System and method for compensating for rotor imbalance in wind turbine

Abstract

The present disclosure relates to a method of compensating for rotor imbalance of a wind turbine. The method includes receiving, via a processor of a controller of the wind turbine, a signal associated with an acceleration of the tower and a signal associated with a position of the rotor. The method also includes estimating a rotor imbalance based on a signal associated with the acceleration of the tower. The method further includes estimating a component of the rotor imbalance with respect to the rotor position via an adaptive filtering algorithm. The method further includes calculating a respective pitch angle offset of a rotor blade of the wind turbine based on the estimated component of the rotor imbalance. The method further includes adjusting the pitch angle of each of the rotor blades by a respective pitch angle offset, thereby reducing a first excitation amplitude disturbance with respect to acceleration of the tower.

Description

Technical Field

[0001] This disclosure generally relates to wind turbines, and more particularly to systems and methods for compensating for rotor imbalances in wind turbines to reduce or minimize undesirable tower motion caused by such imbalances. 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, the blades of a wind turbine 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, 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] Factors that can cause fluctuations in the load on rotor blades include manufacturing tolerances, pitch installation misalignment, blade icing, and blade airfoil roughness. Such variability in rotor blade loading leads to tower movement, particularly in the lateral direction, which accelerates tower wear and reduces operating margins. Therefore, in tower configurations, it is useful to ensure good rotor balance so that operation can approximate the natural frequency of the wind turbine tower.

[0005] In view of the foregoing, this disclosure relates to systems and methods for resolving rotor imbalance so as to significantly reduce or eliminate the variability of forces exerted by the rotor blades. Summary of the Invention

[0006] The aspects and advantages of this disclosure will be set forth in part in the description which follows, or may be apparent from the description, or may be learned by practice of this disclosure.

[0007] In one aspect, this disclosure relates to a method for compensating for rotor imbalance in a wind turbine. The method includes receiving, via a processor of a wind turbine controller, at least one signal associated with acceleration of the wind turbine tower and at least one signal associated with the position of the wind turbine rotor. The method further includes estimating rotor imbalance based on the at least one signal associated with tower acceleration. The method further includes estimating a component of rotor imbalance with respect to rotor position via an adaptive filtering algorithm programmed in the processor of the controller. The method further includes calculating, via the controller, corresponding pitch angle offsets of a plurality of rotor blades of the wind turbine based on the estimated components of the rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades are configured to reduce a first excitation amplitude of the rotor imbalance. The method further includes, via the controller, adjusting the pitch angle of each of the plurality of rotor blades according to the corresponding pitch angle offset, thereby reducing disturbance to the first excitation amplitude with respect to tower acceleration.

[0008] In embodiments of the method, at least one signal associated with the acceleration of the wind turbine tower includes lateral acceleration of the tower due to the tower's natural frequency and rotor imbalance, and the first excitation amplitude includes a portion of the tower's lateral acceleration due to rotor imbalance.

[0009] In an embodiment, the method further includes filtering the acceleration signal via an inverse model of tower dynamics to remove the lateral acceleration of the tower caused by the natural frequency of the tower from at least one signal associated with the tower's acceleration.

[0010] In one embodiment, the method further includes dividing the acceleration of the wind turbine's filter tower by the square of the wind turbine's rotor speed.

[0011] In embodiments of the method, the adaptive filtering algorithm includes recursive least squares (RLS).

[0012] In embodiments of the method, the estimated components of rotor imbalance include sine and cosine components of rotor position.

[0013] In embodiments of the method, estimating the rotor imbalance component with respect to rotor position via an adaptive filtering algorithm programmed in the controller's processor includes estimating the rotor imbalance component at multiple wind speeds or air densities at the wind turbine or at multiple rotor speeds or power levels of the wind turbine.

[0014] In one embodiment, the method further includes a proportional controller programmed in the processor of the controller to calculate the corresponding pitch angle offset of the plurality of rotor blades of the wind turbine based on the estimated component of rotor imbalance.

[0015] In an embodiment of the method, calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated components of rotor imbalance further includes: using at least one of wind speed or air density at the wind turbine or rotor speed or power level of the wind turbine, and torque at the base of the rotor imbalance calculation tower; and determining the corresponding pitch angle offset of each of the plurality of rotor blades, which corresponds to the minimum standard deviation of the torque at the base of the tower, such that the sum of the corresponding pitch angle offsets of each of the plurality of rotor blades is approximately equal to zero.

[0016] In an embodiment of the method, calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated components of rotor imbalance further includes: using at least one of wind speed or air density at the wind turbine or rotor speed or power level of the wind turbine, and calculating the torque at the base of the rotor imbalance tower; and determining the corresponding pitch angle offset of each of the plurality of rotor blades, which corresponds to the minimum standard deviation of the torque at the base of the tower, such that the sum of the corresponding pitch angle offsets of each of the plurality of rotor blades is approximately equal to zero.

[0017] In an embodiment of the method, calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated components of rotor imbalance further includes: calculating a component of each pitch angle offset of the plurality of rotor blades; and determining the corresponding pitch angle offset of the plurality of rotor blades using at least one of wind speed or air density at the wind turbine or rotor speed or power level of the wind turbine, and the component of each pitch angle offset.

[0018] In another aspect, this disclosure relates to a system for compensating for rotor imbalance in a wind turbine. The system includes a wind turbine comprising a tower, a rotor, and a plurality of rotor blades. The system also includes a controller communicatively coupled to the wind turbine, the controller including a processor. The controller is configured to receive, via the processor, at least one signal associated with acceleration of the wind turbine's tower and at least one signal associated with the position of the wind turbine's rotor. The controller is further configured to estimate rotor imbalance based on the at least one signal associated with the tower's acceleration. The controller is further configured to estimate a component of the rotor imbalance with respect to the rotor position via an adaptive filtering algorithm programmed in the controller's processor. The controller is further configured to calculate corresponding pitch angle offsets of the plurality of rotor blades of the wind turbine based on the estimated components of the rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades are configured to reduce a first excitation amplitude of the rotor imbalance. The controller is further configured to adjust the pitch angle of each of the plurality of rotor blades according to the corresponding pitch angle offset, thereby reducing disturbances to the first excitation amplitude with respect to the tower's acceleration. Technical Solution 1. A method for compensating for rotor imbalance in a wind turbine, the method comprising: The processor of the controller of the wind turbine receives at least one signal associated with the acceleration of the tower of the wind turbine and at least one signal associated with the position of the rotor of the wind turbine. The rotor imbalance is estimated based on the at least one signal associated with the acceleration of the tower; The component of the rotor imbalance with respect to the rotor position is estimated via an adaptive filtering algorithm programmed in the processor of the controller; Via the controller, corresponding pitch angle offsets of a plurality of rotor blades of the wind turbine are calculated based on the estimated components of the rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades are configured to reduce the first excitation amplitude of the rotor imbalance; and The controller adjusts the pitch angle of each of the plurality of rotor blades to offset the corresponding pitch angle, thereby reducing the first excitation amplitude disturbance with respect to the acceleration of the tower. Technical Solution 2. The method according to Technical Solution 1, wherein the at least one signal associated with the acceleration of the tower of the wind turbine includes the lateral acceleration of the tower due to the natural frequency of the tower and the rotor imbalance, and the first excitation amplitude includes a portion of the lateral acceleration of the tower due to the rotor imbalance. Technical Solution 3. The method according to Technical Solution 2, further comprising: By filtering the acceleration signal via the inverse model of the tower dynamics, the lateral acceleration of the tower caused by the natural frequency of the tower is removed from the at least one signal associated with the acceleration of the tower. Technical Solution 4. The method according to Technical Solution 3, further comprising: Divide the filtered tower acceleration of the wind turbine by the square of the rotor speed of the wind turbine. Technical Solution 5. The method according to Technical Solution 1, wherein the adaptive filtering algorithm includes Recursive Least Squares (RLS). Technical Solution 6. The method according to Technical Solution 1, wherein the estimated component of the rotor imbalance includes the sine and cosine components of the rotor position. Technical Solution 7. The method according to Technical Solution 1, wherein estimating the component of the rotor imbalance with respect to the rotor position via the adaptive filtering algorithm programmed in the processor of the controller includes estimating the component of the rotor imbalance at multiple wind speeds or air densities at the wind turbine or at multiple rotor speeds or power levels of the wind turbine. Technical Solution 8. The method according to Technical Solution 1, further comprising: The proportional controller programmed in the processor of the controller calculates the corresponding pitch angle offset of the plurality of rotor blades of the wind turbine based on the estimated component of the rotor imbalance. Technical Solution 9. The method according to Technical Solution 1, wherein calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: The torque at the base of the tower is calculated using at least one of the wind speed or air density at the wind turbine, or the rotor speed or power level of the wind turbine, and the rotor imbalance; and Determine the corresponding pitch angle offset of each of the plurality of rotor blades, which corresponds to the minimum standard deviation of the torque at the base of the tower, such that the sum of the corresponding pitch angle offsets of each of the plurality of rotor blades is approximately equal to zero. Technical Solution 10. The method according to Technical Solution 1, wherein calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: Calculate the component of each pitch angle offset of the plurality of rotor blades; and The respective pitch angle offset of the plurality of rotor blades is determined using at least one of the wind speed or air density at the wind turbine or the rotor speed or power level of the wind turbine, and the component of each pitch angle offset. Technical Solution 11. A system for compensating for rotor imbalance in a wind turbine, the system comprising: The wind turbine includes a tower, a rotor, and multiple rotor blades; A controller communicatively coupled to the wind turbine, the controller including a processor, the controller being configured to: The processor receives at least one signal associated with the acceleration of the tower of the wind turbine and at least one signal associated with the position of the rotor of the wind turbine. The rotor imbalance is estimated based on the at least one signal associated with the acceleration of the tower; The component of the rotor imbalance with respect to the rotor position is estimated via an adaptive filtering algorithm programmed in the processor of the controller; Via the controller, corresponding pitch angle offsets of a plurality of rotor blades of the wind turbine are calculated based on the estimated components of the rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades are configured to reduce the first excitation amplitude of the rotor imbalance; and The controller adjusts the pitch angle of each of the plurality of rotor blades to offset the corresponding pitch angle, thereby reducing the first excitation amplitude disturbance with respect to the acceleration of the tower. Technical Solution 12. The system according to Technical Solution 11, wherein the at least one signal associated with the acceleration of the tower of the wind turbine includes lateral acceleration of the tower due to the natural frequency of the tower and the rotor imbalance, and the first excitation amplitude includes a portion of the lateral acceleration of the tower due to the rotor imbalance. Technical Solution 13. The system according to Technical Solution 12, wherein the controller is further configured to: By filtering the acceleration signal via the inverse model of the tower dynamics, the lateral acceleration of the tower caused by the natural frequency of the tower is removed from the at least one signal associated with the acceleration of the tower. Technical Solution 14. The system according to Technical Solution 13, wherein the controller is further configured to: Divide the filtered tower acceleration of the wind turbine by the square of the rotor speed of the wind turbine. Technical Solution 15. The system according to Technical Solution 11, wherein the adaptive filtering algorithm includes Recursive Least Squares (RLS). Technical Solution 16. The system according to Technical Solution 11, wherein the estimated component of the rotor imbalance includes the sine and cosine components of the rotor position. Technical Solution 17. The system according to Technical Solution 11, wherein the adaptive filtering algorithm programmed in the processor of the controller estimates the component of the rotor imbalance with respect to the rotor position by estimating the component of the rotor imbalance at multiple wind speeds or air densities at the wind turbine or at multiple rotor speeds or power levels of the wind turbine. Technical Solution 18. The system according to Technical Solution 11, wherein the controller is further configured to: The proportional controller programmed in the processor of the controller calculates the corresponding pitch angle offset of the plurality of rotor blades of the wind turbine based on the estimated component of the rotor imbalance. Technical Solution 19. The system according to Technical Solution 11, wherein calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: The torque at the base of the tower is calculated using at least one of the wind speed or air density at the wind turbine, or the rotor speed or power level of the wind turbine, and the rotor imbalance; and Determine the corresponding pitch angle offset of each of the plurality of rotor blades, which corresponds to the minimum standard deviation of the torque at the base of the tower, such that the sum of the corresponding pitch angle offsets of each of the plurality of rotor blades is approximately equal to zero. Technical Solution 20. The system according to Technical Solution 11, wherein calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: Calculate the component of each pitch angle offset of the plurality of rotor blades; and The respective pitch angle offset of the plurality of rotor blades is determined using at least one of the wind speed or air density at the wind turbine or the rotor speed or power level of the wind turbine, and the component of each pitch angle offset.

[0019] These and other features, aspects, and advantages of this disclosure 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 this disclosure and, together with the description, serve to explain the principles of this disclosure. Attached Figure Description

[0020] The complete and open disclosure of this disclosure, including its best mode for those skilled in the art, is set forth in the specification with reference to the accompanying drawings, in which:

[0021] Figure 1 A perspective view showing an embodiment of a wind turbine according to the present disclosure;

[0022] Figure 2 A simplified interior view of an embodiment of the nacelle of a wind turbine according to the present disclosure is shown;

[0023] Figure 3 A schematic diagram illustrating an embodiment of a controller according to the present disclosure is shown;

[0024] Figure 4 A perspective view of an embodiment of a wind turbine according to the present disclosure is shown, which in particular shows the various axes of rotation and the stresses and moments acting on the wind turbine.

[0025] Figure 5 A flowchart illustrating an embodiment of a method for compensating for rotor imbalance in a wind turbine according to the present disclosure;

[0026] Figures 6A-6B Various graphs are shown showing the amplitude and phase (y-axis) versus frequency (x-axis) of embodiments of the pure inverse model according to this disclosure compared with an actual inverse model of the movement of the wind turbine tower;

[0027] Figure 7A graph showing an embodiment of the estimation of the first excitation frequency vector due to rotor imbalance at multiple wind speeds according to the present disclosure;

[0028] Figure 8 This illustrates the method for reducing according to the present disclosure. Figure 7 A graph depicting the first excitation amplitude of the vector, representing a simulated example of the pitch angle shift due to mass imbalance at multiple wind speeds;

[0029] Figure 9A A graph showing an embodiment of reducing lateral tower movement by compensating for rotor imbalance according to this disclosure; and

[0030] Figure 9B The graph shows an embodiment of improving the quality of electrical power output by compensating for rotor imbalance according to the present disclosure. Detailed Implementation

[0031] Reference will now be made in detail to embodiments of the present disclosure, 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 may be made in this disclosure without departing from the scope or spirit of the disclosure. 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 this disclosure cover such modifications and variations that fall within the scope of the appended claims and their equivalents.

[0032] Generally, this disclosure relates to systems and methods for compensating for rotor imbalance in wind turbines. Specifically, in embodiments, the systems and methods of this disclosure use a controller that receives one or more signals associated with the acceleration of the wind turbine tower. Signals associated with the position of the wind turbine rotor may also be received. In embodiments, for example, the signals may be received at various points in time and may provide data associated with how the wind turbine tower moves over a given time period. Furthermore, the signals associated with the movement of the wind turbine can be used to estimate the rotor imbalance. An adaptive filtering algorithm can then estimate the components of the rotor imbalance at the rotor position. In embodiments, for example, the components may be sine and cosine components of the rotor imbalance. Furthermore, the estimates of the rotor imbalance components can be used to calculate a corresponding pitch angle offset for each rotor blade of the wind turbine to reduce the first excitation amplitude of the rotor imbalance. The controller can then instruct the wind turbine to adjust the pitch angle of each of the rotor blades by a corresponding pitch angle offset to reduce the first excitation amplitude, thereby resulting in a reduction in the first excitation amplitude disturbance to the tower's acceleration. Therefore, the tower's acceleration can be reduced.

[0033] Therefore, the systems and methods of this disclosure can lead to a reduction in the impact of rotor imbalance on the operation and energy output of wind turbines. Consequently, the operational life of wind turbines can be extended, and the stability of power output, i.e., the power quality provided by the wind turbine, can be improved. These and other characteristics provided by the systems and methods of this disclosure will be discussed in more detail below.

[0034] Now refer to the diagram. Figure 1 A perspective view of an embodiment of a wind turbine according to the present disclosure is shown. 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.

[0035] The wind turbine 10 may also include a wind turbine controller 26 centrally located within the nacelle 16. However, in other embodiments, the controller 26 may be located within any other component of the wind turbine 10 or at a location outside the wind turbine. Furthermore, the controller 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 controller 26 may include a computer or other suitable processing unit. Thus, in several embodiments, the controller 26 may include suitable computer-readable instructions that, when implemented, configure the controller 26 to perform various functions, such as receiving, sending, and / or implementing wind turbine control signals. Therefore, the controller 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.

[0036] Now refer to Figure 2 , showing Figure 1The 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.

[0037] 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 controller 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).

[0038] Still refer to Figure 2The 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 of one of the rotor blades 22 or for measuring the load acting on one of the rotor blades 22; generator sensors (not shown) for monitoring the generator 24 (e.g., torque, speed, acceleration, and / or power output); sensors for measuring unbalanced loads in the rotor (e.g., a main shaft bending sensor); and / or 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. Furthermore, the 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 understood that, as used herein, the term "monitor" and its variations indicate that various sensors can 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 controller 26 to determine the actual condition.

[0039] Now refer to Figure 3 This diagram illustrates a block diagram of various components of a controller 26 according to the present disclosure. As shown, the controller 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 controller 26 may include a communication module 62 to facilitate communication between the controller 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 may be communicatively coupled to the communication module 62 using any suitable means. For example, as... Figure 3As 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.

[0040] 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, which, when implemented by the processor(s) 58, configure the controller 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.

[0041] Additionally, controller 26 may include various models, algorithms, or other control systems that, when implemented by controller 26, can assist in compensating for rotor imbalance, as described in more detail below. For example, controller 26 may include pre-programmed algorithms, such as adaptive filtering algorithms, or more specifically, closed-loop adaptive filtering algorithms, or more specifically, recursive least squares methods. As described, the term "adaptive filtering algorithm" generally refers to an algorithm that acts as a filter for a signal, adjusting based on the difference between the actual output signal and the desired output signal. Furthermore, the term "closed-loop adaptive filtering algorithm" generally refers to an adaptive filtering algorithm that adjusts the filter in a closed loop until the difference between the actual output signal and the desired output signal is reduced or minimized to the desired level. Furthermore, the term "recursive least squares method" generally refers to a closed-loop adaptive filtering algorithm that recursively estimates the coefficients to be used with respect to the filter, which reduce or minimize the cost or loss function.

[0042] As described above, controller 26 may also include one or more models programmed therein. For example, controller 26 may include pre-programmed models, such as inverse models, or more specifically, pure inverse models or practical inverse models. As described, the term "inverse model" generally refers to a model that performs the inverse operation on the expected output of a model. Furthermore, the term "pure inverse model" generally refers to the mathematical inverse operation of the tower model equations, while the term "practical inverse model" generally refers to a modification of the pure inverse model to make it suitable and implementable as a filter. Specifically, when it involves a practical inverse model, the output can be filtered to extract a desired estimate for a particular input. More specifically, when it involves the tower model equations, the practical inverse model can act as a filter to extract an estimate of the tower acceleration caused by the effects of mass imbalance. As described herein, both algorithms such as adaptive filtering algorithms and models such as inverse models can provide particular advantages when used to provide systems and methods for compensating for rotor imbalance, as will be discussed in further detail below.

[0043] Now refer to Figure 4 An exploded view of an embodiment of the wind turbine 10 is shown, particularly illustrating the various axes of rotation according to the present disclosure and the corresponding forces and moments acting on the wind turbine 10. The forces applied to the wind turbine 10 may vary, but generally correspond to at least one of the following: blade root resultant force (e.g., F...). 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, torque loads can also be applied to the wind turbine 10.

[0044] Therefore, the torque load applied to the wind turbine 10 can also vary, but generally corresponds to at least one of the following: blade root resultant torque load (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 torque loads shown are provided for illustrative purposes only.

[0045] Now refer to Figure 5 This diagram illustrates a flowchart of an embodiment of a method for compensating rotor imbalance in a wind turbine according to the present disclosure. In embodiments, rotor blade imbalance may include mass imbalance between rotor blades, resulting in an imbalance of inertial moments exhibited in the rotor; however, other types of unbalanced forces, such as aerodynamic imbalance between rotor blades, may be considered. Method 100 is described herein as being implemented on, 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 developed thereafter. Additionally, although... Figure 5 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.

[0046] As shown at (102), method 100 includes receiving at least one signal associated with the acceleration of the tower 12 of the wind turbine 10, and at least one signal associated with the position of the rotor 18 of the wind turbine 10. In an embodiment, the signals may represent the acceleration of the tower 12 at a point in time. Furthermore, the signals may be provided to represent acceleration over a period of time. More specifically, in an embodiment, the signals may represent the lateral acceleration of the tower 12 at its natural frequency, and / or any other type of signal related to rotor imbalance exhibited by the rotor 18 of the wind turbine 10 due to the rotor blades 22.

[0047] Additionally, in this embodiment, the signal associated with the position of rotor 18 can indicate the location of rotor 18 at a given point in time. Multiple signals can be provided to indicate the position of rotor 18 across a time period.

[0048] As shown at (104), method 100 includes estimating rotor imbalance based on at least one signal associated with the tower's acceleration. As used herein, rotor imbalance may generally include forces, accelerations, torques, or functions thereof. To estimate rotor imbalance, models such as inverse models, pure inverse models, or actual inverse models, as described above, may be employed.

[0049] For example, now refer to Figures 6A-6B According to this disclosure, various graphs are shown of the amplitude and phase (y-axis) versus frequency (x-axis) of an embodiment of a pure inverse model compared to an actual inverse model of the movement of a wind turbine tower. More specifically, as shown in graph 200 ( Figure 6A The graph depicts the amplitude (y-axis) versus frequency (x-axis) of the pure inverse model 204 compared to the actual inverse model 206, while the curve 202 ( Figure 6B The phase (y-axis) versus frequency (x-axis) plots of the pure inverse model 204 compared to the actual inverse model 206. Specifically, as shown, the inverse model plots a graph or Bode plot of the inverse frequency response of the tower 12 as the amplitude and phase of the signal associated with the tower 12 vary. Additionally, the inverse model provides a dynamic simulation of how the tower 12 operates with frequency variations in its movement or acceleration.

[0050] As can be seen from graphs 200 and 202, the frequency 208 at which the amplitude reverses to its peak and the large phase shift occurs can be determined. Therefore, in this embodiment, the amplitude and phase of frequency 208 can be compared with the known natural frequency of the tower 12 of the wind turbine 10 to determine the rotor imbalance force. As described herein, the term "natural frequency of the tower" refers to the natural movement of the tower caused by the forces distributed across the wind turbine 10 due to the mass of the wind turbine 10.

[0051] Therefore, in this embodiment, to determine the rotor imbalance force, the signal is filtered via an inverse model by implementing an inverse model. The known natural frequency of the tower 12 of the wind turbine 10 can be removed from the signal of the tower 12, as depicted in graphs 200 and 202. Other factors besides the natural frequency of the tower 12 can also be removed from the signal via the inverse model. For example, if wind exerts a force on the wind turbine 10, the frequency of the tower attributable to the wind force can also be removed from the signal of the tower 12 (depicted in graphs 200 and 202).

[0052] In an embodiment, method 100 may include dividing the acceleration of tower 12 by the square of the rotor speed of wind turbine 10. This allows the components of rotor imbalance (e.g., sine and cosine components) to be better represented graphically, such as in graph 300. Figure 7As shown in the diagram. Dividing the acceleration of tower 12 by the rotor speed can help provide better data, which can be compared with the data used to determine the pitch angle offset of rotor blades 22 to compensate for rotor unbalance forces.

[0053] Refer back Figure 5 As shown at (106), method 100 further includes estimating the rotor imbalance components with respect to rotor position via an adaptive filtering algorithm programmed in the processor 58 of controller 26. In embodiments, the adaptive filtering algorithm may be a closed-loop adaptive filtering algorithm or a recursive least squares algorithm programmed in the processor 58 of controller 26. For example, in an embodiment, the adaptive filtering algorithm may determine estimates of the sine and cosine components of the rotor imbalance of rotor 18. In particular, the estimated sine and cosine components of the rotor imbalance may represent a decomposition of the rotor imbalance. This decomposition enables analysis of the rotor imbalance in such a way that a reduction in imbalance offset can be determined. To account for multiple conditions, the sine and cosine components may be estimated at various wind speeds that may be present at wind turbine 10. The sine and cosine components may also be estimated for other operating conditions present at or around wind turbine 10. For example, the sine and cosine components may be estimated at various air densities at wind turbine 10 or at various rotor speeds or power levels of wind turbine 10.

[0054] Furthermore, the sine and cosine components can be estimated at or with respect to the position of the rotor 18 of the wind turbine 10. More specifically, in an embodiment, an adaptive filtering algorithm can be used to estimate the rotor position locking tower acceleration of the wind turbine 10 by parsing / matching the estimated tower acceleration signal to both the sine and cosine components of the rotor position. Through the estimation of the rotor position locking tower acceleration, the sine and cosine components resulting from rotor imbalance can be separated from the sine and cosine components of the total force acting on the wind turbine 10.

[0055] Next, the sine and cosine components can be used to represent rotor imbalance. More specifically, the sine and cosine components can represent the first excitation frequency of the force occurring at the rotor 18 of the wind turbine 10. The components of rotor imbalance can be estimated at multiple wind speeds and represented by vectors. Depending on whether a pure inverse model or an actual inverse model is used, the sine and cosine components can be adjusted to compensate for the differences between the pure inverse model and the actual inverse model.

[0056] As an example of such a component representing rotor imbalance, Figure 7A graph illustrating an embodiment of the estimation of a first excitation frequency vector due to mass imbalance force at multiple wind speeds according to the present disclosure is shown. As shown, according to the present disclosure, graph 300 depicts multiple vectors 302, 304, 306, 308, which represent the components of rotor imbalance at multiple wind speeds. Specifically, graph 300 depicts vectors 302, 304, 306, 308 at the first excitation frequency for tower 12, wherein the amplitudes of vectors 302, 304, 306, 308 are attributed to the rotor imbalance force. Additionally, as shown, vectors 302, 304, 306, 308 represent the cosine (x-axis) and sine (y-axis) components of rotor imbalance causing partial lateral acceleration of tower 12. The components of rotor imbalance can also be estimated for other conditions present at or around the wind turbine 10. For example, the components of rotor imbalance can be estimated at multiple air densities at the wind turbine 10 or at multiple rotor speeds or power levels of the wind turbine 10.

[0057] Refer back Figure 5 As shown at (108), method 100 includes calculating corresponding pitch angle offsets of a plurality of rotor blades 22 of the wind turbine 10 based on an estimated component of rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades 22 are configured to reduce the first excitation amplitude of rotor imbalance. Torque calculation can be performed when the wind turbine 10 is inactive or before estimating rotor imbalance. The calculated torque can be mapped and stored in memory, such as in the memory(s)60 of controller 26. When desired, controller 26 can retrieve the calculated torque from memory for further use.

[0058] In one embodiment, controller 26 is configured to calculate the torque at the base of tower 12 using rotor imbalance and the wind speed at which force is applied at wind turbine 10. Controller 26 then calculates the minimum standard deviation of the torque to determine the pitch angle offset of each of the rotor blades 22 of wind turbine 10. In this embodiment, controller 26 may also determine the sum of the pitch angle offsets of the rotor blades 22 such that the sum is equal to or approximately equal to zero.

[0059] Similar to torque calculations, the minimum standard deviation of the torque can be calculated when the wind turbine 10 is inactive or before assessing rotor imbalance. Furthermore, like the calculated torque, the minimum standard deviation of the torque can be mapped and stored in memory, such as in the memory(s) 60 of the controller 26. Likewise, when desired, the controller 26 can retrieve the minimum standard deviation of the torque from memory for further use.

[0060] In a particular embodiment, the pitch angle offset for the rotor blade 22 can be calculated by determining the pitch angle offset corresponding to the minimum standard deviation of the torque at the base of the tower 12 relative to a predetermined target value. Alternatively, the pitch angle offset can also be determined by finding the pitch angle offset corresponding to the minimum standard deviation of the electrical power output by the wind turbine 10, using the minimum of the pitch angle offset of the rotor blade 22 and the minimum of the standard deviation of the torque at the base of the tower 12. For both in these embodiments, the pitch angle offset is calculated such that the sum of the pitch angle offsets equals zero.

[0061] Specifically, if the pitch angle offset that minimizes the standard deviation of the moment at the base of tower 12 is to be solved, an optimization equation can be provided according to the following equation (1). Make in and It is equal to the pitch angle offset of rotor blade 22; TwrSS equals the movement of tower 12; and

[0062] TwrSS target This is equal to the target movement of tower 12. Furthermore, if the pitch angle offset is calculated to minimize the standard deviation of the moment at the base of tower 12 and the electrical output of wind turbine 10, then the optimization equation can be provided according to the following equation (3). Make in and It is equal to the pitch angle offset of rotor blade 22; TwrSS equals the movement of tower 12; TwrSS target The target movement is equal to tower 12; PwrEl equals the electrical power output of wind turbine 10; and PwrEl target This is equal to the target electrical power output of a wind turbine 10.

[0063] By solving for the pitch angle offset corresponding to the minimum standard deviation of torque or torque and electrical power output, a reduction in tower movement or an increase in the stability and quality of the electrical power output by the wind turbine 10 is provided. Furthermore, by requiring the sum of the pitch angle offsets of the rotor blades 22 to be equal to zero, the aerodynamic balance between the rotor blades 22 can be maintained, while providing the aforementioned improvements.

[0064] Next, the pitch angle offset of each of the rotor blades 22 can be correlated with the signal of the tower 12 to calculate the sine and cosine components of the pitch angle offset of each rotor blade 22. The calculated sine and cosine components of each pitch angle offset can then be compared with the sine and cosine components of the rotor imbalance to determine the adjustment of the pitch angle of each of the rotor blades 22 with the corresponding pitch angle offset. Specifically, the pitch angle offset can be calculated using a proportional controller programmed in the processor 58 of the controller 26 and compared with the rotor imbalance. As described, the term "proportional controller" generally refers to a controller that implements a proportional change in the actual output in response to the difference between the actual output and the desired output.

[0065] When calculating pitch angle offset, the proportional controller can calculate a percentage to increase or decrease the current pitch angle of the rotor blades 22 using the pitch angle offset. For example, the percentage could be approximately half or less than half of the pitch angle offset. By using only half or less of the pitch angle offset, the possibility of negative results such as over-correction of the pitch angle can be avoided. Furthermore, by using the proportional controller, multiple types of inputs for rotor imbalance can be utilized simultaneously. For example, the proportional controller can simultaneously use mass imbalance or moment of inertia imbalance, along with aerodynamic imbalance exhibited in the rotor blades 22.

[0066] Specifically, in an embodiment, the proportional controller can provide a constant offset in the pitch angle of the rotor blades 22 to compensate for at least two different types of rotor imbalance. For example, as discussed above, the proportional controller may be able to utilize both mass force imbalance and aerodynamic imbalance in the rotor blades 22. In the case of implementing two different control strategies (i.e., considering both mass force imbalance and aerodynamic imbalance), a certain level of coordination can be maintained between the two strategies to facilitate convergence to a final solution that is stable. Such a stable solution is naturally achieved if both strategies are limited to proportional action, as opposed to solutions where both control solutions contain some form of accumulator (which can potentially grow in opposite directions and never converge to a final solution).

[0067] Additionally, pitch angle offsets can be calculated for multiple wind speeds. For example, now refer to... Figure 8 This illustrates the method for reducing according to the present disclosure. Figure 7 The graph depicts a simulated embodiment of the first excitation amplitudes of vectors 302, 304, 306, and 308 at multiple wind speeds, representing the pitch angle shift due to mass imbalance. As shown, regarding... Figure 7The vectors 302, 304, 306, and 308 of the rotor unbalance force are shown in graph 300, and graph 400 depicts the pitch angle offset vectors 402, 404, 406, and 408, respectively. Therefore, the pitch angle offset vectors 402, 404, 406, and 408 and the vectors 302, 304, 306, and 308 of the tower rotor unbalance force can be compared and used to adjust the pitch angle of the rotor blades 22.

[0068] Refer back Figure 5 As shown at (110), method 100 includes adjusting the pitch angle of each of the plurality of rotor blades 22 by a corresponding pitch angle offset to reduce the first excitation amplitude, thereby reducing or minimizing the first excitation amplitude disturbance to the acceleration of the tower 12. More specifically, when the controller 26 instructs the wind turbine 10 to adjust the pitch angle of the rotor blades 22 according to vectors 402, 404, 406, 408 (e.g. Figure 8 (as shown in the image), by Figure 7 The disturbance of the first excitation amplitude caused by the rotor imbalance force depicted by vectors 302, 304, 306, and 308 can be reduced or minimized. Therefore, according to this disclosure, the tower acceleration of the wind turbine 10 can be reduced by compensating for rotor imbalance.

[0069] Now refer to Figures 9A-9B According to this disclosure, graphs depict the lateral movement of the tower 12 and the electrical power output. As shown, graphs 500 and 550 depict the lateral movement of the tower 12 and the electrical power output of the wind turbine 10, respectively. In particular, as... Figure 9A As shown, graph 500 depicts the lateral movement 504 of the tower 12 without control, and the lateral movement 506 of the tower 12 with rotor imbalance compensation according to the present disclosure. Therefore, as shown, the lateral movement or acceleration of the tower 12 can be reduced by compensating for rotor imbalance forces according to the present disclosure.

[0070] In addition, such as Figure 9B As shown, graph 550 depicts the electrical power output 552 of an uncontrolled wind turbine 10 and the electrical power output 554 of a wind turbine 10 with rotor imbalance compensation according to this disclosure. Therefore, as... Figure 9B As shown, by compensating for rotor imbalance according to this disclosure, the power quality output by the wind turbine 10 (i.e., less oscillation in the voltage) can be improved.

[0071] This written description uses examples to disclose this disclosure (including the best mode) and also enables those skilled in the art to practice this disclosure (including making and using any device or system and performing any incorporated methods). The patentable scope of this disclosure is defined by the claims and may include other examples that would 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 compensating for rotor imbalance in a wind turbine, the method comprising: The processor of the controller of the wind turbine receives at least one signal associated with the acceleration of the tower of the wind turbine and at least one signal associated with the position of the rotor of the wind turbine. The rotor imbalance is estimated based on the at least one signal associated with the acceleration of the tower; The component of the rotor imbalance with respect to the rotor position is estimated via an adaptive filtering algorithm programmed in the processor of the controller; The controller calculates the corresponding pitch angle offsets of a plurality of rotor blades of the wind turbine based on the estimated components of the rotor imbalance, wherein the corresponding pitch angle offsets of the plurality of rotor blades are configured to reduce the first excitation amplitude of the rotor imbalance. as well as The controller adjusts the pitch angle of each of the plurality of rotor blades to offset the corresponding pitch angle, thereby reducing the first excitation amplitude disturbance with respect to the acceleration of the tower.

2. The method according to claim 1, wherein, The at least one signal associated with the acceleration of the tower of the wind turbine includes the lateral acceleration of the tower due to the natural frequency of the tower and the rotor imbalance, and the first excitation amplitude includes a portion of the lateral acceleration of the tower due to the rotor imbalance.

3. The method according to claim 2, further comprising: By filtering the acceleration signal via the inverse model of the tower dynamics, the lateral acceleration of the tower caused by the natural frequency of the tower is removed from the at least one signal associated with the acceleration of the tower.

4. The method according to claim 3, further comprising: Divide the filtered tower acceleration of the wind turbine by the square of the rotor speed of the wind turbine.

5. The method according to claim 1, wherein, The adaptive filtering algorithm includes the recursive least squares (RLS) method.

6. The method according to claim 1, wherein, The estimated components of the rotor imbalance include the sine and cosine components of the rotor position.

7. The method according to claim 1, wherein, The adaptive filtering algorithm programmed in the processor of the controller estimates the component of the rotor imbalance with respect to the rotor position, including estimating the component of the rotor imbalance at multiple wind speeds or air densities at the wind turbine or at multiple rotor speeds or power levels of the wind turbine.

8. The method according to claim 1, further comprising: The proportional controller programmed in the processor of the controller calculates the corresponding pitch angle offset of the plurality of rotor blades of the wind turbine based on the estimated component of the rotor imbalance.

9. The method according to claim 1, wherein, Calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: The torque at the base of the tower is calculated using at least one of the wind speed or air density at the wind turbine, or the rotor speed or power level of the wind turbine, and the rotor imbalance; and Determine the corresponding pitch angle offset of each of the plurality of rotor blades, which corresponds to the minimum standard deviation of the torque at the base of the tower, such that the sum of the corresponding pitch angle offsets of each of the plurality of rotor blades is approximately equal to zero.

10. The method according to claim 1, wherein, Calculating the corresponding pitch angle offset of the plurality of rotor blades based on the estimated component of the rotor imbalance further includes: Calculate the component of each pitch angle offset of the plurality of rotor blades; and The respective pitch angle offset of the plurality of rotor blades is determined using at least one of the wind speed or air density at the wind turbine or the rotor speed or power level of the wind turbine, and the component of each pitch angle offset.

Images