System and method for optimizing control of wind turbine

Abstract

A method for optimizing control of a wind turbine includes receiving, via a control system, a condition of the wind turbine. The method also includes estimating a current state of the wind turbine using the condition. The method further includes calculating, via a model implemented by the control system, a linearized representation of operation of the wind turbine for a future time interval after the current state. The method further includes defining an optimization problem to be solved. The method also includes determining a pitch adjustment factor for modifying a current state of the wind turbine. The method further includes calculating, via the optimization solver, an optimized pitch parameter of a rotor blade of the wind turbine. The method also includes adjusting a pitch parameter of the rotor blade to an optimized pitch parameter to improve the control.

Description

Technical Field

[0001] This disclosure generally relates to wind turbines, and more particularly to systems and methods for optimizing the control of wind turbines. Background Technology

[0002] Wind power is considered one of the cleanest and most environmentally friendly energy sources available today, and wind turbines are receiving increasing attention in this area. A modern wind turbine typically includes a tower, generator, gearbox, nacelle, and one or more rotor blades. The rotor blades are the primary components used to convert wind energy into electrical energy. The blades typically have an airfoil cross-sectional profile, causing air to flow over the blades during operation, creating a pressure difference between their sides. Therefore, lift forces acting on the blades act from the pressure side towards the suction side. This lift generates torque on the main rotor shaft, which is connected to the generator used to produce electricity.

[0003] The amount of power that can be generated by a wind turbine is typically limited by the structural constraints (i.e., design loads) of individual wind turbine components. For example, wind turbine blades can experience loads associated with both average loads due to turbine operation and dynamic fluctuating loads due to environmental conditions. These loads can be affected by the blade pitch angle and other factors. Such loads can damage turbine components, such as the pitch or yaw bearing, thereby causing turbine failure. Fluctuating loads can vary daily or seasonally and can be affected by wind speed, wind crests, wind turbulence, wind shear, changes in wind direction, air density, bearing misalignment, upwelling, or similar conditions.

[0004] In this regard, the purpose of wind turbine design is to ensure that the loads acting on the turbine components do not exceed the design load. Therefore, many wind turbines employ one or more sensors configured to measure the loads acting on various turbine components. Furthermore, wind turbines may utilize control systems configured to estimate the loads acting on the turbine based on multiple factors.

[0005] Therefore, the control system can operate in conjunction with multiple sensors to estimate the loads acting on the wind turbine components and adjust the wind turbine's operation in response to the estimated loads. For example, the control system can instruct the wind turbine to adjust the pitch angle of its rotor blades or the rotor position of the wind turbine. These adjustments can be made to improve one or more conditions associated with the wind turbine's operation. However, improving the first condition associated with the wind turbine can adversely affect another, second condition associated with the wind turbine. Furthermore, in attempting to optimize the conditions associated with the wind turbine's operation, the control system may overcorrect or undercorrect the wind turbine's operation.

[0006] In view of the foregoing, the art continues to seek new and improved systems for optimizing the control of wind turbines, such as pitch control. Summary of the Invention

[0007] Aspects and advantages of the invention will be set forth in part in the description which follows, and may be apparent from the description or learned by practice of the invention.

[0008] In one aspect, this disclosure relates to a method for optimizing the control of a wind turbine. The method includes receiving at least one state of the wind turbine via a control system. The method further includes estimating the current state of the wind turbine using the at least one state via the control system. The method also includes calculating a linearized representation of the wind turbine's operation over future time intervals following the current state via a model implemented by the control system. The method further includes defining an optimization problem to be solved via the control system, wherein the optimization problem includes a cost function and pitch constraints. The method also includes determining a pitch adjustment factor via the control system for modifying the current state of the wind turbine, wherein the pitch adjustment factor includes at least one weight in the cost function that, when implemented, increases or decreases the behavior exhibited by the wind turbine, wherein the cost function is implemented in an optimization solver implemented by the control system. The method further includes: calculating optimized pitch parameters of at least one rotor blade of the wind turbine from the linearized representation using the pitch adjustment factor and pitch constraints via the optimization solver implemented in the control system, wherein the optimized pitch parameters are a solution to the optimization problem. The method further includes: adjusting the pitch parameters of at least one rotor blade to the optimized pitch parameters such that the behavior exhibited by the wind turbine increases or decreases, and improves the control of the wind turbine.

[0009] In embodiments of the method, at least one condition includes at least one measurement of rotor speed, generator speed, wind speed, wind direction, wind shear, wind direction, wind turbulence, structural force or moment, structural displacement, structural velocity or structural acceleration.

[0010] In embodiments of the method, the current state of the wind turbine includes transient aerodynamic effects distributed across a portion of the wind turbine, wherein the transient aerodynamic effects include at least one of a force or torque acting on a portion of the wind turbine, or the current state of the wind turbine includes transient structural effects distributed across a portion of the wind turbine, wherein the transient structural effects include at least one of a structural displacement, structural velocity, or structural acceleration of any structural component of the wind turbine.

[0011] In embodiments of the method, improvements to the control of the wind turbine include reducing the load on the wind turbine, increasing the expected bearing life, increasing power generation, improving power quality, improving power tracking performance, or improving speed tracking performance.

[0012] In embodiments of the method, optimizing pitch parameters includes the pitch angle, pitch rate, or pitch acceleration trajectory of at least one rotor blade of the wind turbine.

[0013] In an embodiment of the method, the weights correspond to the symmetrical pitch motion of at least one rotor blade of a wind turbine.

[0014] In an embodiment of the method, the weights correspond to the asymmetric pitch motion of at least one rotor blade of a wind turbine.

[0015] In embodiments of the method, the weights correspond to the amplitude of the harmonics of the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration above at least one rotor blade.

[0016] In an embodiment of the method, at least one rotor blade includes a first rotor blade and a second rotor blade, wherein the pitch angle, pitch rate, or pitch acceleration of the first rotor blade includes a frequency higher than that of the second rotor blade, wherein a weight is applied to the pitch angle, pitch rate, or pitch acceleration of the first rotor blade such that the amplitude of harmonics higher than the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration is reduced.

[0017] In embodiments of the method, the pitch adjustment factor includes one of a linear or quadratic term at a future time interval, wherein the pitch constraint includes a linear or quadratic constraint at a future time interval, or wherein the pitch adjustment factor includes the variance or tracking of the pitch angle, pitch rate, or pitch acceleration of at least one rotor blade.

[0018] In embodiments of the method, the pitch constraint corresponds to the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration of at least one rotor blade, or the pitch constraint corresponds to the maximum or minimum permissible pitch motor torque, current, voltage, or power.

[0019] In embodiments of the method, the pitch constraint further includes an increase or decrease in the maximum permissible pitch angle, pitch rate, or pitch acceleration of at least one rotor blade, or a decrease or increase in the minimum permissible pitch angle, pitch rate, or pitch acceleration of at least one rotor blade, wherein the maximum or minimum permissible increase or decrease in pitch angle, pitch rate, or pitch acceleration is applied in response to at least one received condition at a future time interval, or wherein the pitch constraint further includes an increase or decrease in the maximum permissible pitch motor torque, current, voltage, or power, or a decrease or increase in the minimum permissible pitch motor torque, current, voltage, or power, wherein the maximum or minimum permissible increase or decrease in pitch angle, pitch rate, or pitch acceleration is applied in response to at least one received condition at a future time interval.

[0020] In embodiments of the method, the pitch adjustment factor includes two or more pitch adjustment factors, wherein the optimized pitch parameter of at least one rotor blade is calculated using two or more pitch adjustment factors and pitch constraints.

[0021] In embodiments of the method, the pitch adjustment factor includes one or more penalties for the total pitch angle variation of at least one rotor blade, or a penalty for the product of the pitch travel of at least one rotor blade and the magnitude of the load on at least one rotor blade.

[0022] In an embodiment, the method further includes: using a pitch adjustment factor via an optimization solver implemented in the control system, calculating an optimized torque of the wind turbine rotor from a linearized representation using the pitch adjustment factor and pitch constraints; and adjusting the rotor torque to the optimized torque such that the behavior exhibited by the wind turbine increases or decreases, and improves the control of the wind turbine.

[0023] In another aspect, this disclosure relates to a system for optimizing the control of a wind turbine. The system includes at least one sensor configured to monitor at least one condition of the wind turbine. The system also includes a control system configured to receive at least one condition of the wind turbine. The control system is further configured to estimate the current state of the wind turbine using the at least one condition. The control system is further configured to compute a linearized representation of the wind turbine's operation over future time intervals following the current state via a model implemented by the control system. The control system is further configured to define an optimization problem to be solved, wherein the optimization problem includes a cost function and pitch constraints. The control system is further configured to determine a pitch adjustment factor for modifying the current state of the wind turbine, wherein the pitch adjustment factor includes at least one weight in the cost function that, when implemented, increases or decreases the behavior exhibited by the wind turbine, wherein the cost function is implemented in an optimization solver implemented by the control system. The control system is further configured to compute optimized pitch parameters of at least one rotor blade of the wind turbine from the linearized representation using the pitch adjustment factor and pitch constraints via the optimization solver implemented in the control system, wherein the optimized pitch parameters are a solution to the optimization problem. The control system is also configured to adjust the pitch parameter of at least one rotor blade to an optimized pitch parameter, thereby increasing or decreasing the behavior exhibited by the wind turbine and improving the control of the wind turbine.

[0024] These and other features, aspects, and advantages of the invention will become more readily understood with reference to the following description and the appended claims. The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. Attached Figure Description

[0025] The complete and open disclosure of the invention, including its best mode for those skilled in the art, is set forth in the description with reference to the accompanying drawings, in which:

[0026] Figure 1 A perspective view showing an embodiment of a wind turbine according to the present disclosure;

[0027] Figure 2 A simplified interior view of one embodiment of the nacelle of a wind turbine according to the present disclosure is shown;

[0028] Figure 3 A schematic diagram illustrating an embodiment of a controller according to the present disclosure is shown;

[0029] Figure 4 A simplified diagram illustrating an embodiment of a wind turbine control system according to the present disclosure is shown;

[0030] Figure 5 A perspective view of an embodiment of a wind turbine according to the present disclosure is shown, particularly illustrating various axes of rotation and the corresponding structural forces and moments acting on the wind turbine;

[0031] Figure 6 A flowchart illustrating an embodiment of a method for optimizing the control of a wind turbine according to the present disclosure;

[0032] Figure 7 A diagram illustrating an embodiment of an estimate of the current state of a wind turbine from its condition, based on the present disclosure, and a linearized representation of the wind turbine's operation calculated over future time intervals following the current state;

[0033] Figure 8 A diagram illustrating an embodiment of a multi-objective model for determining optimized pitch parameters of a wind turbine according to the present disclosure;

[0034] Figures 9A-9B A graph illustrating the effect of adjusting the pitch parameters of a wind turbine rotor blade to an optimized pitch parameter using weights corresponding to symmetrical or asymmetrical pitch motion according to this disclosure.

[0035] Figure 10A-10D A graph illustrating the effect of adjusting the pitch parameters of rotor blades to optimize pitch parameters according to this disclosure by using the weights of the harmonic amplitudes corresponding to the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration of the rotor blades above the wind turbine.

[0036] Figure 11A-11B A graph showing the pitch adjustment factor applied in response to peak load intervals according to this disclosure; and

[0037] Figure 12A-12D A graph showing the effect of adjusting the rotor blade pitch parameters to optimized pitch parameters according to this disclosure. Detailed Implementation

[0038] Reference will now be made in detail to embodiments of the invention, one or more of which are illustrated in the accompanying drawings. Each example is provided by way of illustration and not by way of limitation. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made to the invention without departing from the scope or spirit of the invention. For example, features shown or described as part of an embodiment may be used with another embodiment to produce yet another embodiment. Therefore, it is intended that the invention cover such modifications and variations that fall within the scope of the appended claims and their equivalents.

[0039] Generally, this disclosure relates to improved systems and methods for optimizing the control (such as pitch control) of wind turbines. More specifically, the systems and methods of this disclosure use a control system that receives one or more conditions of a wind turbine. These conditions may be received at various time intervals. These conditions may also relate to the pitch of the wind turbine. The control system then estimates the current state of the wind turbine using the conditions(s). Next, the control system implements a model to calculate the expected state of the wind turbine for future time intervals using the current state of the wind turbine. Subsequently, the control system defines an optimization problem to be solved, which includes a pitch adjustment factor and pitch constraints. By solving the optimization problem, optimized pitch parameters are determined that, when implemented by the control system of the wind turbine, can improve the control of the wind turbine and increase or decrease the behavior exhibited by the wind turbine.

[0040] Once the optimization problem is defined, the control system determines the pitch adjustment factor used to modify the current state of the wind turbine by finding weights in a cost function implemented within the control system. The optimization solver is then implemented to compute the optimal pitch parameters of the wind turbine rotor blades from a linearized representation using the pitch adjustment factor and pitch constraints, where the optimal pitch parameters are the solution to the optimization problem. The control system then adjusts the rotor blade pitch parameters to the optimal pitch parameters, thereby increasing or decreasing the behavior exhibited by the wind turbine and improving its control. Thus, the control of the wind turbine can be improved, as demonstrated by the achievement of various objectives.

[0041] Therefore, the systems and methods disclosed herein provide a framework through which the control of wind turbines can be periodically updated and optimized to match objectives determined by the operator. These objectives may include at least: a reduction in one or more loads acting on the wind turbine, an expected increase in pitch bearing life, and / or an increase in power generation.

[0042] Now refer to Figure 1This diagram shows a perspective view of an embodiment of a wind turbine 10 that can implement the control technology according to this disclosure. As shown, the wind turbine 10 generally includes a tower 12 extending from a support surface 14, a nacelle 16 mounted on the tower 12, and a rotor 18 coupled to the nacelle 16. The rotor 18 includes a rotatable hub 20 and at least one rotor blade 22 coupled to and extending outward from the hub 20. For example, in the illustrated embodiment, the rotor 18 includes three rotor blades 22. However, in alternative embodiments, the rotor 18 may include more or fewer than three rotor blades 22. Each rotor blade 22 may be spaced about the hub 20 to allow the rotor 18 to rotate so that kinetic energy can be converted from wind into usable mechanical energy, and subsequently, electrical energy. For example, the hub 20 may be rotatably coupled to a generator 24 positioned within the nacelle 16. Figure 2 ), to allow the generation of electrical energy.

[0043] The wind turbine 10 may also include a wind turbine control system 26 centrally located within the nacelle 16. However, in other embodiments, the control system 26 may be located within any other component of the wind turbine 10 or at a location outside the wind turbine. Furthermore, the control system 26 may be communicatively coupled to any number of components of the wind turbine 10 to control the operation of such components and / or perform corrective actions. In this regard, the control system 26 may include a computer or other suitable processing unit. Thus, in several embodiments, the control system 26 may include suitable computer-readable instructions that, when implemented, configure the control system 26 to perform various functions, such as receiving, transmitting, and / or implementing wind turbine control signals. Therefore, the control system 26 may be generally configured to control various operating modes (e.g., start-up or shutdown sequences), reduce the rated power of the wind turbine, and / or control various components of the wind turbine 10, as will be discussed in more detail below.

[0044] Now refer to Figure 2 , showing Figure 1 The diagram shows a simplified internal view of an embodiment of the nacelle 16 of the wind turbine 10. As shown, a generator 24 may be coupled to a rotor 18 to generate electrical power from the rotational energy generated by the rotor 18. For example, as shown in the illustrated embodiment, the rotor 18 may include a rotor shaft 34 coupled to a hub 20 for rotation therewith. The rotor shaft 34 may then be rotatably coupled to a generator shaft 36 of the generator 24 via a gearbox 38. As generally understood, the rotor shaft 34 may provide a low-speed, high-torque input to the gearbox 38 in response to rotation of the rotor blades 22 and the hub 20. The gearbox 38 may then be configured to convert the low-speed, high-torque input into a high-speed, low-torque output to drive the generator shaft 36 and thus the generator 24.

[0045] Each rotor blade 22 may also include a pitch adjustment mechanism 32 configured to rotate each rotor blade 22 about its pitch axis 28. Furthermore, each pitch adjustment mechanism 32 may include a pitch drive motor 40 (e.g., any suitable electric, hydraulic, or pneumatic motor), a pitch drive gearbox 42, and a pitch drive pinion 44. In such embodiments, the pitch drive motor 40 may be coupled to the pitch drive gearbox 42 to apply mechanical force to the pitch drive gearbox 42. Similarly, the pitch drive gearbox 42 may be coupled to the pitch drive pinion 44 for rotation therewith. The pitch drive pinion 44 may then be rotatably engaged with a pitch bearing 46 connected between the hub 20 and the corresponding rotor blade 22, such that rotation of the pitch drive pinion 44 causes rotation of the pitch bearing 46. Therefore, in such embodiments, the rotation of the pitch drive motor 40 drives the pitch drive gearbox 42 and the pitch drive pinion 44, thereby causing the pitch bearing 46 and the rotor blades 22 to rotate about the pitch axis 28. Similarly, the wind turbine 10 may include one or more yaw drive mechanisms 66 communicatively coupled to the control system 26, wherein each yaw drive mechanism(s) 66 is configured to change the angle of the nacelle 16 relative to the wind (e.g., by engaging the yaw bearing 68 of the wind turbine 10).

[0046] Still refer to Figure 2 The wind turbine 10 may also include one or more sensors 48, 50 for measuring various operating conditions that can be used to determine the operating state of the wind turbine 10, as described in more detail below. For example, in various embodiments, the sensors may include: blade sensors 48 for measuring the pitch angle, pitch rate, or pitch acceleration of one of the rotor blades 22; for measuring the load acting on one of the rotor blades 22; or for measuring the rotor speed of the rotor 18. The sensors may also include generator sensors (not shown) for monitoring the generator 24 (e.g., torque, speed, acceleration, and / or power output); sensors (not shown) for measuring unbalanced loads in the rotor (e.g., a main shaft bending sensor); various wind sensors 50 for measuring various wind conditions such as wind speed, wind crest, wind turbulence, wind shear, wind direction change, air density, or the like; and / or sensors (not shown) for measuring structural forces or moments, structural displacements, structural velocities, or structural accelerations exhibited by or applied to the wind turbine 10.

[0047] Additionally, sensors may be located near the ground, on the nacelle, or on the weather mast of the wind turbine. It should also be understood that any other number or type of sensors may be used at any location. For example, sensors may be micro inertial measurement units (MIMUs), strain gauges, accelerometers, pressure sensors, angle-of-attack sensors, vibration sensors, proximity sensors, light-detecting and ranging (LIDAR) sensors, camera systems, fiber optic systems, anemometers, wind vanes, sound-detecting and ranging (SODAR) sensors, infrared lasers, radiometers, pitot tubes, radiosondes, other optical sensors, and / or any other suitable sensors. It should be recognized that, as used herein, the term “monitor” and its variations indicate that various sensors may be configured to provide direct or indirect measurements of the monitored condition. Thus, for example, sensors may be used to generate signals associated with the monitored condition, which can then be utilized by control system 26 to determine the actual condition.

[0048] Now refer to Figure 3 This diagram illustrates a block diagram of various components of a control system 26 according to the present disclosure. As shown, the control system 26 may include one or more processors 58 and associated memory devices(s) 60 configured to perform various computer-implemented functions (e.g., performing methods, steps, calculations, etc., and storing related data, as disclosed herein). Additionally, the control system 26 may include a communication module 62 to facilitate communication between the control system 26 and various components of the wind turbine 10. Furthermore, the communication module 62 may include a sensor interface 64 (e.g., one or more analog-to-digital converters) to allow signals transmitted from sensors 48, 50 to be converted into signals that can be understood and processed by the processor 58. It should be appreciated that sensors 48, 50, or any other sensors monitoring the wind turbine 10 may be communicatively coupled to the communication module 62 using any suitable means. For example, as... Figure 3 As shown, sensors 48 and 50 are connected to sensor interface 64 via a wired connection. However, in other embodiments, sensors 48 and 50 may be connected to sensor interface 64 via a wireless connection, such as by using any suitable wireless communication protocol known in the art.

[0049] As used herein, the term "processor" refers not only to integrated circuits included in a computer as understood in the art, but also to controllers, microcontrollers, microcomputers, programmable logic controllers (PLCs), application-specific integrated circuits (ASICs), and other programmable circuits. Additionally, the memory device(s) 60 may generally include memory elements(s), including but not limited to computer-readable media (e.g., random access memory (RAM)), computer-readable non-volatile media (e.g., flash memory), floppy disks, read-only optical disc (CD-ROM), magneto-optical disc (MOD), digital versatile optical disc (DVD), and / or other suitable memory elements. Such memory device(s) 60 may be generally configured to store suitable computer-readable instructions, when implemented by the processor(s) 58, to configure the control system 26 to perform various functions, including but not limited to determining one or more current wind turbine conditions of the wind turbine 10 based on multiple operational data, determining maximum wind turbine conditions, sending suitable control signals to implement control actions to reduce the load acting on the wind turbine, and various other suitable computer-implemented functions.

[0050] As described, control system 26 may also be able to implement a variety of processing and control methods. For example, and specifically referring to Figure 4 The control system 26 may be a model predictive control (MPC) system capable of implementing the MPC framework 70. The MPC framework may be any MPC system understood in the art. The MPC framework 70 may also utilize any algorithm, rule, or code, such as machine learning or artificial intelligence.

[0051] As shown, the MPC framework 70 may generally include an estimation module 72, a simulation module 74, an optimization module 76, and a regulation module 78. The estimation module 72 is configured to receive at least one condition of the wind turbine 10 and estimate the current state of the wind turbine 10 using the condition(s). The simulation module 74 is configured to implement a model to calculate the expected state of the wind turbine 10, which defines a future time interval following the current state. As described, the "future time interval" can be any time in the future that the control system 26 can predict, i.e., a prediction range. For example, the future time interval can be approximately 0.001 to 11 seconds, such as approximately 0.01 to 10 seconds, such as approximately 1 to 9 seconds.

[0052] The optimization module 76 is configured to define the optimization problem to be solved, which includes a pitch adjustment factor and pitch constraints. The optimization module 76 is also configured to determine a pitch adjustment factor for modifying the current state of the wind turbine. The optimization module is further configured to implement an optimization solver to compute optimized pitch parameters for the wind turbine 10 to solve the optimization problem. As further described herein, the pitch parameters are any conditions relating to the pitch system (such as the pitch drive mechanism 32 of the wind turbine 10). For example, in embodiments, the pitch parameters may be a pitch trajectory, the pitch angle of at least one rotor blade 22, the pitch rate of at least one rotor blade 22, and / or the pitch acceleration of at least one rotor blade 22.

[0053] Once the optimized pitch parameters are determined, the control system 26 can then adjust the pitch parameters of at least one rotor blade 22 to the optimized pitch parameters in order to optimize the control of the wind turbine 10 and / or increase or decrease the behavior exhibited by the wind turbine 10. Before or after adjusting the pitch parameters, the adjustment module 78 is configured to take into account the adjustment of the pitch parameters and further calculate the expected state of the wind turbine 10, which represents the operation of the wind turbine 10 at future time intervals.

[0054] Therefore, as described, the MPC framework 70 is configured to handle multiple factors within a predictive framework. Specifically, as it relates to this disclosure, the MPC framework 70 is capable of managing input constraints, structural loads, and / or operability constraints while optimizing the operation of the wind turbine 10, as will be discussed in more detail herein. Furthermore, the MPC framework 70 is configured to provide a single multiple-input multiple-output (MIMO) formula that unifies performance and constraint objectives. Thus, the MPC framework 70 avoids the complex interactions of multiple single-input single-output (SISO) control functions traditionally used to solve wind turbine control design when considering multiple objectives.

[0055] Now go to Figure 5 An exploded view of an embodiment of the wind turbine 10 is shown, particularly illustrating the various axes of rotation and the corresponding structural forces and moments acting on the wind turbine 10. The forces applied to the wind turbine 10 can vary between wind turbines, but generally correspond to at least one of the following: distributed forces from the wind, conventionally decomposed into lift and drag components; gravity; and the resultant force at the blade root (e.g., F0). rB ), pitch and hub force (F) xB F yb and F zb ), principal axial force (e.g., F) yr F zr ), main bearing force (e.g., F) xr F yr ), yaw drive force (e.g., F) xk), yaw bolt / bearing / flange force (e.g., F) yk F zk ) or tower bending force (e.g., F xt F yt and F zt Since forces are applied to the wind turbine 10 at various locations and on various structural components across the entire profile of the wind turbine 10, torque loads can also be applied to the wind turbine 10.

[0056] Similar to the forces applied to the wind turbine 10, the moment load applied to the wind turbine 10 can vary between turbines, but generally corresponds to at least one of the following: moments generated by distributed aerodynamic forces and gravity, and a combined moment load at the blade root (e.g., M). rB ), pitch and hub moment load (M) xB M yb and M zb ), spindle torque load (e.g., M) yr M zr ), main bearing torque load (e.g., M) xr M yr ), yaw drive torque load (e.g., M) xk ), yaw bolt / bearing / flange torque load (e.g., M) yk M zk ) or tower bending moment load (e.g., M xt M yt and M zt It should be understood that the force and moment loads described herein may also include any additional force or moment loads experienced by the wind turbine 10, and Figure 4 The force and moment loads shown are provided for illustrative purposes only.

[0057] Now refer to Figure 6 This disclosure illustrates a flowchart of an embodiment of a method 100 for optimizing pitch control of a wind turbine. In embodiments, for example, pitch control can be optimized using, for example, a control system 26, one or more of rotor blades 22, a pitch bearing 46, and / or the hub 20 of the wind turbine 10. Method 100 is described herein as being implemented using, for example, the wind turbine 10 described above. However, it should be recognized that the disclosed method 100 can be implemented using any other suitable wind turbine now known in the art or subsequently developed. Additionally, although... Figure 6 The steps performed in a particular order are depicted for illustrative and discussion purposes; however, the methods described herein are not limited to any particular order or arrangement. Those skilled in the art will recognize using the disclosure provided herein that the various steps of the methods can be omitted, rearranged, combined, and / or modified in various ways.

[0058] As shown at (102), method 100 includes receiving at least one condition of the wind turbine 10 via control system 26. For example, in an embodiment, the condition(s) may be one or more of the following: rotor speed, generator speed, wind speed, wind direction, wind shear, wind direction, wind turbulence, structural force or moment, structural displacement, structural velocity, structural acceleration, or the like. Such conditions may be detected by sensors 48, 50 positioned relative to the wind turbine 10 or any other sensors communicatively coupled to the wind turbine 10. Conditions may also be detected using sensors (not shown) external to the wind turbine 10.

[0059] As shown at (104), method 100 includes estimating the current state of wind turbine 10 using conditions(s) via control system 26. For example, in an embodiment, the current state of wind turbine 10 may include transient aerodynamic effects distributed across portions of wind turbine 10 (such as at least one of rotor blades 22). Specifically, transient aerodynamic effects may include force and moment loads described above, such as the resultant force at the blade root (e.g., F0). rB ), pitch and hub force (F) xB F yb and F zb ), the resultant moment load at the blade root (e.g., M) rB ) or pitch and hub moment load (M) xB M yb and M zb Instantaneous aerodynamic effects can be calculated from the pitch of each of the rotor blades 22 of the wind turbine 10 and the torque applied to the rotor blades 22, as well as the wind forces acting on the wind turbine 10 (such as wind speed, wind direction, vertical shear, horizontal shear, directional change, or turbulence). However, if it is not possible to determine the wind force (e.g., due to a lack of sensors), the wind force can be estimated for the purpose of calculating instantaneous aerodynamic effects.

[0060] The current state of the wind turbine 10 may also include transient structural effects across portions of the wind turbine 10 (such as the tower 12 or the nacelle 16). Specifically, transient structural effects may include at least one of structural displacement, structural velocity, or structural acceleration of any structural member of the wind turbine 10. For example, transient structural effects may include principal axial forces (e.g., F...). yr F zr ), main bearing force (e.g., F) xr F yr ), yaw drive force (e.g., F) xk ), yaw bolt / bearing / flange force (e.g., F) yk F zk ), tower bending force (e.g., F) xt F yt and F zt), spindle torque load (e.g., M yr M zr ), main bearing torque load (e.g., M) xr M yr ), yaw drive torque load (e.g., M) xk ), yaw bolt / bearing / flange torque load (e.g., M) yk M zk ) or tower bending moment load (e.g., M xt M yt and M zt Instantaneous structural effects can also be calculated from the pitch of each of the rotor blades 22 of the wind turbine 10 and the torque applied to the rotor blades 22, as well as the wind forces acting on the wind turbine 10 (such as wind speed, wind direction, vertical shear, horizontal shear, directional change, or turbulence). Furthermore, similar to instantaneous aerodynamic forces, if it is impossible to determine the wind forces (e.g., due to a lack of sensors), the wind forces for calculating instantaneous aerodynamic effects can be estimated.

[0061] As shown at (106), method 100 includes calculating a linearized representation of the operation of the wind turbine 10 over future time intervals following the current state via a model implemented by the control system 26. Specifically, the linearized representation of the operation of the wind turbine 10 over future time intervals can define the expected state of the wind turbine 10. Furthermore, the expected state can be defined as a set of quantities (represented by the model) that fully characterize the dynamics of the wind turbine 10. Specifically, as... Figure 7 As shown, the current state 200 of the wind turbine 10 can be received by the control system 26. Therefore, the control system 26 can use the current state 200 to simulate a desired state 202 for future time intervals of the wind turbine 10. For example, the desired state 202 can be calculated from the input trajectory u* and the current state 200. The input trajectory u* can be provided for any time interval to be simulated, such as the time interval described above with reference to future time intervals that can be observed by the control system 26.

[0062] The input trajectory u* may include predictions of factors used to calculate the instantaneous aerodynamic or structural effects acting on the wind turbine 10 (i.e., the pitch of each of the rotor blades 22 of the wind turbine 10 and the torque applied to the rotor by the generator, as well as the wind forces acting on the wind turbine 10, such as wind speed, wind direction, vertical shear, horizontal shear, directional change, or turbulence). However, if it is impossible to determine the wind force (e.g., due to a lack of sensors), the wind force may also be estimated to set the input trajectory u* with respect to the instantaneous aerodynamic or structural effects. However, if the wind force is estimated, the estimation will be used for each of the time intervals that provide the input trajectory u*. Additionally, as the expected state 202 progresses over time, one or more input trajectories u* from previous time-optimized instances will be used together with the input trajectory u* of the time instance to be simulated to provide an output for the expected state 202 at the new time instance. This set of input trajectory u* provided along with the current state 200 can then be used to calculate another expected state 202, as by Figure 7 The graph shown in the image represents this.

[0063] Additionally, as described above, one or more linearized representations of the operation of the wind turbine 10 may be provided. These linearized representations may be determined at sampling time intervals (such as time interval 204). However, they may also be provided at any time of the expected state 202. The linearized representations may be one or more matrices representing the expected behavior of the wind turbine 10 at a future time interval (such as at time interval 204) prior to when the linearized representations are initially determined. Once determined, the linearized representations may be collected and used within the model to implement subsequent functions or calculations as discussed below.

[0064] In an alternative embodiment, a linearization process can be achieved without simulating the model. If the optimization problem used in the predictive controller is a nonlinear programming (NLP) problem, the model can be linearized not only before the optimization solver is executed, but also during the optimization process. To accelerate convergence, the NLP solver algorithm may need to linearize the model at each iteration of the solver.

[0065] Refer back Figure 6 As shown at (108), method 100 further includes defining the optimization problem to be solved via a control system. The optimization problem may include a cost function and pitch constraints. In an embodiment, the cost function may be the formula (1) provided below: It is the number of constraint signals associated with the output from the model. It is the number of performance signals associated with the input to the model. It is the j-th performance signal associated with the input of the model (in particular, for pitch motion, parameters such as angle, speed, and acceleration can be input performance signals). It is a signal Reference value, W u (j) is the weight of the difference between the input signals and their corresponding reference values. It is the j-th performance signal associated with the output of the model (e.g., any load value, such as torque or force at any location of the turbine structure, or any result of turbine operation, such as generated power or rotor speed). It is a signal Reference value, W y (j) is the weight of the difference between the output signal and its corresponding reference value. ∈ U (j) is the slack variable corresponding to any upper bound constraint. It is a slack variable ∈ U The weight of (j), ∈ L (j) is the slack variable corresponding to any lower bound constraint, and It is a slack variable ∈ L The weight of (j).

[0066] Solving the optimization problem, which will be described in more detail below, may involve finding specific weights and slack variables corresponding to the pitch constraints that minimize the output J of the cost function. Additionally, the cost function may be implemented in an optimization solver implemented by the control system 26. The optimization solver may be any type of algorithm, program, or software that determines the values ​​that minimize the output of the cost function, such as optimization module 76. The pitch constraints, also described in more detail below, may be any statement that, when implemented, sets a maximum or minimum value related to the pitch of the rotor blades 22 of the wind turbine 10 when input into the model implemented by the control system 26. These maximum or minimum values ​​may be absolute values, or they may be modified values ​​that can be changed based on real-time data analysis.

[0067] As shown at (110), method 100 also includes determining a pitch adjustment factor, determined via control system 26, for modifying the current state of wind turbine 10. The pitch adjustment factor may be an algorithm, formula, or rule that, when input to a model implemented by control system 26, promotes or hinders results (when it relates to pitch control of wind turbine 10). For example, the pitch adjustment factor may include one or more weights in a cost function (i.e., formula (1)) that, when implemented, increase or decrease the behavior exhibited by the wind turbine. The pitch adjustment factor may also include terms in the cost function, such as performance signals and reference signals, or results derived from the use of performance signals and reference signals. These terms may relate to the control of factors such as whether symmetrical or asymmetrical pitch is implemented, or whether harmonic activity is reduced. When it relates to formula (1), the pitch adjustment factor may also result in the minimization of the output J of the cost function when used.

[0068] Multiple pitch control factors, such as two or more, can be identified, which can collectively promote or hinder one or more results (when they relate to the pitch control of the wind turbine 10). For example, now referring to... Figure 8 The present disclosure illustrates a diagram of an embodiment of a multi-objective model for determining an optimized state 308 of the wind turbine 10. By providing optimized pitch parameters, the wind turbine 10 can be operated at the optimized state 308, as will be described in more detail below. Generally, an optimized state can indicate that the control of the wind turbine 10 is improved, or that the behavior exhibited by the wind turbine is reduced.

[0069] like Figure 8 As shown, the results or outputs of the multi-objective model 300 are provided along the axes of the multi-objective model 300. Specifically, the first possible output (provided on the x-axis 300) is the optimization of the annual power generation (AEP) of the wind turbine 10, i.e., increasing the AEP of the wind turbine. The second possible output (provided on the y-axis 304) is the optimization of the load acting on the wind turbine 10, i.e., reducing the total load acting on the wind turbine 10. As described, the load to be optimized can be any load acting on the wind turbine 10, such as fatigue load or extreme / peak load. The third possible output (provided on the z-axis 306) is the optimization of bearing life utilization (BLU), i.e., improving the bearing life of the wind turbine 10 by reducing bearing life utilization.

[0070] Therefore, as shown, the optimized pitch parameter state 308 can lead to a reduction in load on the wind turbine 10, a decrease in bearing life utilization (such as the bearing life of the pitch bearing 46), and / or an increase in AEP. Specifically, a single output can be achieved without emphasizing other outputs while mitigating detrimental effects. Such outputs can be readily observed with respect to the starting point 314. For example, as shown at point 316, the control system 26 can facilitate a maximum reduction in bearing life utilization while maintaining AEP with respect to point 314. At point 312, a maximum increase in AEP can be provided while reducing the total bearing life utilization required for such an increase with respect to point 314. At point 310, the load can be minimized while maintaining AEP with respect to point 314. In addition to reducing load, decreasing bearing life utilization, or increasing power generation, the use of pitch adjustment factors can also provide improvements in power quality (i.e., a reduction in power oscillations or harmonic levels), power tracking performance, or speed tracking performance. Each of these improvements in the control of the wind turbine 10 can be achieved by using pitch adjustment factors and pitch constraints as described herein.

[0071] For example, in an embodiment, the pitch adjustment factor may be a weight for symmetrical or asymmetrical pitch activities. As described, symmetrical pitch or total pitch is defined as when all rotor blades 22 have the same pitch motion. Conversely, asymmetrical pitch or periodic pitch is when rotor blades 22 have different pitch motions from each other. Symmetrical pitch activities can be controlled respectively using the following formulas (2)-(4): Where W is the weighting factor. θ 1k θ 2k and θ 3k It is the pitch angle of each rotor blade 22. It is the pitch rate of each rotor blade 22, and It is the pitch acceleration of each rotor blade 22.

[0072] As shown, when the weighting factor W increases, the symmetrical pitch activity of the wind turbine 10 decreases. Conversely, when the weighting factor W decreases, the symmetrical pitch activity of the wind turbine 10 increases.

[0073] In contrast to the symmetric pitch control provided by formulas (2)-(4), the asymmetric pitch activity can be controlled by using the following formulas (5)-(7): Where W is the weighting factor. θ 1k θ 2k and θ3k It is the pitch angle of each rotor blade 22. θ ik This represents the pitch angle of the i-th rotor blade 22 at the k-th time step within the prediction range. and This is the pitch rate of each rotor blade 22. This represents the pitch rate of the i-th rotor blade 22 at the k-th time step within the prediction range. and It is the pitch acceleration of each rotor blade 22, and This represents the pitch acceleration of the i-th rotor blade 22 at the k-th time step within the prediction range.

[0074] As shown, the asymmetric pitch activity of the wind turbine 10 decreases when the weighting factor W increases. Conversely, the asymmetric pitch activity of the wind turbine 10 increases when the weighting factor W decreases.

[0075] Now refer to Figure 9A and 9B A graph showing the effect of applying pitch adjustment factors to provide asymmetric and symmetric pitch control. (Example) Figure 9A The graph 400 shown provides the pitch curves for each rotor blade 402, 404, and 406. (See graph 400 for details.) Figure 9B The graph 450 shown provides a curve depicting the loads placed on the same rotor blades 402, 404, and 406. Specifically, in... Figure 9A In the graph, the pitch of each rotor blade 402, 404, 406 is provided on the y-axis 408 and plotted over time, which is placed on the x-axis 410 of the graph 400. Figure 9B In this process, the load placed on each rotor blade 402, 404, 406 is provided on the y-axis 452, and along with... Figure 9A The same time was plotted, which is placed on the x-axis 454 of Figure 450.

[0076] In addition, such as Figure 9B As shown, the loads applied to rotor blades 402, 404, and 406 are indicated as exceeding threshold 456 within box 458. To address this, control system 26 can actuate asymmetric or periodic pitch of rotor blades 402, 404, and 406, such as... Figure 9AAs shown in box 412. Specifically, the reduction of the weight W provided in formulas (5)-(7) is implemented by actuating asymmetric or periodic pitch. Thus, a difference in pitch angle is provided between rotor blades 402, 404, 406, which causes rotor blades 402, 404, 406 to operate out of phase with each other, as shown in box 412. Due to this difference in pitch between rotor blades 402, 404, 406, the load placed on rotor blades 402, 404, 406 is reduced to below threshold 456, as shown in box 460. Thus, the load can be reduced by using asymmetric or periodic pitch, which leads to an increase in the difference in pitch angle between rotor blades 402, 404, 406. In addition, as Figure 9A and 9B As shown, once the load placed on rotor blades 402, 404, and 406 falls below a threshold 456, symmetrical pitch can be employed, as shown in box 414. Since load reduction is achieved using asymmetrical pitch, this strategy results in additional power generation compared to the standard approach of handling blade loads by increasing total pitch. In this way, an appropriate combination of the weights of symmetrical and asymmetrical pitch can achieve the desired behavior: periodic pitch when load reduction is critical, and symmetrical pitch in other situations.

[0077] Therefore, by using the weights W in formulas (2)-(7), it is feasible to finely adjust the pitch parameters of the wind turbine 10 and rotor blades 22 to achieve an optimal trade-off between load reduction, BLU savings, and power generation. Specifically, by utilizing these increases or decreases in the cost function, optimal utilization of total or asymmetric pitch action can be achieved to address any particular load constraints. Further customization can be achieved by arranging the weighting factors according to an operating parameter such as wind speed or wind turbulence intensity.

[0078] In another embodiment, the pitch adjustment factor may correspond to the amplitude of harmonics higher than the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration. Specifically, the pitch adjustment factor may be a weight that, when applied, reduces the amplitude of harmonics higher than the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration. For example, harmonics can be controlled using the following formula (8): Among them W s and W c All are weighting factors. θ k It is equal to the pitch angle of rotor blade 22 (which can also be calculated using pitch rate and pitch acceleration), λ is the wavelength, and k is the k-factor.

[0079] By providing a weight that reduces the amplitude of harmonics above the fundamental frequency, higher-order harmonics can be reduced or completely eliminated from being exhibited by the rotor blades 22 of the wind turbine 10. If desired, the weight can be applied to all rotor blades 22. Alternatively, if a particular rotor blade 22 operates at a higher frequency for its pitch angle, pitch rate, or pitch acceleration compared to the second rotor blade 22, the reduction can be applied to the particular rotor blade 22 operating at the higher frequency.

[0080] In the example, when utilizing higher-order harmonics in pitch control (which can drive excessive BLU), the weight W is appropriately selected. s and W c Allowing the penalty of specific Fourier components of the pitch trajectory, which is related to pitch bearing life management. Specifically, when the weight W is increased... s and W c At this time, the amplitude of higher-order harmonics can be reduced. Therefore, the pitch bearing life can be improved by selecting a pitch adjustment factor that results in a reduction in the amplitude of harmonics above the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration. For example, if the user needs to remove harmonic components from the pitch trajectory, the user can use formula (8) to increase the weight W. s and W c To punish these higher-order harmonics.

[0081] Specifically, and referring to Figure 10A-10D Various charts are shown to demonstrate the effectiveness of formula (8) in identifying the high harmonic components of the pitch signal. Figure 10A The graph 500 shows the fundamental frequencies of a high-frequency signal 502 and a low-frequency signal 504 for the pitch angle, pitch rate, or pitch acceleration of one or more rotor blades 22; while Figure 10B-10D The graphs 520, 540, and 560 are shown, providing the first, second, and third harmonics of the fundamental frequency of the high-frequency signal 502 and the low-frequency signal 504. Specifically, for Figure 10A-10D For each of the curves 500, 520, 540, and 560 provided, the y-axis 506 is the pitch angle of one or more rotor blades 22, while the x-axis 508 is the phase of one or more rotor blades 22.

[0082] Additionally, as shown, Figure 10B-10D The curves 520, 540, and 560 show the first, second, and third harmonics of the two signals 502 and 504 applied by formula (8). Specifically, as shown, formula (8) applies a low level to the first harmonic. Additionally, in Figure 10B As shown in graph 520, at the first harmonic, the penalties for high-frequency signal 502 and low-frequency signal 504 are equal or approximately the same. However, as... Figure 10C-10DAs shown in graphs 540 and 560, the second and third harmonics are practically zero for the low-frequency signal 504, while they are high for the high-frequency signal 502. Therefore, it can be seen that by selecting the weight W in formula (8)... s and W c This can reduce or completely eliminate higher-order harmonics of high-frequency signals. Therefore, it can reduce higher-order harmonics of higher-frequency signals, and thus improve the life of the pitch bearing of the wind turbine 10.

[0083] In another embodiment, the pitch adjustment factor can be a linear or quadratic penalty term at a future time interval. For example, a linear penalty term can be provided at a future time interval using the following formula (9): P=Σθ k w k (9) Where θ k Equal to the pitch angle, and W k It is a weighting factor.

[0084] In addition, the secondary penalty term can be provided at future time intervals using the following formula (10): P=(Σθ k w k ) 2 (10) Where θ k Equal to the pitch angle, and W k It is a weighting factor.

[0085] Both linear and quadratic penalty terms can be applied at any time interval for future time intervals. For example, the penalty term can be applied at sampling time 204 ( Figure 7 The penalty is applied at the location specified in the original text. Additionally, linear and quadratic penalties can vary across multiple time intervals. However, it should be understood that while the term "penalty" is used, corresponding rewards can also be utilized to encourage activity or enhance the behavior exhibited by the wind turbine 10.

[0086] In another embodiment, the pitch constraint can be a linear constraint or a quadratic constraint at a future time interval. For example, a linear constraint can be provided at a future time interval using the following formula (11): LB≤Σθ k w k ≤UB (11) Where θ k Equal to the pitch angle, W k It is a weighting factor. L B It is the lower limit, and U B That is the upper limit.

[0087] In addition, the quadratic constraint can be provided at future time intervals using the following formula (12): LB≤Σ(θ k w k ) 2 ≤UB (12) Where θ k Equal to the pitch angle, W k It is a weighting factor. L B It is the lower limit, and U B That is the upper limit.

[0088] Similar to the penalty term, linear and quadratic constraints can also be provided at multiple future time intervals and vary across multiple future time intervals.

[0089] In another embodiment, the pitch adjustment factor may also include the pitch angle, pitch rate, or variance or tracking of pitch acceleration of one or more of the rotor blades 22.

[0090] Each of these penalties, constraints, variances, or tracking can provide finer adjustments to any of the other pitch control factors provided. Specifically, the use of other pitch control factors can be controlled more efficiently by providing any of the penalty terms or constraints corresponding to Equations (9)-(12).

[0091] In another embodiment, the pitch constraint may be a maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration of at least one rotor blade 22. For example, the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration may be implemented using formulas (13)-(15), respectively: LB≤θ ik ≤UB (13) Where θ ik Equal to the pitch angle, It is the pitch rate. It is pitch acceleration. LB, rLB, and aLB are the lower limits of pitch angle, pitch rate, and pitch acceleration, respectively. UB, rUB, and aUB are the upper limits for pitch angle, pitch rate, and pitch acceleration, respectively.

[0092] Physical limits or upper limits can be imposed on the pitch activity of rotor blades 22 by using the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration as described herein. Specifically, the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration can be set using formulas (11)-(13). As described, the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration can be modified based on protection logic. For example, if conditions such as wind conditions require a lower maximum permissible pitch angle, pitch rate, or pitch acceleration, the control system 26 may include protection logic defined by the control system 26 that instructs the wind turbine 10 to reduce the maximum pitch angle, pitch rate, or pitch acceleration. Thus, depending on the conditions present around the wind turbine 10, the protection logic can increase or decrease the maximum and minimum permissible pitch angle, pitch rate, or pitch acceleration of the rotor blades 22 of the wind turbine 10. Furthermore, if the conditions that caused the protection logic to be implemented no longer exist, the control system 26 can restore the maximum or minimum allowable pitch angle, pitch rate, or pitch acceleration of the rotor blades 22 to their values ​​before the protection logic was implemented. Therefore, it is understood that the protection logic can be temporarily activated depending on the conditions existing around the wind turbine 10.

[0093] In another embodiment, the pitch constraint may correspond to the maximum or minimum permissible pitch motor torque, current, voltage, or power. Such constraints may provide protection for the electrical components of the wind turbine 10, such as the pitch drive motor 40.

[0094] Additionally, if flexibility in these maximum or minimum permissible values ​​is desired, increases or decreases in input or output constraints can be utilized. For example, increases or decreases in maximum pitch angle, pitch rate, or pitch acceleration, or increases or decreases in minimum pitch angle, pitch rate, or pitch acceleration, can be provided. In another instance, increases or decreases in maximum permissible pitch motor torque, current, voltage, or power, or increases or decreases in minimum permissible pitch motor torque, current, voltage, or power, can be provided. Increases or decreases can be applied at one or more future time intervals and vary across multiple future time intervals, where the inequalities defining the constraints can be required to be satisfied at each or multiple future time intervals. For example, increases in input and output constraints can be provided according to the following formula (16): 0≤∈ L 0≤∈ U (16)) Where y cin Equals input constraints, y cout Equals output constraints, UB ycinIt is the upper limit of the input constraints. UB ycout It is the upper limit of the output constraint, and ∈ U It is a placeholder for the increase of the upper limit.

[0095] Furthermore, the reduction in input and output constraints can be provided according to the following formula (17): 0≤∈ L 0≤∈ U (17) Where y cin Equals input constraints, y cout Equals output constraints, LB ycin It is the upper limit of the input constraints. LB ycout It is the lower bound of the output constraint. ∈ U These are slack variables used in the final case of a bounds violation, and ∈ L It is a slack variable used in the final case where the lower bound is violated.

[0096] As shown, the placeholder ∈ U or ∈ L It can act as a slack variable for constraints. Additionally, the placeholder ∈ U or ∈ L Can be an absolute term. Placeholder ∈ U or ∈ L It can also be used for any other term recognized in the art to provide an increase or decrease in the upper or lower bound of the expected value. For example, placeholder ∈ U or ∈ L It can also be an adaptation term, which changes in real time based on the conditions around the wind turbine 10. Specifically, weights can also be applied to slack variables to provide better control over the constraints. In addition, increases or decreases can be applied at future time intervals in response to the operating conditions of the wind turbine 10 (such as those received by the sensors of the wind turbine 10).

[0097] In another embodiment, the pitch adjustment factor may be one or more variance penalties for the pitch angle, pitch rate, or pitch acceleration of at least one rotor blade 22. For example, the variance penalty can be provided according to the following formula (18): Where θ k It is equal to the pitch angle of a single rotor blade 22 (and can also be calculated using pitch rate and acceleration), and It is equal to the average value of all rotor blades 22 of the wind turbine 10.

[0098] In yet another embodiment, the pitch adjustment factor may be one or more penalties for the total pitch angle change of at least one rotor blade 22 (i.e., the total angle traveled by each rotor blade 22 or all rotor blades 22 together). For example, the total pitch angle change may be penalized according to the following formula (19): in Equal to pitch change or pitch rate, i is the leaf index. N is the prediction range, i.e., the time during which the control system 26 is set to estimate the expected state, and W is the weighting factor.

[0099] In this embodiment, the benefit of penalizing total pitch variation, for example by increasing the weighting factor W in Equation (17), is that the control system 26 can prevent micro-pitch variations, which are small movements of the blade pitch that significantly contribute to bearing life loss without much benefit to load reduction. Furthermore, Equation (17) will not prevent necessary control actions during gust events. Additionally, Equation (17) will also unduly penalize large deviations in the pitch angle, especially when compared to other conventional methods. Examples of such scenarios include gust events where the pitch should be rapidly increased to reduce load, or sudden drops in wind speed where the pitch should be rapidly decreased to capture more energy.

[0100] In another embodiment, the pitch adjustment factor may be a penalty for the product of the pitch travel for at least one rotor blade 22 and the magnitude of the load on at least one rotor blade 22.

[0101] Refer back Figure 6 As shown at (112), method 100 includes calculating optimized pitch parameters of at least one rotor blade 22 of the wind turbine 10 from a linearized representation using a pitch adjustment factor and pitch constraints via an optimization solver implemented in the control system. Specifically, the optimized pitch parameters may be a solution to an optimization problem that results in the minimization of a cost function. For example, the optimized pitch parameters may be an output in the form of a trajectory of the pitch angle, pitch rate, or pitch acceleration of at least one of the rotor blades 22. The optimized pitch parameters may also be the optimized torque of the rotor 18 of the wind turbine 10.

[0102] When determining the optimal pitch parameters, the model can use a pitch adjustment factor to determine the pitch parameters of at least one rotor blade 22 to achieve the desired result, as described above. Figure 8The results described. For example, such results may lead to an increase or decrease in the behavior exhibited by the wind turbine 10, resulting in an improvement in the pitch control of the wind turbine 10. Such behavior, which will be described in more detail below, may include symmetrical or asymmetrical pitch, higher-order harmonics in pitch activity, or operating the wind turbine 10 beyond set constraints or limits.

[0103] Additionally, as described above, multiple pitch adjustment factors can be used to determine optimized pitch parameters to achieve one or more results. The determination of optimized pitch parameters can be achieved by modifying the linearized representation of the expected state within the model using pitch adjustment factors to provide optimized pitch parameters. This determination can take the form of simulating the pitch parameters of wind turbine 10 being modified by control system 26 so that wind turbine 10 transitions from the expected state to the optimized state.

[0104] As shown at (114), method 100 includes adjusting the pitch parameter of at least one rotor blade 22 to an optimized pitch parameter that increases or decreases the behavior exhibited by the wind turbine 10 and improves the control of the wind turbine 10. By doing so, the rotor blade(s) 22 can be adjusted such that the rotor blade(s) 22 are modified to an optimized pitch parameter that achieves one or more results provided within the model.

[0105] In another embodiment, the torque of the rotor 18 of the wind turbine 10 can be adjusted to increase or decrease the behavior exhibited by the wind turbine 10 and improve the control of the wind turbine. By doing so, the rotor blades(s)22 can be adjusted such that the rotor 18 is modified to optimize the pitch parameters to achieve one or more results provided within the model.

[0106] Therefore, by using a model to simulate and optimize the pitch parameters and by using the control system 26 to adjust the wind turbine 10 to align with the optimized pitch parameters, the control of the wind turbine 10 can be optimized.

[0107] Furthermore, the control of the wind turbine 10 can be continuously optimized. For example, by updating the simulation of the expected state based on the adjustment of the pitch parameters of at least one rotor blade 22, the model may be able to simulate new expected states and use those new expected states to further determine the optimal state that the wind turbine 10 can match. Therefore, this disclosure provides a system and method for continuously optimizing pitch control using a control system 26.

[0108] For example, now refer to Figure 11A-11B Various graphs are provided for the pitch adjustment factor in response to peak load intervals according to embodiments of the present disclosure. Figure 11A As shown in 11B, the load can be increased or decreased. Specifically, such as Figure 11A-11BAs shown, graphs 600 and 650 provide the load and weighting factors placed on one or more rotor blades 22 on the y-axis 602 and 652, while the x-axis 604 and 654 provide the wind speed acting on one or more rotor blades 22. Additionally, Figure 11A Peak load interval 606 is provided at a location on its graph 600, while Figure 11B Peak load interval 656 is provided at another location on its curve 650. Furthermore, the peak load interval coincides with the minimum weighting factor intervals 608 and 658. Specifically, as... Figure 11A As shown, the peak load interval 606 is achieved at the minimum weight factor interval 608. (As indicated...) Figure 11B As shown, peak load interval 656 is achieved at minimum weighting factor interval 658. These peak load intervals 606, 656 and minimum weighting factor intervals 608, 658 can be provided at different wind speeds. Conversely, due to the heavier application of weighting factors, the load is reduced in the portions outside the peak load intervals 606, 656 and minimum weighting factor intervals 608, 658. Therefore, as previously described, these loads can be mitigated by using a pitch control factor that includes weighting factors. In the example, increasing the difference between pitch angle, pitch rate, or pitch acceleration can help reduce loads such as... Figure 9B The load shown in the image, such as that generated by Figure 11A or Figure 11B As shown. Pitch constraints can also be used for further enhancement. Figure 11A-11B The controls displayed in the middle.

[0109] Now refer to Figure 12A-12D Various graphs are provided showing the effects of applying pitch adjustment factors and pitch constraints according to embodiments of the present disclosure to increase or maintain differences in the pitch parameters of the rotor blades of a wind turbine. As shown, the pitch parameters may be power, pitch angle, generator torque, or pitch speed, where solid lines represent control using the pitch adjustment factor with pitch control system 26, and dashed lines represent pitch control according to conventional means.

[0110] Specifically, such as Figure 12A The graph 700 shows the power generated using control system 26 compared to the conventional method. Furthermore, as shown, power is provided on the y-axis 702, while time is plotted on the x-axis 704. Additionally, the conventional method is indicated by line 706, while the method using control system 26 is indicated by line 708. Moreover, as shown, line 706, indicating the conventional method, has a deeper valley and is consistently lower than line 708, indicating the method using control system 26. Therefore, it can be seen that the method using control system 26 provides improved power generation compared to the conventional method.

[0111] like Figure 12BThe graph 720 shows the pitch angle of the rotor blades 22 using control system 26 compared to the conventional method. Furthermore, as shown, the pitch angle of one or more rotor blades 22 is provided on the y-axis 722, while time is plotted on the x-axis 724. Additionally, the conventional method is indicated by line 726, while the method using control system 26 is indicated by line 728. Furthermore, as shown, line 726, indicating the conventional method, has a more unstable pattern compared to line 728, indicated by a greater number of peaks and troughs. Therefore, it can be seen that the method described herein provides better control over the pitch angle movement of the rotor blades 22 compared to the conventional method.

[0112] like Figure 12C The graph 740 shows the generator torque compared to the conventional method using control system 26. Furthermore, as shown, the generator torque is provided on the y-axis 742, while time is plotted on the x-axis 744. Additionally, the conventional method is indicated by line 746, while the method using control system 26 is indicated by line 748. Moreover, as shown, line 746, indicating the conventional method, has a deeper valley and is consistently lower than line 748, indicating the method using control system 26. Therefore, it can be seen that the method described herein provides improved generator torque compared to the conventional method.

[0113] like Figure 12D The graph 760 shows the rotor speed of the wind turbine 10 using control system 26 compared to the conventional method. Furthermore, as shown, the rotor speed is provided on the y-axis 762, while time is plotted on the x-axis 764. Additionally, the conventional method is indicated by line 706, while the method using control system 26 is indicated by line 768. Furthermore, as shown, when compared to line 768 indicating the method using control system 26, line 766 indicating the conventional method has a larger peak and a deeper valley. Therefore, it can be seen that, compared to the conventional method, the method using control system 26 provides improved control of the rotor speed of the wind turbine 10. Therefore, as shown, when compared to the conventional control method, pitch control can be smoother and more optimized by using the control method described herein.

[0114] Various aspects and embodiments of the present invention are defined by the following numbered clauses: Clause 1. A method for optimizing the control of a wind turbine, the method comprising: The control system receives at least one status of the wind turbine; The current state of the wind turbine is estimated using the at least one condition via the control system; A linearized representation of the operation of the wind turbine is calculated via a model implemented by the control system for future time intervals following the current state; The optimization problem to be solved is defined by the control system, wherein the optimization problem includes a cost function and a pitch constraint; The control system determines a pitch adjustment factor for modifying the current state of the wind turbine, wherein the pitch adjustment factor includes at least one weight in the cost function, which, when implemented, increases or decreases the behavior exhibited by the wind turbine, wherein the cost function is implemented in an optimization solver implemented by the control system. Optimal pitch parameters for at least one rotor blade of the wind turbine are calculated from the linearized representation using the pitch adjustment factor and the pitch constraints via the optimization solver implemented in the control system, wherein the optimized pitch parameters are a solution to the optimization problem; and The pitch parameter of the at least one rotor blade is adjusted to the optimized pitch parameter, such that the behavior exhibited by the wind turbine increases or decreases, and the control of the wind turbine is improved. Clause 2. The method according to Clause 1, wherein the at least one condition includes at least one measurement of rotor speed, generator speed, wind speed, wind direction, wind shear, wind direction, wind turbulence, structural force or moment, structural displacement, structural velocity or structural acceleration. Clause 3. The method according to any one of Clauses 1-2, wherein the current state of the wind turbine includes transient aerodynamic effects distributed across a portion of the wind turbine, wherein the transient aerodynamic effects include at least one of a force or torque acting on the portion of the wind turbine; or The current state of the wind turbine includes transient structural effects across a portion of the wind turbine, wherein the transient structural effects include at least one of structural displacement, structural velocity, or structural acceleration of any structural component of the wind turbine. Clause 4. The method according to any of the preceding clauses, wherein the improvement in the control of the wind turbine includes: a reduction in load on the wind turbine, an increase in expected bearing life, an increase in power generation, an improvement in power quality, an improvement in power point tracking performance, or an improvement in speed point tracking performance. Clause 5. The method according to Clause 4, wherein the optimized pitch parameters include the pitch angle, pitch rate, or pitch acceleration trajectory of at least one rotor blade of the wind turbine. Clause 6. The method according to any of the preceding clauses, wherein the weight corresponds to the symmetrical pitch motion of the at least one rotor blade of the wind turbine. Clause 7. The method according to any of the preceding clauses, wherein the weight corresponds to the asymmetric pitch motion of the at least one rotor blade of the wind turbine. Clause 8. The method according to any of the preceding clauses, wherein the weight corresponds to the amplitude of a harmonic of the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration of the at least one rotor blade. Clause 9. The method according to Clause 8, wherein the at least one rotor blade comprises a first rotor blade and a second rotor blade. The pitch angle, pitch rate, or pitch acceleration of the first rotor blade includes a frequency higher than that of the pitch angle, pitch rate, or pitch acceleration of the second rotor blade. The weights applied to the pitch angle, pitch rate, or pitch acceleration of the first rotor blade reduce the amplitude of the harmonics at the fundamental frequency higher than the pitch angle, pitch rate, or pitch acceleration. Clause 10. The method according to any of the preceding clauses, wherein the pitch adjustment factor includes one of a linear term or a quadratic term at the future time interval; The pitch constraint mentioned above includes a linear constraint or a quadratic constraint at the future time interval; or The pitch adjustment factor includes the pitch angle, pitch rate, or variance or tracking of the pitch acceleration of at least one rotor blade. Clause 11. The method according to any of the preceding clauses, wherein the pitch constraint corresponds to the maximum or minimum allowable pitch angle, pitch rate, or pitch acceleration of the at least one rotor blade; or The pitch constraint corresponds to the maximum or minimum allowable pitch motor torque, current, voltage, or power. Clause 12. The method according to Clause 11, wherein the pitch constraint further includes an increase or decrease in the maximum permissible pitch angle, pitch rate, or pitch acceleration of the at least one rotor blade, or a decrease or increase in the minimum permissible pitch angle, pitch rate, or pitch acceleration of the at least one rotor blade, wherein the increase or decrease in the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration is applied at the future time interval in response to at least one received condition; or The pitch constraint further includes the maximum permissible increase or decrease in pitch motor torque, current, voltage, or power, or the minimum permissible decrease or increase in pitch motor torque, current, voltage, or power, wherein the increase or decrease in the maximum or minimum permissible pitch angle, pitch rate, or pitch acceleration is applied at the future time interval in response to at least one received condition. Clause 13. The method according to any of the preceding clauses, wherein the pitch adjustment factor comprises two or more pitch adjustment factors, wherein the optimized pitch parameter of the at least one rotor blade is calculated using the two or more pitch adjustment factors and the pitch constraint. Clause 14. The method according to any of the preceding clauses, wherein the pitch adjustment factor includes one or more penalties for the total pitch angle variation of the at least one rotor blade, or a penalty for the product of the pitch travel of the at least one rotor blade and the magnitude of the load on the at least one rotor blade. Clause 15. The method described according to any one of the preceding clauses, the method further comprising: The optimized torque of the wind turbine rotor is calculated from the linearized representation using the pitch adjustment factor and the pitch constraints via the optimization solver implemented in the control system; and Adjusting the rotor torque to the optimized torque increases or decreases the behavior exhibited by the wind turbine and improves the control of the wind turbine. Clause 16. A system for optimizing the control of a wind turbine, the system comprising: At least one sensor configured to monitor at least one condition of the wind turbine; The control system is configured as follows: Receive at least one of the conditions of the wind turbine; The wind vortex is estimated using the at least one condition via the control system. The current state of the wheel; A linearized representation of the operation of the wind turbine is calculated via a model implemented by the control system for future time intervals following the current state; The optimization problem to be solved is defined by the control system, wherein the optimization The problems include cost functions and pitch constraints; The control system determines a pitch adjustment factor for modifying the current state of the wind turbine, wherein the pitch adjustment factor includes at least one weight in the cost function, which, upon implementation, increases or decreases the behavior exhibited by the wind turbine, wherein the cost function is used in the optimization performed by the control system. Implemented in the decoder; The optimized pitch parameters of at least one rotor blade of the wind turbine are calculated from the linearized representation using the pitch adjustment factor and the pitch constraints via the optimization solver implemented in the control system, wherein the optimized pitch parameters... It is the solution to the optimization problem; and The pitch parameter of the at least one rotor blade is adjusted to the optimized pitch parameter, such that the behavior exhibited by the wind turbine increases or decreases, and the control of the wind turbine is improved. Clause 17. The system according to Clause 16, wherein the at least one condition includes at least one measurement of rotor speed, generator speed, wind speed, wind direction, wind shear, wind direction, wind turbulence, structural force or moment, structural displacement, structural velocity or structural acceleration. Clause 18. A system according to any one of Clauses 16-17, wherein the current state of the wind turbine includes transient aerodynamic effects distributed across a portion of the wind turbine, wherein the transient aerodynamic effects include at least one of a force or torque acting on the portion of the wind turbine; or The current state of the wind turbine includes transient structural effects across a portion of the wind turbine, wherein the transient structural effects include at least one of structural displacement, structural velocity, or structural acceleration of any structural component of the wind turbine. Clause 19. The system according to any one of Clauses 16-18, wherein the weights correspond to the symmetrical or asymmetrical pitch motion of the at least one rotor blade of the wind turbine. Clause 20. The system according to any one of Clauses 16-19, wherein the weight corresponds to the amplitude of a harmonic higher than the fundamental frequency of the pitch angle, pitch rate, or pitch acceleration of the at least one rotor blade.

[0115] This written description uses examples to disclose the invention (including the best mode) and also enables those skilled in the art to practice the invention (including making and using any device or system and performing any incorporated methods). The patentable scope of the invention is defined by the claims and may include other examples that may occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they include structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are not significantly different from the literal language of the claims.

Claims

1. A method for optimizing control of a wind turbine, the method comprising: receiving, via a control system, at least one condition of the wind turbine; estimating, via the control system, a current state of the wind turbine using the at least one condition; computing, via a model implemented by the control system, a linearized representation of operation of the wind turbine for a future time interval following the current state; defining, via the control system, an optimization problem to be solved, wherein the optimization problem comprises a cost function and a pitch constraint; determining, via the control system, a pitch adjustment factor for modifying the current state of the wind turbine, wherein the pitch adjustment factor comprises at least one weight in the cost function that, when implemented, increases or decreases behavior exhibited by the wind turbine, wherein the cost function is implemented in an optimization solver implemented by the control system; computing, via the optimization solver implemented in the control system, an optimized pitch parameter for at least one rotor blade of the wind turbine from the linearized representation using the pitch adjustment factor and the pitch constraint, wherein the optimized pitch parameter is a solution to the optimization problem; and adjusting a pitch parameter of the at least one rotor blade to the optimized pitch parameter such that the behavior exhibited by the wind turbine is increased or decreased and the control of the wind turbine is improved.

2. The method of claim 1, wherein, the at least one condition comprises at least one measurement of rotor speed, generator speed, wind speed, wind direction, wind shear, wind veer, wind turbulence, structural force or moment, structural displacement, structural speed, or structural acceleration.

3. The method of claim 1, wherein, the current state of the wind turbine comprises an instantaneous aerodynamic effect distributed across a portion of the wind turbine, wherein the instantaneous aerodynamic effect comprises at least one of a force or moment acting on the portion of the wind turbine; or wherein the current state of the wind turbine comprises an instantaneous structural effect across a portion of the wind turbine, wherein the instantaneous structural effect comprises at least one of a structural displacement, structural speed, or structural acceleration of any structural member of the wind turbine.

4. The method of claim 1, wherein, the improvement in the control of the wind turbine comprises a decrease in load on the wind turbine, an increase in bearing life expectancy, an increase in power production, an improvement in power quality, an improvement in power tracking performance, or an improvement in speed tracking performance.

5. The method of claim 4, wherein, the optimized pitch parameter comprises a pitch angle, a pitch rate, or a pitch acceleration trajectory of the at least one rotor blade of the wind turbine.

6. The method of claim 1, wherein, the weight corresponds to a symmetric pitch motion of the at least one rotor blade of the wind turbine.

7. The method of claim 1, wherein, the weight corresponds to an asymmetric pitch motion of the at least one rotor blade of the wind turbine.

8. The method of claim 1, wherein, the weight corresponds to an amplitude of a harmonic higher than a fundamental frequency of the pitch angle, the pitch rate, or the pitch acceleration of the at least one rotor blade.

9. The method of claim 8, wherein, the at least one rotor blade comprises a first rotor blade and a second rotor blade, wherein the pitch angle, the pitch rate, or the pitch acceleration of the first rotor blade comprises a higher frequency than the pitch angle, the pitch rate, or the pitch acceleration of the second rotor blade, wherein the weight is applied to the pitch angle, the pitch rate, or the pitch acceleration of the first rotor blade such that the amplitude of the harmonics of the base frequency higher than the pitch angle, the pitch rate, or the pitch acceleration is reduced.

10. The method of claim 1, wherein, the pitch adjustment factor comprises one of a linear term or a quadratic term at the future time interval; wherein the pitch constraint comprises a linear constraint or a quadratic constraint at the future time interval; or wherein the pitch adjustment factor comprises a variance or a tracking of a pitch angle, a pitch rate, or a pitch acceleration of the at least one rotor blade.

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