine. Background Technology

[0002] With the accelerating global energy transition, offshore wind power, as a crucial component of clean energy, is expanding from nearshore fixed foundations to deep-sea floating technologies. Traditional fixed wind turbines are limited by water depth and seabed conditions, making them suitable only for waters less than 60 meters deep. However, over 80% of global offshore wind energy resources are located in deep-sea areas with depths exceeding 60 meters. Floating wind turbines, combined with mooring systems and floating platforms, can overcome these depth limitations, enabling the development of deep-sea wind energy.

[0003] As the core of wind turbine power regulation and safety protection, the pitch system faces multiple challenges in deep-sea scenarios:

[0004] (1) Dynamic coupling interference: The floating platform generates six degrees of freedom motion under the action of waves, which causes changes in the relative wind speed of the impeller and produces a "negative damping effect". However, the traditional pitch control algorithm is difficult to respond accurately to such complex dynamic changes, which can easily cause power fluctuations and structural resonance, and in severe cases, even safety risks.

[0005] (1) Complex load action: Floating wind turbines need to withstand multi-source coupled loads of wind, waves and currents. Under frequent load changes, the pitch bearings and drive mechanism must maintain high reliability while dealing with the significantly increased difficulty in predicting mechanical fatigue life and lightweight design.

[0006] (3) Multi-objective collaborative optimization: The pitch system needs to be collaboratively optimized with platform motion control, mooring design, etc., which involves deep coupling of aerodynamics, hydrodynamics and control theory.

[0007] Therefore, researching pitch control strategies for floating wind turbines to better control offshore wind turbines and ensure their safety and stability is currently a key focus and challenge. Summary of the Invention

[0008] In view of this, the present invention provides a method, device, equipment and product for pitch control of floating wind turbine units, so as to solve the problem that traditional pitch control strategies are difficult to guarantee the safety and stability of the unit.

[0009] In a first aspect, the present invention provides a pitch control method for a floating wind turbine, the method comprising:

[0010] A model of the floating wind turbine to be controlled is obtained, constructed using aerodynamic, hydrodynamic, and mooring dynamic factors. Based on the model, a gain-based scheduling control model is used to adjust a preset PI control method and determine the uniform pitch angle of the floating wind turbine. Based on a preset platform roll value, the deviation pitch angle of each blade in the floating wind turbine is calculated using expert PID control and Coleman coordinate transformation. Pitch control is then applied to the floating wind turbine according to the uniform pitch angle and the deviation pitch angle of each blade, yielding the pitch control result.

[0011] The pitch control method for floating wind turbines provided by this invention constructs a wind turbine model of the floating wind turbine to be controlled by comprehensively considering factors such as aerodynamics, hydrodynamics, and mooring dynamics, which can fully reflect the actual operating conditions of the floating wind turbine. Furthermore, based on the wind turbine model, a gain scheduling control model is used to adjust a preset PI control method to determine a uniform pitch angle, which can adapt to different operating conditions and effectively overcome the limitations of traditional PID control in the complex dynamic environment of floating wind turbines, reducing power fluctuations and lowering the risk of structural resonance. Furthermore, expert PID control can effectively handle the nonlinearity of floating wind turbines. Simultaneously, the introduction of a preset platform roll value in expert PID control solves the "negative damping problem" that occurs in floating wind turbines with uniform pitch control. Furthermore, precise allocation of control signals can be achieved through Coleman coordinate transformation, enabling the blades to respond more flexibly and accurately to platform motion and complex loads. Finally, pitch control was implemented based on a unified pitch angle and the deviation pitch angle of each blade, achieving a combination of unified pitch control and independent pitch control. This reduced the pitch amplitude, lowered the blade load, significantly improved the stability and safety of the floating wind turbine, and ensured the reliable operation of the unit.

[0012] In one optional implementation, obtaining a model of the floating wind turbine to be controlled includes:

[0013] The aerodynamics of the floating wind turbine to be controlled is modeled to obtain an aerodynamic model; the hydrodynamics of the floating wind turbine to be controlled is modeled based on linear wave theory and potential flow theory to obtain a hydrodynamic model; the mooring dynamics of the floating wind turbine to be controlled are modeled to obtain a mooring model, which includes a catenary mooring system model and a force model; based on the aerodynamic model, hydrodynamic model and mooring model, the wind turbine model is determined.

[0014] The pitch control method for floating wind turbines provided by this invention models the aerodynamics of the floating wind turbine, accurately describing the interaction between the rotor and airflow, and providing an accurate basis for analyzing wind capture, power generation, and aerodynamic torque. Furthermore, a hydrodynamic model is established based on linear wave theory and potential flow theory, considering the effects of waves and ocean currents on the floating platform. This allows for accurate analysis of the platform's motion characteristics and stress conditions in water, helping to assess platform stability and the impact of motion on the wind turbine. Further, by establishing a mooring model including a catenary mooring system model and a force model, the mechanical behavior of the mooring system can be accurately characterized, ensuring a reasonable design of the mooring system and guaranteeing accurate and reliable positioning of the floating wind turbine in complex marine environments. Finally, combining the above three models to determine the wind turbine model comprehensively covers the multi-physics coupling effects during the operation of the floating wind turbine, providing reliable system model support for subsequent control strategy design and optimization.

[0015] In one optional implementation, based on a wind turbine model, a gain scheduling control model is used to adjust a preset PI control method and determine a uniform pitch angle for the floating wind turbine to be controlled, including:

[0016] Based on the wind turbine model, a preset PI control method is used to control the floating wind turbine to be controlled, and the first proportional control parameter and the first integral control parameter are obtained. The first proportional control parameter and the first integral control parameter are adjusted using a gain scheduling control model to obtain the second proportional control parameter and the second integral control parameter. Based on the second proportional control parameter and the second integral control parameter, the uniform pitch angle of the floating wind turbine to be controlled is determined.

[0017] The pitch control method for floating wind turbines provided by this invention, based on a wind turbine model, uses a preset PI control method to determine the first and second control parameters, initially realizing the control of the floating wind turbine and providing basic parameters for subsequent gain scheduling control. Furthermore, based on the gain scheduling control model, the control parameters can be dynamically adjusted according to different operating conditions, enabling the controller to better adapt to the complex and variable operating conditions of the floating wind turbine, improving control accuracy and robustness. Finally, a unified pitch angle is determined based on the adjusted third and fourth control parameters, providing a more accurate and suitable pitch angle setpoint for unified pitch control of the wind turbine, optimizing power regulation, and reducing the instability risk caused by improper pitch angle. Therefore, by implementing this invention, the limitations of traditional PID control in the complex dynamic environment of floating wind turbines are effectively overcome, power fluctuations are reduced, and the risk of structural resonance is lowered.

[0018] In one optional implementation, based on a wind turbine model, a preset PI control method is used to control the floating wind turbine to be controlled, obtaining a first proportional control parameter and a first integral control parameter, including:

[0019] The control objective is determined based on the wind turbine model; according to the control objective, the first pitch angle relationship is determined using a preset PI control method; the first pitch angle relationship is subjected to a Laplace transform to obtain the second pitch angle relationship; the linearized model of the wind turbine drive chain is obtained, and the motion relationship of the single-degree-of-freedom model of the wind turbine drive is determined based on the linearized model of the wind turbine drive chain; the first proportional control parameter and the first integral control parameter are calculated based on the first pitch angle relationship, the second pitch angle relationship, and the motion relationship.

[0020] The floating wind turbine pitch control method provided by this invention determines the control objective based on a wind turbine model, clarifying the control direction and desired outcome. Furthermore, a first pitch angle relationship is determined using a preset PI control method, and a second pitch angle relationship is obtained through Laplace transform, establishing a mathematical relationship between the pitch angle and system control variables, providing a theoretical basis for accurate calculation of control parameters. Further, a linearized model of the wind turbine drivetrain is obtained and its kinematic relationships are determined, accurately describing the dynamic characteristics of the wind turbine drive system. The influence of factors such as inertia and friction during transmission is considered, providing a more realistic drive system model for calculating control parameters. Finally, the first and second control parameters are calculated by combining the pitch angle relationship and the kinematic relationships, ensuring that the calculation of control parameters is closely integrated with the actual dynamic characteristics and control requirements of the wind turbine, improving parameter accuracy and control effectiveness.

[0021] In one optional implementation, based on a preset platform pitch value, and using an expert PID control method and a Coleman coordinate transformation method, the deviation pitch angle of each blade in the floating wind turbine to be controlled is calculated, including:

[0022] The floating wind turbine under control is controlled using an expert PID control method to obtain the initial pitch and yaw pitch angles. Based on the preset platform pitch value, the initial pitch and yaw pitch angles are controlled using the expert PID control method to obtain the target pitch and yaw pitch angles. Based on the target pitch and yaw pitch angles, the deviation pitch angle of each blade in the floating wind turbine under control is obtained by processing the target pitch and yaw pitch angles using the Coleman coordinate transformation method.

[0023] The pitch control method for floating wind turbines provided by this invention utilizes expert PID control to obtain the initial pitch and yaw pitch angles, effectively addressing the large nonlinearity issues of floating wind turbines. Furthermore, the influence of platform roll motion on the turbine is incorporated into the control strategy, making the pitch angle adjustment more closely aligned with actual operating conditions and improving the control's targeting and effectiveness. Finally, the target pitch angle is processed through Coleman coordinate transformation to obtain the deviation pitch angle for each blade, achieving precise allocation of control signals according to blade azimuth angles. This allows each blade to independently adjust its pitch angle based on its position and stress conditions, effectively reducing uneven blade loads and improving turbine stability.

[0024] In one alternative implementation, the gain scheduling control model is expressed as the following relation:

[0025] K p_β =K p *η(β)

[0026] K i_β =K i *η(β)

[0027] In the formula: K p_β Indicates the second proportional control parameter; K p Indicates the first proportional control parameter; K i_β Indicates the second integral control parameter; K i η(β) represents the first integral control parameter; η(β) represents the correction coefficient; β represents the pitch angle.

[0028] The floating wind turbine pitch control method provided by this invention dynamically adjusts the proportional control parameters and integral control parameters according to the pitch angle, enabling the controller to automatically optimize the control parameters as the pitch angle changes. This maintains good control performance under different pitch angle conditions, improving control accuracy and adaptability.

[0029] In a second aspect, the present invention provides a floating wind turbine pitch control device, the device comprising:

[0030] The module consists of four parts: an acquisition module for acquiring the model of the floating wind turbine to be controlled, constructed using aerodynamic, hydrodynamic, and mooring dynamic factors; an adjustment and determination module for adjusting a preset PI control method based on the wind turbine model and using a gain scheduling control model to determine the uniform pitch angle of the floating wind turbine; a calculation module for calculating the deviation pitch angle of each blade in the floating wind turbine based on a preset platform pitch value, processed by an expert PID control method and a Coleman coordinate transformation method; and a control module for performing pitch control on the floating wind turbine according to the uniform pitch angle and the deviation pitch angle of each blade, obtaining the pitch control result.

[0031] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the floating wind turbine pitch control method of the first aspect or any corresponding embodiment described above.

[0032] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the floating wind turbine pitch control method of the first aspect or any corresponding embodiment described above.

[0033] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the floating wind turbine pitch control method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0035] Figure 1 This is a schematic flowchart of a floating wind turbine pitch control method according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic flowchart of another floating wind turbine pitch control method according to an embodiment of the present invention;

[0037] Figure 3 This is a flowchart illustrating another floating wind turbine pitch control method according to an embodiment of the present invention.

[0038] Figure 4 This is a flowchart illustrating the independent pitch control method for floating wind turbines that incorporates platform feedback according to an embodiment of the present invention.

[0039] Figure 5 This is a schematic diagram of a mooring system according to an embodiment of the present invention;

[0040] Figure 6 This is a schematic diagram of the expert PID control according to an embodiment of the present invention;

[0041] Figure 7 This is a schematic diagram of the control flow of the integrated control model according to an embodiment of the present invention;

[0042] Figure 8 This is a schematic diagram comparing the control results according to an embodiment of the present invention;

[0043] Figure 9 This is a structural block diagram of a floating wind turbine pitch control device according to an embodiment of the present invention;

[0044] Figure 10 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of 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 some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] This invention provides a pitch control method for floating wind turbines. By introducing a gain scheduling control model into unified pitch control and expert control and preset platform roll values ​​into independent pitch control, the stability and safety of floating wind turbines are significantly improved, ensuring reliable operation of the units.

[0047] According to an embodiment of the present invention, a method for pitch control of a floating wind turbine is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0048] This embodiment provides a pitch control method for floating wind turbines, which can be used in electronic devices such as computers, mobile phones, and tablets. Figure 1This is a flowchart of a floating wind turbine pitch control method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0049] Step S101: Obtain the wind turbine model of the floating wind turbine to be controlled.

[0050] The wind turbine model is constructed using the aerodynamic, hydrodynamic, and mooring dynamic factors corresponding to the floating wind turbine to be controlled.

[0051] Specifically, by comprehensively considering the aerodynamics, hydrodynamics, and mooring dynamics of the floating wind turbine to be controlled, a model of the floating wind turbine to be controlled is constructed, which can fully reflect the actual operating conditions of the floating wind turbine.

[0052] Aerodynamics refers to the dynamics of airflow acting on a floating wind turbine. Specifically, wind acts on the turbine blades, and through the blades' unique shape and angle, creates a pressure difference in the airflow, which in turn generates an aerodynamic torque that drives the blades to rotate. Furthermore, factors such as wind speed, wind direction, and air density affect the magnitude and direction of the aerodynamic force. Simultaneously, blade surface roughness and airflow turbulence also influence aerodynamic characteristics (such as turbine power output and load distribution).

[0053] Hydrodynamics refers to the forces exerted by ocean fluids (mainly waves and currents) on floating wind turbine platforms. Specifically, the heave, pitch, and roll motions generated by waves, as well as the drag force of ocean currents, cause the platform to exhibit six degrees of freedom of motion.

[0054] Mooring dynamics refers to the mechanical behavior of a floating wind turbine platform constrained by a mooring system.

[0055] Step S102: Based on the wind turbine model, the preset PI control method is adjusted using the gain scheduling control model, and the uniform pitch angle of the floating wind turbine to be controlled is determined.

[0056] The gain scheduling control model represents a technical model capable of dynamically adjusting controller parameters based on system operating conditions. Specifically, during the operation of a floating wind turbine, operating conditions constantly change due to the marine environment and the turbine's own state, such as wind speed fluctuations and platform sway. The gain scheduling control model can monitor these changes in real time and then automatically adjust the controller parameters according to pre-set rules or algorithms. In this way, the controller can better adapt to the dynamic characteristics of the wind turbine, improving the stability and accuracy of the control effect.

[0057] Furthermore, PI control stands for Proportional and Integral control. In wind turbine control, proportional control can respond quickly based on the magnitude of the current error; the larger the error, the stronger the control effect, thus adjusting the pitch angle in a timely manner. Integral control is used to accumulate errors and eliminate the steady-state error of the system by continuously accumulating the errors, making the adjustment of the pitch angle more precise.

[0058] Specifically, in complex systems like floating wind turbines, fixed-parameter PI control struggles to maintain consistent performance under various operating conditions. Therefore, this embodiment utilizes a gain-dispatch control model to adjust the preset PI control method, dynamically changing the proportional and integral coefficients in the PI controller based on the real-time operating conditions of the wind turbine. When wind speed changes drastically, the proportional coefficient is adjusted appropriately to enhance rapid response; when steady-state errors exist, the integral coefficient is optimized to accelerate error elimination.

[0059] Furthermore, by introducing a pre-defined PI control method based on a gain scheduling control model to control the floating wind turbine, a corresponding uniform pitch angle can be determined. This means that all blades in the floating wind turbine are adjusted using the same pitch angle, ensuring that each blade of the floating wind turbine works in coordination under the same operating conditions. This makes the aerodynamic forces on the turbine impeller more balanced, thereby optimizing the power output of the turbine, improving the stability and reliability of the wind turbine, and ensuring its safe and efficient operation in complex marine environments.

[0060] Furthermore, by introducing a pre-defined PI control method based on a gain scheduling control model to determine a uniform pitch angle, it can adapt to different operating conditions, effectively overcome the limitations of traditional PID control in the complex dynamic environment of floating wind turbines, reduce power fluctuations, and lower the risk of structural resonance.

[0061] Step S103: Based on the preset platform pitch value, the deviation pitch angle of each blade in the floating wind turbine to be controlled is calculated through expert PID control method and Coleman coordinate transformation method.

[0062] Among them, the expert PID control method represents a control strategy that combines expert systems with traditional PID control. Expert systems are intelligent systems built upon the knowledge and experience of domain experts.

[0063] Furthermore, in expert PID control, the expert system can adjust the parameters (proportional coefficient, integral coefficient, and derivative coefficient) of the PID controller online according to pre-set rules and knowledge, based on information such as the system's operating status, environmental factors, and control objectives.

[0064] Furthermore, when the system experiences significant disturbances or changes in operating conditions, the expert system can use its knowledge base to determine the current situation and adjust the PID parameters, enabling the controller to better adapt to the dynamic characteristics of the system and improve control accuracy and robustness.

[0065] Furthermore, the Coleman coordinate transformation method represents a coordinate transformation method for converting physical quantities in a stationary coordinate system to a rotating coordinate system. In wind turbine control, it is often used to handle problems related to blade orientation.

[0066] Furthermore, the deviation pitch angle of each blade is used to reflect the additional angle adjustment required for each blade relative to the uniform pitch angle.

[0067] Specifically, in actual operation, floating wind turbines operate in complex environments with strong nonlinear characteristics, making it difficult for traditional fixed-parameter PID control to achieve ideal results. Therefore, introducing an expert system to optimize PID control can effectively address the nonlinearity issues of floating wind turbines.

[0068] In some optional implementations, when the system is running, the expert system can obtain corresponding rules from the rule base based on the current operating status of the platform (such as pitch speed, acceleration, etc.), environmental conditions (wind speed, wave height, etc.) and preset platform pitch values, and dynamically adjust the parameters of the PID controller so that the controller can more effectively cope with complex situations and obtain more suitable control signals.

[0069] Furthermore, the floating platform experiences pitching motion under wave action, causing periodic changes in the blades' relative wind speed. Traditional pitch control methods struggle to compensate for the resulting asymmetric loads. Therefore, this embodiment incorporates a preset platform pitch value into the expert PID control, ensuring the control target operates within a defined range to achieve platform stability and power output stability.

[0070] Furthermore, the Coleman coordinate transformation method enables precise allocation of control signals, allowing the blades to respond more flexibly and accurately to platform motion and complex loads.

[0071] Step S104: Based on the uniform pitch angle and the deviation pitch angle of each blade, pitch control is performed on the floating wind turbine to obtain the pitch control result.

[0072] Specifically, by superimposing the obtained uniform pitch angle β and the deviation pitch angles (Δβ1, Δβ2, Δβ3) of each blade, the final actual pitch angle of each blade can be obtained. By superimposing, the overall control requirements and individual blade differences are taken into account, enabling each blade to be precisely adjusted according to the actual situation.

[0073] Furthermore, after receiving the actual pitch angle signal of each blade, the pitch system of the floating wind turbine can drive the blade to rotate through actuators such as motors, reducers, and transmission mechanisms, and adjust the blade to the corresponding actual pitch angle position.

[0074] By combining unified pitch control with independent pitch control, the blade pitch angle is precisely adjusted, changing the angle between the blade and the airflow, reducing the pitch amplitude, lowering the blade load, significantly improving the stability and safety of the floating wind turbine, and ensuring the reliable operation of the unit.

[0075] The floating wind turbine pitch control method provided in this embodiment constructs a wind turbine model of the floating wind turbine to be controlled by comprehensively considering aerodynamics, hydrodynamics, and mooring dynamics, which can fully reflect the actual operating conditions of the floating wind turbine. Furthermore, based on the wind turbine model, a gain scheduling control model is used to adjust a preset PI control method to determine a uniform pitch angle, which can adapt to different operating conditions and effectively overcome the limitations of traditional PID control in the complex dynamic environment of floating wind turbines, reducing power fluctuations and lowering the risk of structural resonance. Furthermore, expert PID control can effectively handle the large nonlinearity problem of floating wind turbines. Simultaneously, the introduction of a preset platform roll value in expert PID control solves the "negative damping problem" that occurs in floating wind turbines with uniform pitch. Furthermore, precise allocation of control signals can be achieved through Coleman coordinate transformation, enabling the blades to respond more flexibly and accurately to platform motion and complex loads. Finally, pitch control was implemented based on a unified pitch angle and the deviation pitch angle of each blade, achieving a combination of unified pitch control and independent pitch control. This reduced the pitch amplitude, lowered the blade load, significantly improved the stability and safety of the floating wind turbine, and ensured the reliable operation of the unit.

[0076] This embodiment provides a pitch control method for floating wind turbines, which can be used in electronic devices such as computers, mobile phones, and tablets. Figure 2 This is a flowchart of a floating wind turbine pitch control method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0077] Step S201: Obtain the wind turbine model of the floating wind turbine to be controlled.

[0078] Specifically, step S201 includes:

[0079] Step S2011: Model the aerodynamics of the floating wind turbine to be controlled to obtain the aerodynamic model.

[0080] Specifically, based on the blade element momentum theory, the blade can be divided into countless tiny blade element segments (length dr) along its length. Each blade element segment can then be analyzed separately to study its aerodynamic characteristics under relative wind speed. By integrating the aerodynamic forces of all blade element segments, the aerodynamic characteristics of the entire blade and the wind turbine impeller can be obtained.

[0081] First, take the blade element segment of length dr, which is subjected to the aerodynamic force generated by the relative wind speed. It can be decomposed into a lift force L and a drag force D, as shown in the following equations (1) and (2):

[0082] dL=0.5cρC l w 2 dr (1)

[0083] dD=0.5cρC d w 2 dr (2)

[0084] In the formula: c represents the chord length of the blade element segment, i.e., the width of the blade perpendicular to the airflow direction; ρ represents the air density; C l represents the lift coefficient, whose value depends on the selected airfoil and the corresponding angle of attack, and can be obtained from the airfoil's aerodynamic characteristic curve; w represents the wind speed; C d The drag coefficient can be obtained from the aerodynamic characteristic curve of the angle of attack corresponding to the selected airfoil.

[0085] Furthermore, by decomposing lift and drag, the axial aerodynamic force F in the blade element section can be obtained. x and tangential aerodynamic force F y The relationships are shown in equations (3) and (4) respectively:

[0086]

[0087] Furthermore, by simultaneously solving the above relations (1) to (4), we can obtain:

[0088]

[0089] Secondly, the force on the blade element is only related to the change in momentum of the area swept by the airflow through the impeller. The thrust dF of the airflow acting on the swept area of ​​the blade element is shown in the following relationship (7):

[0090]

[0091] In the formula: v i denoted by tangential velocity of blade rotation; r represents the distance from the blade element segment to the center of blade rotation; a represents the axial induction factor, used to characterize the degree of change in the axial velocity of the incoming airflow due to the presence of the blade.

[0092] Furthermore, the torque dM of the airflow acting on the swept area of ​​the blade element is expressed by angular momentum, as shown in the following relationship (8):

[0093]

[0094] In the formula: Ω represents the angular velocity of the blade rotation; a ′ This represents the tangential induction factor, used to reflect the tangential variation of the incoming air velocity.

[0095] Finally, assuming the number of wind turbine blades is n, and combining the above aerodynamic formula with the formula for airflow action, we can obtain:

[0096]

[0097] Among them, the above-mentioned equation (9) is used to express the relationship between the impeller aerodynamic force and the change in airflow momentum in the axial direction; the above-mentioned equation (10) is used to express the relationship between the impeller aerodynamic force and the change in airflow angular momentum in the tangential direction.

[0098] By deriving and combining the above formulas, we can complete the aerodynamic modeling of the floating wind turbine and obtain the corresponding aerodynamic model, namely the above relations (9) and (10).

[0099] Step S2012: Based on linear wave theory and potential flow theory, the hydrodynamics of the floating wind turbine to be controlled is modeled to obtain a hydrodynamic model.

[0100] Specifically, dynamic models of large-scale marine structures in the deep sea can be established based on linear wave theory and potential flow theory.

[0101] Furthermore, for the wave force problem of large-scale structures, a hydrodynamic model is established using potential flow theory:

[0102] (1) Diffraction Load: When the floating platform is stationary, the incident wave generates a diffraction load by circling or being dispersed by the platform. Using the wave spectrum defined by the national standard to describe the wave, the wave height ζ(t) can be expressed as the following equation (11):

[0103]

[0104] In the formula: W(ω) represents the Fourier transform of Gaussian white noise; S JS (ω) represents the wave spectrum; ω represents the angular frequency; t represents time.

[0105] Furthermore, the diffraction load F can be calculated using the following relationship (12). waves :

[0106]

[0107] In the formula: X i (ω,β a ) represents the complex value of the unit wave force experienced by the floating platform; β a Indicates the angle of incidence of the wave.

[0108] (2) Radiation load: Without considering the influence of the incident wave, the force exerted on the floating platform by the radiation wave generated when the floating platform is in multi-degree-of-freedom motion is defined as the radiation load. During its propagation, it will continuously affect the motion of the platform. The motion of the object will be affected by the motion state of the previous moment. Therefore, the radiation effect has a memory effect, as shown in the following relationship (13):

[0109]

[0110] In the formula: F r Indicates radiation load; K ij τ represents the wave radiation delay matrix, used to reflect the hydrodynamics of the platform's motion in mode i caused by a unit pulse signal in the j-direction; τ represents the delay time. Indicates wave speed.

[0111] (3) Hydrostatic effect: This is mainly reflected in the buoyancy of the floating platform in calm ocean and the hydrostatic restoring force when the floating platform shifts position, as shown in the following relationship (14):

[0112] F h =ρ 水 gV0δ 13 +C ij q j (14)

[0113] In the formula: F h ρ represents hydrostatic force; 水 The density of seawater is represented by δ; g represents the acceleration due to gravity; V0 represents the volume of water displaced by the floating platform when it is at rest; δ 13 Represents the Krone function; ρ 水 gV0δ 13 Represents Archimedes' buoyancy; C ij Represents the still water recovery stiffness matrix; q j This indicates the offset displacement.

[0114] Furthermore, by diffraction load F waves Radiation load F r hydrostatic force F h By combining these equations, the hydrodynamic loads of a large-scale floating platform calculated based on potential flow theory can be obtained using the following relationship (15), and the hydrodynamic model can be established:

[0115] FHyd =F waves +F r +F h (15)

[0116] In the formula: F Hyd This indicates hydrodynamic load.

[0117] Step S2013: Model the mooring dynamics of the floating wind turbine to be controlled to obtain the mooring model.

[0118] The mooring model includes a catenary mooring system model and a force model.

[0119] Specifically, the catenary mooring system is connected at one end to a floating platform and at the other end to an anchor point on the seabed. In a static state, the mooring rope in the middle is slack, and the restoring force of the catenary mooring system mainly depends on the weight of the rope itself.

[0120] Furthermore, disregarding the bending moment and torque of the mooring cable, i.e., assuming that any section only bears tensile force, for any arc-shaped micro-segment of the mooring cable at any position (x,y), a differential equation can be established based on its stress condition, i.e., satisfying the following relationship (16):

[0121]

[0122] In the formula: H represents the horizontal force on a small segment. Since the entire mooring cable is in horizontal equilibrium, the magnitude of the horizontal force at each point is H; W ′ This represents the weight of a unit length of mooring cable in seawater under tension.

[0123] Furthermore, when the mooring cable is not under stress, let the weight per unit length of the mooring cable in seawater be W, and the axial stiffness be EA. Then, according to the law of conservation of mass, the weight per unit length W′ under tension can be calculated using the following relationship (17):

[0124]

[0125] In the formula: T represents the tension on the micro segment, which can be calculated using the following relationship (18):

[0126]

[0127] Furthermore, combining the above relations (16) to (18), we can obtain the parametric equation satisfied at any position (x,y) of the system, as shown in the following relation (19):

[0128]

[0129] In the formula: u represents the parameter in the parametric equation; α and β represent the constant terms in the parametric equation.

[0130] By deriving and combining the above formulas, we can complete the modeling of the mooring dynamics of floating wind turbines and obtain the corresponding catenary mooring system model.

[0131] Furthermore, based on the force equilibrium conditions in the horizontal and vertical directions, we can obtain:

[0132]

[0133] In the formula: H A V represents the force in the horizontal direction. A The vertical force indicates the force applied; L represents the original length of the cable when it is not under force.

[0134] Furthermore, mooring tension can be calculated in different cases:

[0135] (1) When V>WL, the mooring line has no bottom section, and the mooring tension can be calculated by the following relationship (21):

[0136]

[0137] In the formula: l and h represent variables related to mooring tension, used to jointly characterize mooring tension;

[0138] (2) When V≤WL, due to the presence of the seabed, part of the mooring cable will lie flat on the seabed, forming a bottom-lying section. In this case, the above relationship (22) needs to be modified when calculating the mooring cable tension, and the following modified expression is obtained:

[0139]

[0140] In the formula: L B Indicates the length coefficient of the lying bottom segment; C B This represents the coefficient of friction on the seabed.

[0141] By deriving and combining the above formulas, we can complete the modeling of the mooring dynamics of the floating wind turbine and obtain the corresponding force model.

[0142] Step S2014: Determine the wind turbine model based on the aerodynamic model, hydrodynamic model, and mooring model.

[0143] Specifically, by combining aerodynamic, hydrodynamic, and mooring models to form a model of the floating wind turbine to be controlled, the multi-physics coupling effect during the operation of the floating wind turbine can be fully covered, thereby comprehensively reflecting the actual operating conditions of the floating wind turbine and providing reliable system model support for subsequent control strategy design and optimization.

[0144] Step S202: Based on the wind turbine model, the preset PI control method is adjusted using the gain scheduling control model, and the uniform pitch angle of the floating wind turbine to be controlled is determined.

[0145] Specifically, step S202 includes:

[0146] Step S2021: Based on the wind turbine model, the floating wind turbine to be controlled is controlled using a preset PI control method to obtain the first proportional control parameter and the first integral control parameter.

[0147] Specifically, based on the wind turbine model, the first and second control parameters were determined using a preset PI control method, which initially realized the control of the floating wind turbine and provided basic parameters for subsequent gain scheduling control.

[0148] In some optional implementations, step S2021 above includes:

[0149] Step a1: Determine the control objective based on the wind turbine model.

[0150] Step a2: Determine the first pitch angle relationship using a preset PI control method based on the control objective.

[0151] Step a3: Perform a Laplace transform on the first pitch angle relationship to obtain the second pitch angle relationship.

[0152] Step a4: Obtain the linearized model of the wind turbine drive chain and determine the kinematic relationship of the single-degree-of-freedom model of the wind turbine drive based on the linearized model of the wind turbine drive chain.

[0153] Step a5: Calculate the first proportional control parameter and the first integral control parameter based on the first pitch angle relationship, the second pitch angle relationship, and the motion relationship.

[0154] Among them, the first pitch angle relationship is used to describe the relationship between the pitch angle adjustment and the speed deviation and PI control parameters; the second pitch angle relationship is used to describe the relationship between the pitch angle adjustment and the speed deviation in the complex frequency domain; the Laplace transform represents an integral transform method that converts a time-domain function into a complex frequency domain function; the wind turbine drive chain linearization model represents a mathematical model obtained after simplifying and approximating the wind turbine drive system.

[0155] Specifically, the wind turbine model integrates aerodynamic, hydrodynamic, and mooring dynamics characteristics. By analyzing this model, considering the wind turbine's operation under different marine environmental conditions such as wind speed, waves, and ocean currents, as well as the wind turbine's own structural and performance characteristics, control objectives can be further determined.

[0156] Furthermore, in this embodiment, for floating wind turbines, the control target is to maintain the output power at the rated value under high wind speeds, so as to avoid damage to the wind turbine due to excessive power and ensure stable and safe operation of the wind turbine.

[0157] Furthermore, the PI controller can adjust the proportional control parameter K. p and integral control parameter K i The control quantity is calculated according to the following formula (23):

[0158]

[0159] In the formula: u(t) represents the output control quantity of the PI controller at time t; e(t) represents the error signal at time t. In the pitch control of wind turbine, e(t) represents the difference ΔΩ between the actual speed and the rated speed of the generator.

[0160] Furthermore, by performing a Laplace transform on the above relation (23) and according to classical control theory, the transfer function G(s) of the system can be obtained as shown in the following relation (24):

[0161] G(s)=U(s) / E(s) (24)

[0162] In the formula: U(s) represents the complex frequency domain variable of the PI controller output control quantity u(t) after Laplace transform. In the pitch control of wind turbine units, it is related to control actions such as pitch angle adjustment. After the system action, it is used to adjust the operating state of the wind turbine, such as controlling the output power to maintain the rated value; E(s) represents the complex frequency domain variable of the error signal e(t) after Laplace transform. It is used to reflect the deviation between the actual operating state of the system and the desired state (rated speed). Then, the controller calculates and outputs the corresponding control quantity based on this deviation signal.

[0163] Furthermore, in wind turbine control, the difference ΔΩ between the actual speed and the rated speed of the generator is related to the pitch angle θ, and thus the first pitch angle relationship can be determined as shown in the following relationship (25):

[0164]

[0165] In the formula: Δθ represents the pitch angle adjustment; N g Indicates the transmission ratio;

[0166] Furthermore, by performing a Laplace transform on the above relation (25), the second pitch angle relation can be obtained, as shown in the following relation (26):

[0167]

[0168] In the formula: Δθ(s) represents the complex frequency domain variable of Δθ after the Laplace transform; ΔΩ(s) represents the complex frequency domain variable of ΔΩ after the Laplace transform.

[0169] Furthermore, by analyzing the structure, mechanical characteristics, and motion laws of the wind turbine drive chain, and considering factors such as the moment of inertia and torque transmission of each component in the drive chain (such as impeller, drive shaft, generator, etc.), a corresponding linearized model of the wind turbine drive chain can be established.

[0170] Furthermore, based on the established linearized model of the wind turbine transmission chain, the wind turbine transmission system can be simplified into a single-degree-of-freedom model. Then, according to Newton's second law (rotational form), considering the aerodynamic torque and generator torque acting on the impeller, as well as the inertia of the transmission system, the following kinematic relationship (27) can be obtained:

[0171]

[0172] in:

[0173]

[0174] In the formula: T a τ represents the aerodynamic torque acting on the impeller. g Indicates motor torque; I rotor I represents the moment of inertia of the rotor. gen Ω0 represents the generator's moment of inertia; I represents the rotor's rated speed. D Indicates the inertia of the transmission system; P represents the derivative of the rotational speed deviation ΔΩ with respect to time, i.e., acceleration; P represents aerodynamic power; Ω represents the angular velocity of the wind turbine rotation; P rate This indicates the rated power.

[0175] Furthermore, by performing Taylor expansions on the aerodynamic torque and generator torque respectively, and combining the above relationships (25) to (29) above the rated wind speed, the equation of motion for the rotor speed can be obtained, as shown in the following relationship (30):

[0176]

[0177] Furthermore, by neglecting the negative damping term in the generator torque control, the first proportional control parameter K can be calculated. p and the first integral control parameter K i The relationships are shown in equations (31) to (32) respectively:

[0178]

[0179] In the formula: Indicates the damping ratio; Indicates the natural frequency; The pitch angle sensitivity reflects the aerodynamic characteristics of the wind turbine rotor and can be determined by wind speed, rotor speed, and pitch angle. Through calculation at different operating points, the pitch angle sensitivity and the pitch angle have an approximately linear relationship, as shown in the following equation (33):

[0180]

[0181] in, This represents the sensitivity when the pitch angle is 0; the pitch angle is β. a The sensitivity is 0.5 times that when the propeller pitch angle is 0.

[0182] Step S2022: Adjust the first proportional control parameter and the first integral control parameter using the gain scheduling control model to obtain the second proportional control parameter and the second integral control parameter.

[0183] The gain scheduling control model is shown in the following equations (34) and (35):

[0184] K p_β =K p *η(β) (34)

[0185] K i_β =K i *η(β) (35)

[0186] In the formula: K p_β Indicates the second proportional control parameter; K i_β η(β) represents the second integral control parameter; η(β) represents the correction coefficient; β represents the pitch angle.

[0187] Specifically, the gain dispatch control model can adjust the first proportional control parameter K based on the operating conditions of the wind turbine (such as pitch angle β) through a correction coefficient η(β). p and the first integral control parameter K i Adjustments were made.

[0188] Step S2023: Determine the uniform pitch angle of the floating wind turbine to be controlled based on the second proportional control parameter and the second integral control parameter.

[0189] Specifically, based on the obtained second proportional control parameter K p_β Second integral control parameter K i_β By combining the current operating status of the wind turbine (such as speed deviation), the control quantity can be calculated through the PI control algorithm, and then the control quantity is finally converted into a unified pitch angle, realizing the unified adjustment of the blade pitch angle of the floating wind turbine, thereby achieving the control objective of maintaining the output power at the rated value.

[0190] Step S203: Based on the preset platform pitch value, and processed using expert PID control and Coleman coordinate transformation methods, calculate the deviation pitch angle of each blade in the floating wind turbine to be controlled. For details, please refer to [link to relevant documentation]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0191] Step S204: Based on the unified pitch angle and the deviation pitch angle of each blade, pitch control is performed on the floating wind turbine to obtain the pitch control result. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0192] The floating wind turbine pitch control method provided in this embodiment models the aerodynamics of the floating wind turbine, accurately describing the interaction between the rotor and airflow, and providing accurate basis for analyzing wind capture, power generation, and aerodynamic torque. Furthermore, a hydrodynamic model is established based on linear wave theory and potential flow theory, considering the effects of waves and ocean currents on the floating platform. This allows for accurate analysis of the platform's motion characteristics and stress conditions in water, helping to assess platform stability and the impact of motion on the wind turbine. Further, by establishing a mooring model including a catenary mooring system model and a force model, the mechanical behavior of the mooring system can be accurately characterized, ensuring a reasonable design of the mooring system and guaranteeing accurate and reliable positioning of the floating wind turbine in complex marine environments. Finally, combining the above three models to determine the wind turbine model comprehensively covers the multi-physics coupling effects during the operation of the floating wind turbine, providing reliable system model support for subsequent control strategy design and optimization. Furthermore, based on the wind turbine model, the first and second control parameters are determined using a preset PI control method, initially realizing the control of the floating wind turbine and providing basic parameters for subsequent gain scheduling control. Furthermore, based on the gain-based scheduling control model, control parameters can be dynamically adjusted according to different operating conditions, enabling the controller to better adapt to the complex and variable operating conditions of floating wind turbines, thus improving control accuracy and robustness. Finally, a unified pitch angle is determined based on the adjusted third and fourth control parameters, providing a more accurate and suitable pitch angle setpoint for unified pitch control of wind turbines, optimizing power regulation, and reducing the instability risk caused by improper pitch angle. Therefore, by implementing this invention, the limitations of traditional PID control in the complex dynamic environment of floating wind turbines are effectively overcome, power fluctuations are reduced, and the risk of structural resonance is lowered.

[0193] This embodiment provides a pitch control method for floating wind turbines, which can be used in electronic devices such as computers, mobile phones, and tablets. Figure 3 This is a flowchart of a floating wind turbine pitch control method according to an embodiment of the present invention, such as... Figure 3As shown, the process includes the following steps:

[0194] Step S301: Obtain the wind turbine model of the floating wind turbine to be controlled. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0195] Step S302: Based on the wind turbine model, the preset PI control method is adjusted using the gain scheduling control model to determine the uniform pitch angle of the floating wind turbine to be controlled. For details, please refer to [link to relevant documentation]. Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0196] Step S303: Based on the preset platform pitch value, the deviation pitch angle of each blade in the floating wind turbine to be controlled is calculated through expert PID control method and Coleman coordinate transformation method.

[0197] Specifically, step S303 includes:

[0198] Step S3031: Use the expert PID control method to control the floating wind turbine to obtain the initial pitch angle and the initial yaw angle.

[0199] First, the stationary coordinate system is converted to a rotating coordinate system using the Coleman coordinate transformation. Therefore, the blade pitch angle can be converted to a quantity in the rotating coordinate system using the Coleman coordinate transformation shown in the following relation (36):

[0200]

[0201] In the formula: ψ1, ψ2, and ψ3 represent the blade azimuth angles. β1, β2, and β3 represent the blade pitch angle; β d β q Blade pitch angle in a rotating coordinate system.

[0202] Furthermore, the bending moment M at the leaf root i The calculation formula is shown in the following relation (37):

[0203] M i =h M v i +k M β i (37)

[0204] Where: β i The pitch angle of blade i; h M and k M The dimensionless coefficients obtained by linearization under steady-state operating conditions are shown in the following equations (38) and (39):

[0205]

[0206] Furthermore, by combining the calculated bending moment at the blade root, the pitching moment M at the hub can be further calculated. pitch With yaw moment M yaw The following relation (40) is shown:

[0207]

[0208] Furthermore, the calculated pitching moment M pitch With yaw moment M yaw The pitch and yaw angles are converted and input as signals to the controller. This conversion can be performed according to a specific mapping relationship determined experimentally or theoretically based on the wind turbine's aerodynamic and structural mechanical characteristics.

[0209] By inputting the pitch and yaw pitch angles as input signals to the controller, the following effects are achieved:

[0210] (1) The controller can precisely adjust the angle of the blades in the two directions according to the current wind speed and wind direction, so that the blades can face the incoming wind in the best posture, thereby improving the efficiency of wind energy to electrical energy conversion and ensuring that the wind turbine can output relatively stable power under various wind speeds.

[0211] Furthermore, in real-world marine environments, wind direction may constantly change, and complex conditions such as turbulence may exist. Inputting pitch and yaw angle signals allows the controller to sense and process these changes in real time, dynamically adjusting the blade angle to reduce power fluctuations caused by complex wind conditions, maintain the stability of wind turbine power output, and improve power generation quality.

[0212] (2) In floating wind turbines, the platform will experience pitching motion due to factors such as waves. Adjusting the pitch and yaw pitch angles can change the magnitude and direction of the aerodynamic forces on the blades, thereby adjusting the overall stress on the wind turbine, offsetting or reducing the additional load on the wind turbine structure caused by the platform pitching, reducing the risk of fatigue damage to components such as blades, hubs, and towers, and extending the service life of the wind turbine.

[0213] Furthermore, by reasonably adjusting the pitch and yaw angles of the blades, the force on the blades can be made more uniform during rotation, reducing unbalanced loads caused by uneven force distribution, avoiding excessive alternating stress on the wind turbine structural components, and ensuring the integrity and safety of the wind turbine structure.

[0214] (3) By using the pitch and yaw pitch angles as input signals, the controller can adjust the wind turbine operating status in a timely manner based on these angle information, respond quickly to external interference, enhance the wind turbine system's anti-interference capability, and maintain the system's stable operation.

[0215] Furthermore, when the wind turbine starts up, stops, or encounters sudden changes in operating conditions, by controlling the pitch and yaw angles of the blades, the dynamic response process of the wind turbine can be optimized, enabling it to quickly and smoothly transition to the new operating state and avoiding severe vibration or unstable operation.

[0216] Secondly, an expert system is introduced to construct a rules database based on the long-term accumulated knowledge and practical operational experience in the offshore wind power field. This rules database can contain control rules and parameter adjustment strategies under different wind speeds, sea states, and wind turbine operating conditions.

[0217] Furthermore, the system can acquire operational status information of the wind turbine, such as platform motion parameters, wind speed, and blade load. Based on this information, the expert system can then adjust the parameters (proportional, integral, and derivative coefficients) of the PID controller online according to pre-set rules and a knowledge base (containing offshore wind power expertise and experience).

[0218] Finally, the adjusted PID controller can calculate the control quantity, i.e. the corresponding initial pitch pitch angle and initial yaw pitch angle, based on the error signal of the current system and the input pitch and yaw pitch angle signals, through the PID control algorithm shown in the above relationship (23).

[0219] The initial pitch and yaw angles are obtained by using the aforementioned expert PID control method, which can effectively handle the large nonlinearity problem of floating wind turbines.

[0220] Step S3032: Based on the preset platform pitch value, the initial pitch angle and initial yaw angle are controlled using an expert PID control method to obtain the target pitch angle and target yaw angle.

[0221] Specifically, the platform's pitch output feedback information, i.e., the preset platform pitch value, can be obtained in the output circuit of the floating wind turbine and transmitted to the independent pitch expert PID controller.

[0222] Furthermore, during the operation of the wind turbine, the expert system monitors various operating parameters of the wind turbine in real time, and dynamically adjusts the PID control parameters based on the deviation between the preset platform pitch value and the set value, according to the rule database.

[0223] Furthermore, the expert PID controller, after parameter dynamic adjustment, calculates the control quantities, namely the target pitch pitch angle and the target yaw pitch angle, based on the input pitch and yaw direction pitch angle signals and the preset platform roll value, using the PID control algorithm shown in the above relationship (23).

[0224] By introducing preset platform pitch values ​​to adjust the initial pitch and yaw pitch angles, the pitch angle adjustment becomes more closely aligned with actual operating conditions, improving the targeting and effectiveness of the control.

[0225] Step S3033: Based on the target pitch angle and the target yaw angle, the deviation pitch angle of each blade in the floating wind turbine to be controlled is obtained by processing the target pitch angle and the target yaw angle using the Coleman coordinate transformation method.

[0226] Specifically, the target pitch angle and target yaw angle of the output expert PID controller can be transformed into the deviation pitch angle of each blade using the Coleman coordinate transformation method, as shown in the following relationship (41):

[0227]

[0228] In the formula: Δβ1, Δβ2, and Δβ3 represent the deviation pitch angle of each blade.

[0229] Step S304: Based on the unified pitch angle and the deviation pitch angle of each blade, pitch control is performed on the floating wind turbine to obtain the pitch control result. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0230] The floating wind turbine pitch control method provided in this embodiment utilizes expert PID control to obtain the initial pitch and yaw pitch angles, effectively addressing the large nonlinearity issues of floating wind turbines. Furthermore, the influence of platform roll motion on the turbine is incorporated into the control strategy, making the pitch angle adjustment more closely match actual operating conditions and improving the control's targeting and effectiveness. Finally, the target pitch angle is processed through Coleman coordinate transformation to obtain the deviation pitch angle for each blade, achieving precise allocation of control signals according to blade azimuth angles. This allows each blade to independently adjust its pitch angle based on its position and stress conditions, effectively reducing uneven blade load and improving turbine stability.

[0231] In one instance, such as Figure 4 As shown, a method for independent pitch control of a floating wind turbine with platform feedback is provided, including the following steps:

[0232] Step S1: Model the aerodynamics of the floating wind turbine. Mainly, use the blade element momentum theory to establish an aerodynamic model for the blades. Unfold the blades and decompose them into several micro-elements. Solve the force of the incoming airflow on each blade element micro-element. After integration, the aerodynamic load acting on the blades can be obtained.

[0233] Step S2: Model the hydrodynamics and mooring dynamics of the floating wind turbine. A dynamic model of the large-scale marine structure of the floating wind turbine in the deep sea is established based on linear wave theory and potential flow theory. For the wave force problem of the large-scale structure, a hydrodynamic model is established using potential flow theory. The hydrodynamic forces mainly include diffraction loads, radiation loads, and hydrostatic loads. A catenary mooring system is selected, such as... Figure 5 As shown, one end is connected to a floating platform, and the other end is tightly connected to an anchor point on the seabed. Under the influence of wind and waves, the mooring system can restrict the movement of the platform, ensuring the stability and safety of the floating wind turbine.

[0234] Step S3: Establish a unified pitch control strategy for the floating wind turbine. Use the difference between the generator's actual speed and rated speed as input, minimizing the deviation to ensure optimal power control of the wind turbine. At high wind speeds, the blades increase the pitch angle to reduce the turbine rotor speed, thereby reducing the rotor load. PI control is used to control the pitch angle.

[0235] Step S4: Using the load coordinate transformation method, the pitch moment and yaw moment in the rotating coordinate system are obtained. These two outputs are converted into independent deviations of the three pitch angles, thereby achieving independent pitch control. The Coleman coordinate transformation is performed on the blade pitch angle to obtain the deviation pitch angle.

[0236] Step S5: Extract pitch output feedback from the output circuit of the floating wind turbine and combine it with the independent pitch control from Step S4, incorporating it into the independent pitch expert PID control, such as... Figure 6 The diagram shows the flowchart of the expert PID control. An independent pitch angle controller controls the platform's pitch. An expert PID controller is configured to address its nonlinear characteristics, and a dq coordinate transformation is used to distribute the controller's output signal to the three blades according to the difference in azimuth angles of the three blades.

[0237] Furthermore, these values ​​are superimposed with the uniform pitch angle obtained in step 3 to obtain β+Δβ1, β+Δβ2, and β+Δβ3, thereby achieving control.

[0238] Finally, the integrated control model for this example is established, such as... Figure 7 shown.

[0239] Furthermore, controlling the contrast effect as follows Figure 8As shown, the control model proposed in this example can effectively reduce the pitch amplitude, while reducing blade load and improving the stability and safety of the floating wind turbine.

[0240] This embodiment also provides a floating wind turbine pitch control device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0241] This embodiment provides a floating wind turbine pitch control device, such as... Figure 9 As shown, the device includes:

[0242] The acquisition module 901 is used to acquire the wind turbine model of the floating wind turbine to be controlled. The wind turbine model is constructed by the aerodynamic factors, hydrodynamic factors and mooring dynamic factors corresponding to the floating wind turbine to be controlled.

[0243] The adjustment and determination module 902 is used to adjust the preset PI control method based on the wind turbine model and use the gain scheduling control model to determine the uniform pitch angle of the floating wind turbine to be controlled.

[0244] The calculation module 903 is used to calculate the deviation pitch angle of each blade in the floating wind turbine to be controlled, based on the preset platform pitch value and processed by the expert PID control method and the Coleman coordinate transformation method.

[0245] The control module 904 is used to perform pitch control on the floating wind turbine based on the uniform pitch angle and the deviation pitch angle of each blade, and obtain the pitch control result.

[0246] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0247] In this embodiment, the floating wind turbine pitch control device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0248] This invention also provides a computer device having the above-described features. Figure 8 The floating wind turbine pitch control device shown is shown.

[0249] Please see Figure 10 , Figure 10 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 10 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 10 Take a processor 10 as an example.

[0250] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0251] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0252] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0253] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0254] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0255] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0256] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0257] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A pitch control method for a floating wind turbine, characterized in that, The method includes: A model of the floating wind turbine to be controlled is obtained, and the model is constructed by the aerodynamic factors, hydrodynamic factors and mooring dynamic factors corresponding to the floating wind turbine to be controlled. Based on the wind turbine model, the preset PI control method is adjusted using the gain scheduling control model to determine the uniform pitch angle of the floating wind turbine to be controlled. Based on the preset platform pitch value, and after processing by the expert PID control method and the Coleman coordinate transformation method, the deviation pitch angle of each blade in the floating wind turbine to be controlled is calculated. Based on the unified pitch angle and the deviation pitch angle of each blade, pitch control is performed on the floating wind turbine to obtain the pitch control result.

2. The method according to claim 1, characterized in that, Obtain the wind turbine model of the floating wind turbine to be controlled, including: The aerodynamics of the floating wind turbine to be controlled are modeled to obtain an aerodynamic model; Based on linear wave theory and potential flow theory, the hydrodynamics of the floating wind turbine to be controlled are modeled to obtain a hydrodynamic model. The mooring dynamics of the floating wind turbine to be controlled are modeled to obtain a mooring model, which includes a catenary mooring system model and a force model. The wind turbine model is determined based on the aerodynamic model, the hydrodynamic model, and the mooring model.

3. The method according to claim 1, characterized in that, Based on the wind turbine model, a gain scheduling control model is used to adjust the preset PI control method and determine the uniform pitch angle of the floating wind turbine to be controlled, including: Based on the wind turbine model, the floating wind turbine to be controlled is controlled using the preset PI control method to obtain the first proportional control parameter and the first integral control parameter. The first proportional control parameter and the first integral control parameter are adjusted using the gain scheduling control model to obtain the second proportional control parameter and the second integral control parameter. The uniform pitch angle of the floating wind turbine to be controlled is determined based on the second proportional control parameter and the second integral control parameter.

4. The method according to claim 3, characterized in that, Based on the wind turbine model, the floating wind turbine to be controlled is controlled using the preset PI control method to obtain first proportional control parameters and first integral control parameters, including: The control objective is determined based on the aforementioned wind turbine model; Based on the control objective, the first pitch angle relationship is determined using the preset PI control method; The first pitch angle relationship is transformed by Laplace to obtain the second pitch angle relationship; Obtain the linearized model of the wind turbine drive chain and determine the kinematic relationship of the single-degree-of-freedom model of the wind turbine drive based on the linearized model of the wind turbine drive chain; The first proportional control parameter and the first integral control parameter are calculated based on the first pitch angle relationship, the second pitch angle relationship, and the motion relationship.

5. The method according to claim 1, characterized in that, Based on the preset platform pitch value, and using expert PID control and Coleman coordinate transformation methods, the deviation pitch angle of each blade in the floating wind turbine to be controlled is calculated, including: The expert PID control method is used to control the floating wind turbine to obtain the initial pitch angle and the initial yaw angle. Based on the preset platform pitch value, the initial pitch angle and initial yaw angle are controlled using the expert PID control method to obtain the target pitch angle and target yaw angle. Based on the target pitch angle and the target yaw angle, the deviation pitch angle of each blade in the floating wind turbine to be controlled is obtained through the Coleman coordinate transformation method.

6. The method according to claim 3, characterized in that, The gain scheduling control model is expressed by the following relation: K p_β =K p *h(b) K i_β =K i *h(b) In the formula: K p_β Indicates the second proportional control parameter; K p Indicates the first proportional control parameter; K i_β Indicates the second integral control parameter; K i η(β) represents the first integral control parameter; η(β) represents the correction coefficient; β represents the pitch angle.

7. A pitch control device for a floating wind turbine, characterized in that, The device includes: The acquisition module is used to acquire the wind turbine model of the floating wind turbine to be controlled. The wind turbine model is constructed by the aerodynamic factors, hydrodynamic factors and mooring dynamic factors corresponding to the floating wind turbine to be controlled. The adjustment and determination module is used to adjust the preset PI control method based on the wind turbine model and use the gain scheduling control model to determine the uniform pitch angle of the floating wind turbine to be controlled. The calculation module is used to calculate the deviation pitch angle of each blade in the floating wind turbine to be controlled, based on the preset platform pitch value and processed by the expert PID control method and the Coleman coordinate transformation method. The control module is used to perform pitch control on the floating wind turbine based on the uniform pitch angle and the deviation pitch angle of each blade, and obtain the pitch control result.

8. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the pitch control method for a floating wind turbine as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the floating wind turbine pitch control method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the floating wind turbine pitch control method according to any one of claims 1 to 6.

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