System and method for alleviating loads acting on rotor blades of a wind turbine

Abstract

A method for mitigating loads acting on a rotor blade of a wind turbine includes determining, via a state estimator of a controller, a blade state estimate of a rotor blade. The method also includes reconstructing, via the controller, one or more load signals for the rotor blade from the blade state estimate using modal analysis such that the load signal(s) include an advance time. Furthermore, the method includes comparing the load signal(s) for the rotor blade to a load threshold. Furthermore, the method includes implementing a control action based on the comparison such that the advance time provided by the load signal(s) allows the control action to be implemented before a destructive load occurs on the rotor blade.

Description

Technical Field

[0001] The present disclosure relates generally to wind turbines, and more particularly to systems and methods for mitigating loads acting on rotor blades of a wind turbine. Background Art

[0002] Wind power is considered to be one of the cleanest and most environmentally friendly energy sources currently available, and in this regard, wind turbines have received increased attention. Modern wind turbines typically include a tower, a generator, a gearbox, a nacelle, and one or more rotor blades. The rotor blades are the main elements for converting wind energy into electrical energy. The blades typically have a cross-sectional profile of an airfoil so that air flows through the blades during operation, creating a pressure difference between their sides. Therefore, the lift directed from the pressure side toward the suction side acts on the blades. The lift generates a torque on the main rotor shaft, which is connected to a generator for generating electricity.

[0003] The amount of power that can be generated by a wind turbine is typically limited by the structural limitations (i.e., design loads) of the individual wind turbine components. For example, the blade roots of a wind turbine may experience loads associated with average loads due to turbine operation and dynamically fluctuating loads due to environmental conditions (e.g., such as blade tip deflection, blade bending moments, or various blade forces). Such loads may damage turbine components, ultimately causing turbine component failure. Fluctuating loads may vary from day to day or from season to season, and may be based on wind speed, wind peaks, wind turbulence, wind shear, changes in wind direction, density in the air, yaw misalignment, updrafts, or the like. In particular, for example, the loads experienced by a wind turbine may vary with wind speed.

[0004] Thus, it is imperative to ensure that the loads acting on the wind turbine do not exceed the design loads. Therefore, many wind turbines employ one or more sensors configured to measure the loads acting on various wind turbine components. Although the sensors can provide the desired information, new sensor systems can be complex and expensive to install. Furthermore, the sensors can provide inaccurate information and can be susceptible to failure.

[0005] Additionally, large rotors can suffer from small blade tip-tower clearances and high root bending moments, especially during extreme turbulence and extreme wind shear conditions. However, conventional controllers do not have specific control features for tip clearance improvement. Furthermore, existing features have limited impact on tip clearance improvement due to actuation saturation during extreme events and insufficient bandwidth for the pitch system.

[0006] In view of the foregoing, the art is continually seeking new and improved systems for mitigating loads acting on wind turbine rotor blades. Accordingly, the present disclosure is directed to systems and methods for mitigating loads acting on rotor blades by providing an advance time in an estimated future load signal (by using both the velocity and deflection of the blade pattern) thereby providing a faster pitch response. Summary of the invention

[0007] Aspects and advantages of the invention will be set forth in part in the following description, or may be obvious from the description, or may be learned through practice of the invention.

[0008] In one aspect, the present disclosure is directed to a method for mitigating loads acting on a rotor blade of a wind turbine. The method includes determining a blade state estimate of a rotor blade via a state estimator of a controller. The method also includes reconstructing one or more load signals of the rotor blade from the blade state estimate using modal analysis via the controller, such that the (one or more) load signals include an advance time. In addition, the method includes comparing the (one or more) load signals of the rotor blade to a load threshold. Moreover, the method includes implementing a control action based on the comparison, such that the advance time provided by the (one or more) load signals allows the control action to be implemented before a destructive load occurs on the rotor blade.

[0009] In an embodiment, determining the blade state estimate for the rotor blade may include receiving measurement data related to the rotor blade from one or more sensors, and determining the blade state estimate for the rotor blade based on the measurement data.

[0010] In another embodiment, the sensor(s) may include, for example, a micro inertial measurement unit (MIMU), a strain gauge, an accelerometer, a pressure sensor, a vibration sensor, a proximity sensor, or a camera sensor.

[0011] In further embodiments, the load signal(s) may include, for example, blade tip deflection, blade bending moment, or blade force of the rotor blade.

[0012] In an embodiment, using modal analysis may include determining velocity or deflection of a blade modal response of the rotor blade. In another embodiment, using modal analysis further includes using Euler-Bernoulli beam theory.

[0013] In additional embodiments, reconstructing the load signal(s) of the rotor blade from the blade state estimate using modal analysis may include: receiving a measured tip deflection of the rotor blade, a flap-wise natural frequency of the rotor blade for one or more resonant modes, and a gain for the load signal(s) of the rotor blade; estimating a future flap-wise blade tip deflection of the rotor blade for the one or more resonant modes based on the measured tip deflection, the flap-wise natural frequency, and the gain for the one or more load signals; and estimating a future blade bending moment based on the future flap-wise blade tip deflection of the rotor blade for the one or more resonant modes. In embodiments, the gain may be a horizontal gain.

[0014] In several embodiments, estimating the future swing-wise blade tip deflections of the rotor blades for one or more resonance modes may include estimating the future swing-wise blade tip deflections of the rotor blades for a first resonance mode and a second resonance mode. In such embodiments, estimating the future blade bending moment based on the future swing-wise blade tip deflections of the rotor blades for one or more resonance modes may include estimating the future blade bending moment based on the future swing-wise blade tip deflections for the first resonance mode, the future swing-wise blade tip deflections for the second resonance mode, and one or more conversion constants.

[0015] In additional embodiments, comparing the load signal(s) of the rotor blade to the load threshold may include comparing the future blade bending moment to the load threshold.

[0016] In an embodiment, implementing a control action based on the comparison may include adjusting a pitch angle of the rotor blade. In an embodiment, adjusting the pitch angle of the rotor blade may include determining an updated pitch angle limit for the rotor blade based on an expected decrease in the load signal(s) when the future blade bending moment exceeds a load threshold. Alternatively, adjusting the pitch angle of the rotor blade may include allowing the pitch angle limit to decay exponentially to the original pitch angle limit when the future blade bending moment is below the load threshold.

[0017] In another aspect, the present disclosure is directed to a system for mitigating loads acting on a rotor blade of a wind turbine. The system includes: one or more sensors configured to generate measurement data related to the rotor blade; and a controller communicatively coupled to the (one or more) sensors. The controller includes a processor having a state estimator programmed therein. The controller is configured to perform a plurality of operations including, but not limited to: determining a blade state estimate of the rotor blade based on the measurement data via the state estimator; reconstructing one or more load signals of the rotor blade from the blade state estimate using modal analysis, such that the one or more load signals include an advance time; comparing the (one or more) load signals of the rotor blade to a load threshold; and implementing a control action based on the comparison, such that the advance time provided by the one or more load signals allows the control action to be implemented before a destructive load occurs on the rotor blade. It should be understood that the present disclosure may also include any of the additional features described herein.

[0018] These and other features, aspects and advantages of the present invention will become better understood with reference to the following description and appended claims.The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present invention and, together with the description, serve to explain the principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] A full and complete disclosure of the invention including the best mode thereof to one of ordinary skill in the art is set forth in the specification with reference to the accompanying drawings, in which:

[0020] Figure 1 A perspective view showing one embodiment of a wind turbine according to the present disclosure;

[0021] Figure 2 shows a simplified interior view of one embodiment of a nacelle of a wind turbine according to the present disclosure;

[0022] Figure 3 A schematic diagram showing one embodiment of a controller according to the present disclosure;

[0023] Figure 4 A schematic diagram showing one embodiment of a controller according to the present disclosure; and

[0024] Figure 5 A flow chart showing one embodiment of a method for mitigating loads acting on a rotor blade of a wind turbine according to the present disclosure. DETAILED DESCRIPTION

[0025] Reference will now be made in detail to embodiments of the present invention, one or more examples of which are shown in the drawings. Each example is provided as an explanation of the present invention, not a limitation of the present invention. In fact, it will be apparent to those skilled in the art that various modifications and variations may be made in the present invention without departing from the scope or spirit of the present invention. For example, the features shown or described as part of an embodiment may be used with another embodiment to produce further embodiments. Therefore, it is intended that the present invention includes such modifications and variations as fall within the scope of the appended claims and their equivalents.

[0026] In general, the present disclosure is directed to improved systems and methods for mitigating rotor blade loads, such as deflections and blade root bending moments, of a wind turbine. In one embodiment, for example, deflections, moments, and forces are reconstructed from modal deflections and velocities of blade modal responses. Predicted horizontal gains may be used to provide lead time in the reconstructed signals. One or more pitch angles may be adjusted by a controller in response to a signal exceeding a load threshold in order to reduce blade tip deflections and blade root bending moments.

[0027] Various embodiments of the systems and methods described herein provide many advantages. For example, the present disclosure maintains rotor blade loads within predetermined limits while also maximizing annual energy production (AEP). Thus, the present disclosure can help prevent turbine component failures caused by excessive blade loads. Moreover, the present disclosure can be implemented using existing components of a wind turbine and does not require additional sensors. Thus, users do not need to purchase, install, and maintain new equipment. Moreover, the system can be integrated with a wider range of control systems, such as, but not limited to, a wind turbine control system, a plant control system, a remote monitoring system, or a combination thereof.

[0028] Now refer to Figure 1 , shows a perspective view of one embodiment of a wind turbine 10 that may implement control techniques according to the present 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 the hub 20 and extending outwardly 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 less than three rotor blades 22. Each rotor blade 22 may be spaced about the hub 20 to facilitate rotating the rotor 18 so that kinetic energy can be converted from the wind into usable mechanical energy and subsequently into electrical energy. For example, the hub 20 may be rotatably coupled to a generator 24 ( Figure 2 ), to allow the generation of electrical energy.

[0029] The wind turbine 10 may also include a wind turbine controller 26 centralized 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. In addition, the controller 26 may be communicatively coupled to any number of components of the wind turbine 10 in order to control the operation of such components and / or implement corrective actions. Thus, the controller 26 may include a computer or other suitable processing unit. Therefore, in several embodiments, the controller 26 may include suitable computer-readable instructions that, when implemented, configure the controller 26 to perform a variety of different functions, such as receiving, transmitting and / or executing wind turbine control signals. Therefore, as will be discussed in more detail below, the controller 26 may generally be configured to control various operating modes (e.g., startup or shutdown sequences), degrade the wind turbine, and / or control various components of the wind turbine 10.

[0030] Now refer to Figure 2 , showing Figure 1 1 . A simplified internal view of one embodiment of a nacelle 16 of a wind turbine 10 is shown in FIG. As shown, a generator 24 may be coupled to the rotor 18 for generating 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 the hub 20 for rotation therewith. The rotor shaft 34 may in turn 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 the 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.

[0031] Each rotor blade 22 may also include a pitch adjustment mechanism 32 configured to rotate each rotor blade 22 about its pitch axis 28. In addition, 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 such that the pitch drive motor 40 imparts 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, in turn, may be rotationally engaged with a pitch bearing 46 coupled 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. Thus, in such embodiments, rotation of the pitch drive motor 40 drives the pitch drive gearbox 42 and the pitch drive pinion 44, thereby rotating the pitch bearing 46 and the rotor blades 22 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 66 is configured to change the angle of the nacelle 16 relative to the wind (e.g., by engaging a yaw bearing 68 of the wind turbine 10).

[0032] Still refer to Figure 2 The wind turbine 10 may also include one or more sensors 48, 50 for generating measurement data related to the rotor blades and / or any other operating parameters that may be needed to determine the various load conditions described herein. For example, in various embodiments, the sensor(s) may include: one or more blade sensors 48 for measuring a load acting on one of the rotor blades 22; a generator sensor (not shown) for monitoring the generator 24 (e.g., torque, rotational speed, acceleration, and / or power output); a sensor for measuring unbalanced loads in the rotor (e.g., a main shaft bending sensor); and / or various wind sensors 50 for measuring various wind parameters (such as wind speed, wind peaks, wind turbulence, wind shear, changes in wind direction, air density, or the like). Furthermore, the sensors may be located near the ground of the wind turbine, on a nacelle, or on a meteorological mast of the wind turbine.

[0033] It should also be understood that any other number or type of sensors may be employed and at any location. For example, the sensors may include, for example, a micro-inertial measurement unit (MIMU), a strain gauge, an accelerometer, a pressure sensor, a vibration sensor, a proximity sensor, or a camera sensor. It should be understood that, as used herein, the term "monitoring" and variations thereof indicate that the various sensors may be configured to provide a direct measurement of the monitored parameter or an indirect measurement of such a parameter. Thus, the sensors may, for example, be used to generate signals related to the monitored parameters, which signals may then be utilized by the controller 26 to determine the actual parameters.

[0034] Now refer to Figure 3 , shows a block diagram of one embodiment of various components of the controller 26 according to the present disclosure. As shown, the controller 26 may include one or more processors 58 and associated (one or more) memory devices 60, which are configured to perform various computer-implemented functions (e.g., perform methods, steps, calculations, etc. and store relevant data as disclosed herein). In addition, the controller 26 may also include a communication module 62 to facilitate communication between the controller 26 and various components of the wind turbine 10. Moreover, the communication module 62 may include a sensor interface 64 (e.g., one or more analog-to-digital converters) to allow signals transmitted from the sensors 48, 50 to be converted into signals that can be understood and processed by the processor 58. It should be appreciated that the sensors 48, 50 may be communicatively coupled to the communication module 62 using any suitable means. For example, Figure 3 As shown in FIG. 4 , the sensors 48 , 50 are coupled to the sensor interface 64 via a wired connection. However, in other embodiments, the sensors 48 , 50 may be coupled to the sensor interface 64 via a wireless connection (such as by using any suitable wireless communication protocol known in the art).

[0035] As used herein, the term "processor" refers not only to integrated circuits that are considered in the art to be included in a computer, but also to controllers, microcontrollers, microcomputers, programmable logic controllers (PLCs), application specific integrated circuits, and other programmable circuits. In addition, the memory device(s) 60 may generally include memory elements 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, compact disk-read only memory (CD-ROM), magneto-optical disks (MOD), digital versatile disks (DVD), and / or other suitable memory elements. Such memory device(s) 60 may generally be configured to store suitable computer readable instructions that, 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 parameters of the wind turbine 10 based on a plurality of operational data; determining a maximum wind turbine parameter; transmitting suitable control signals to implement a control action to reduce a load acting on the wind turbine; and various other suitable computer implemented functions.

[0036] The processor 58 is configured to estimate rotor blade loads (e.g., tip deflection, blade root resultant moment, and / or force) of the wind turbine 10 using the operating parameters measured from the sensors 48, 50. For example, the sensors 48, 50 are configured to measure various wind turbine and / or environmental conditions to directly or indirectly provide information about one or more of the following parameters: rotor thrust, mechanical torque, forces acting on the rotor blades 22, rotor imbalance measurements, rotor azimuth, rotor speed, gearbox ratio, inching moment, overhang moment, yaw moment, gravity, hub radius, blade radius, taper angle, blade mass, blade weight, the location of the center of gravity for each of the rotor blades 22, or any other operating parameter of the wind turbine 10.

[0037] Now refer to Figure 4, a schematic diagram of a system 100 for mitigating loads acting on (one or more) rotor blades 22 of a wind turbine 10 according to the present disclosure is shown. As shown, the system 100 may include a controller 26, a state estimator 102, a blade tip deflection threshold module 104, an advance time predictor 106, and a collective pitch controller 108. More specifically, as shown, the state estimator 102 is configured to determine a blade state estimate of the rotor blade 22 based on, for example, measurement data 114 from sensors 48, 50. For example, in an embodiment, the state estimator 102 may receive measurement data 114 related to the rotor blade 22 from one or more sensors 48, 50, and determine a blade state estimate of the rotor blade 22 based on the measurement data 114. The state estimator 102 described herein allows for the extraction of a greater number of features than an observed signal. For example, by measuring data related to the rotor blade 22, it is possible to estimate deflection, moment, velocity, force, friction, stiffness, etc., as well as other system parameters.

[0038] Additionally, as shown, the lead time predictor 106 receives the output of the state estimator 102 and is configured to determine a future prediction value 110 for the tip deflection and / or blade root moment 112. As shown at 115, the controller 26 may determine a difference between the future prediction value 110 and a rotor plane deflection threshold 116. Additionally, as shown at 117, the controller 26 may determine a difference between an individual blade deflection threshold 118 at the tower 12 and the rotor plane deflection threshold 116. In further embodiments, a module 124 of the controller 26 may receive the blade deflection at the tower passage 120 as well as the rotor speed and the individual blade orientation 122 to detect whether the blade is within a certain tower section.

[0039] Thus, as shown, the blade tip deflection threshold control 104 may be a selector block configured to select the blade tip deflection delta amount based on a comparison of the blade passing the tower (bottom, center of rotor orientation) and the blade deflection within the entire rotor plane. More specifically, in an embodiment, the blade tip deflection threshold control 104 may be configured to reconstruct one or more load signals of the rotor blade 22 from the blade state estimate (from the state estimator 102) using modal analysis, such that the load signal(s) include a lead time. In an embodiment, for example, the load signal(s) may include, for example, blade forces, blade bending moments, and / or blade tip deflections acting on the rotor blade 22. Moreover, as used herein, modal analysis generally refers to studying the dynamic characteristics of a system in the frequency domain (e.g., such as by measuring vibrations of the rotor blades 22 during operation of the wind turbine 10). As used herein, reconstruction generally refers to determining the original continuous signal from a sequence of equally spaced samples.

[0040] Additionally, as shown, the advance time predictor 106 may include a prediction horizontal gain 105 that may be used to provide an advance time in the reconstructed signal, i.e., by multiplying the gain 105 by the rotor speed of the wind turbine 10. For example, in an embodiment, the horizontal gain generally corresponds to a tuning knob for determining how much velocity component is present in the prediction of the yaw, with larger values ​​providing increased advance time.

[0041] Still refer to Figure 4 , the blade tip deflection threshold control 104 is configured to determine the velocity or deflection of the blade modal response of the rotor blade 22, for example using the Euler-Bernoulli beam theory. As used herein, the Euler-Bernoulli beam theory generally refers to a simplification of the linear theory of elasticity that provides a means of calculating the load support and deflection characteristics of a beam (in this case, a rotor blade).

[0042] For example, in one embodiment, blade tip deflection threshold control 104 is configured to receive a measured tip deflection of rotor blade 22, a swing-wise natural frequency of rotor blade 22 for one or more resonant modes, and / or a gain of a load signal(s) for rotor blade 22. Blade tip deflection threshold control 104 may then estimate a future swing-wise blade tip deflection (e.g., X) of rotor blade 22 for one or more resonant modes based on the measured tip deflection, the swing-wise natural frequency, and the gain of the one or more load signals. Flat1_Pre ), for example using the following formula (1).

[0043] Formula (1)

[0044] Additionally, the blade tip deflection threshold control 104 may also estimate the future swing direction blade tip deflection (X) of the rotor blade 22 for the first resonant mode. Flat1_Pre ) and the future swing direction blade tip deflection (X) of the rotor blade 22 for the second resonance mode Flat2_Pre ).

[0045] Therefore, in an embodiment, the blade tip deflection threshold control 104 may then estimate the future blade bending moment (eg, M ) based on the future swing-direction blade tip deflection of the rotor blade for one or more resonant modes. y B Pre In such embodiments, the blade tip deflection threshold control 104 may then be configured to adjust the blade tip deflection (X) for the first resonance mode based on the future swing direction. Flat1_Pre ), for the future swing direction of the second resonance mode, the blade tip deflection (X Flat2_Pre ) and one or more conversion constants to estimate the future blade bending moment, for example using equation (2) below.

[0046] Formula (2)

[0047] Table 1 below provides definitions of the variables used in equations (1) and (2).

[0048] Table 1: Variable definitions

[0049] variable definition <![CDATA[K Flap1-to-mom ]]> The constant that converts the blade tip deflection into bending moment for the first resonance mode <![CDATA[K Flap2-to-mom ]]> The constant that converts the blade tip velocity into a bending moment for the second resonance mode <![CDATA[K gain ]]> Gain scaling factor to adjust the sensitivity of the 2nd resonance mode contribution <![CDATA[ω Flap1 ]]> Natural frequency of the first resonance mode of blade swing <![CDATA[X Flap1 ]]> For the blade tip deflection in the first swing resonance mode, the actual measured value is <![CDATA[X dotFlap1 ]]> For the blade tip speed in the first swing resonance mode, the actual measured value is <![CDATA[M y B Pre ]]> Blade root bending moment in the swing direction, future prediction <![CDATA[X Flap1_Pre ]]> For the blade tip deflection in the first swing resonance mode, the future prediction value is <![CDATA[X Flap2_Pre ]]> For the blade tip deflection in the second vibration resonance mode, the future prediction value is

[0050] Still refer to Figure 4 , the tip deflection gain sensitivity 126 may be multiplied by the output of the blade tip deflection threshold control 104 as shown at 128. Further, as shown, the output of 128 may be combined with the rotor thrust and pitch sensitivity 127 as shown at 130.

[0051] The collective pitch controller 108 is then configured to use the output of 130 to adjust pitch commands 134 for all rotor blades 22. More specifically, as shown, the collective pitch controller 108 may determine a delta pitch command 136 for an individual rotor blade 22 in the rotor plane or at a tower crossing sector that requires adding the delta pitch amount to the total command to control blade tip deflection. More specifically, in an embodiment, the collective pitch controller 108 is configured to receive load signals and compare them to load thresholds. For example, in one embodiment, the collective pitch controller 108 is configured to compare future blade bending moments to load thresholds.

[0052] Additionally, controller 26 is configured to implement control actions based on the comparison such that the lead time provided by the load signal allows control actions to be implemented before damaging loads occur on rotor blade 22. For example, in one embodiment, one or more pitch angles may be adjusted by controller 26 in response to a signal exceeding a load threshold in order to reduce blade tip deflection and blade root bending moment.

[0053] More specifically, in an embodiment, controller 26 may be configured to determine an updated pitch angle limit for rotor blade 22 based on an expected decrease in load signal(s) when the future blade bending moment exceeds a load threshold. Alternatively, in an embodiment, controller 26 may be configured to allow the pitch angle limit to decay exponentially to the original pitch angle limit when the future blade bending moment is below the load threshold.

[0054] Furthermore, it should be understood that the control actions as described herein may include any suitable commands or constraints by the controller 26. For example, in several embodiments, the control actions may include temporarily de-rating or up-rating the wind turbine to prevent excessive loads on one or more of the wind turbine components. Upgrading the wind turbine (such as by up-rating the torque) may temporarily slow the wind turbine and act as a brake to help reduce or prevent loads.

[0055] De-rating the wind turbine may include speed de-rating, torque de-rating, or a combination of both. Further, as mentioned, the wind turbine 10 may be de-rating by pitching one or more of the rotor blades 22 about their pitch axis 28. More specifically, the controller 26 may generally control each pitch adjustment mechanism 32 so as to change the pitch angle of each rotor blade 22 between 0 degrees (i.e., the power position of the rotor blade 22) and 90 degrees (i.e., the feathered position of the rotor blade 22). Thus, in one embodiment, the controller 26 may command a new pitch set point (e.g., from 0 degrees to 5 degrees), while in another embodiment, the controller 26 may specify a new pitch constraint (e.g., a constraint that ensures that subsequent pitch commands are at least 5 degrees).

[0056] In another embodiment, the wind turbine 10 may be temporarily degraded by modifying the torque demand on the generator 24. In general, the torque demand may be modified using any suitable method, process, structure, and / or means known in the art. For example, in one embodiment, the torque demand on the generator 24 may be controlled using the controller 26 by transmitting suitable control signals / commands to the generator 24 so as to modulate the magnetic flux generated within the generator 24.

[0057] The wind turbine 10 may also be temporarily degraded by yaw the nacelle 22 to change the angle of the nacelle 16 relative to the wind direction. In further embodiments, the controller 26 may be configured to actuate one or more mechanical brakes to reduce the rotational speed of the rotor blades 22, thereby reducing component loads. In further embodiments, the controller 26 may be configured to perform any suitable control action known in the art. In addition, the controller 26 may implement a combination of two or more control actions.

[0058] Now refer to Figure 5 , a flow chart of one embodiment of a method 200 for reducing loads acting on a rotor blade of a wind turbine is shown. The method 200 may be performed using, for example, the method described above with reference to Figure 1-4 For purposes of illustration and discussion, Figure 5 The steps are depicted as being performed in a particular order. Using the disclosure provided herein, one of ordinary skill in the art will appreciate that the various steps of method 200 or any of the methods disclosed herein may be adjusted, modified, rearranged, performed simultaneously, or modified in various ways without departing from the scope of the present disclosure.

[0059] As shown at (202), the method 200 may include determining a blade state estimate for a rotor blade via the state estimator 102 of the controller 26. As shown at (204), the method 200 may include reconstructing one or more load signals for the rotor blade 22 from the blade state estimate using modal analysis via the controller 26 such that the load signal(s) include an advance time. As shown at (206), the method 200 may include comparing the load signal(s) for the rotor blade 22 to a load threshold. As shown at (208), the method 200 may include implementing a control action based on the comparison such that the advance time provided by the load signal(s) allows the control action to be implemented before a destructive load occurs on the rotor blade 22.

[0060] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any device or system and performing any combined method. The patentable scope of the invention is defined by the claims, and may include other examples that 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 do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal language of the claims.

Claims

1. A method for alleviating loads acting on a rotor blade of a wind turbine, the method comprising: determining a blade state estimate of the rotor blade via a state estimator of a controller; reconstructing, via the controller, one or more load signals for the rotor blade from the blade state estimate using modal analysis such that the one or more load signals include an advance time; comparing one or more load signals of the rotor blade to a load threshold; implementing a control action based on the comparison such that the lead time provided by the one or more load signals allows the control action to be implemented before a damaging load occurs on the rotor blade; receiving a measured tip deflection of the rotor blade, a swing-direction natural frequency of the rotor blade for one or more resonant modes, and a gain of one or more load signals for the rotor blade; as well as A future swing-wise blade tip deflection of the rotor blade for the one or more resonant modes is estimated based on the measured tip deflection, the swing-wise natural frequency, and a gain for the one or more load signals.

2. The method according to claim 1, characterized in that Determining a blade condition estimate of the rotor blade further comprises: receiving measurement data related to the rotor blade from one or more sensors; and A blade condition estimate of the rotor blade is determined based on the measurement data.

3. The method according to claim 2, characterized in that The one or more sensors include at least one of a micro inertial measurement unit (MIMU), a strain gauge, an accelerometer, a pressure sensor, a vibration sensor, a proximity sensor, or a camera sensor.

4. The method according to claim 1, characterized in that: The one or more load signals include at least one of a blade tip deflection, a blade bending moment, or a blade force of the rotor blade.

5. The method according to claim 1, characterized in that Using the modal analysis also includes determining a velocity or deflection of a blade modal response of the rotor blade.

6. The method according to claim 5, characterized in that Determining the velocity or deflection of the blade modal response of the rotor blade also includes using Euler-Bernoulli beam theory.

7. The method according to claim 5, characterized in that Determining a velocity or deflection of a blade modal response of the rotor blade further comprises: Future blade bending moments are estimated based on future swing-wise blade tip deflections of the rotor blade for the one or more resonance modes.

8. The method according to claim 7, characterized in that The gain is a horizontal gain.

9. The method according to claim 7, characterized in that: Estimating future swing-wise blade tip deflections of the rotor blade for the one or more resonance modes further includes estimating future swing-wise blade tip deflections of the rotor blade for a first resonance mode and a second resonance mode.

10. The method according to claim 9, characterized in that Estimating the future blade bending moment based on the future swing-direction blade tip deflection of the rotor blade for the one or more resonance modes further comprises: The future blade bending moment is estimated based on the future swing-wise blade tip deflection for the first resonance mode, the future swing-wise blade tip deflection for the second resonance mode, and one or more conversion constants.

11. The method according to claim 10, characterized in that Comparing the one or more load signals of the rotor blade to the load threshold also includes comparing the future blade bending moment to the load threshold.

12. The method according to claim 11, characterized in that Implementing the control action based on the comparison further includes adjusting a pitch angle of the rotor blades.

13. The method according to claim 12, characterized in that Adjusting the pitch angle of the rotor blades further comprises at least one of: determining an updated pitch angle limit for the rotor blade based on an expected decrease in the one or more load signals when the future blade bending moment exceeds the load threshold, or The pitch angle limit is allowed to decay exponentially to the original pitch angle limit when the future blade bending moment is below the load threshold.

14. A system for mitigating loads acting on a rotor blade of a wind turbine, the system comprising: one or more sensors configured to generate measurement data related to the rotor blade; a controller communicatively coupled to the one or more sensors, the controller comprising a processor having a state estimator programmed therein, the controller configured to perform a plurality of operations comprising: determining, via the state estimator, a blade state estimate of the rotor blade based on the measurement data; reconstructing one or more load signals for the rotor blade from the blade state estimate using modal analysis such that the one or more load signals include an advance time; comparing one or more load signals of the rotor blade to a load threshold; implementing a control action based on the comparison such that the lead time provided by the one or more load signals allows the control action to be implemented before a damaging load occurs on the rotor blade; receiving a measured tip deflection of the rotor blade, a swing-direction natural frequency of the rotor blade for one or more resonant modes, and a gain of one or more load signals for the rotor blade; and A future swing-wise blade tip deflection of the rotor blade for the one or more resonant modes is estimated based on the measured tip deflection, the swing-wise natural frequency, and a gain for the one or more load signals.

15. The system according to claim 14, characterized in that The one or more sensors include at least one of a micro inertial measurement unit (MIMU), a strain gauge, an accelerometer, a pressure sensor, a vibration sensor, a proximity sensor, or a camera sensor.

16. The system according to claim 14, characterized in that The one or more load signals include at least one of a blade tip deflection, a blade bending moment, or a blade force of the rotor blade.

17. The system according to claim 14, characterized in that Using the modal analysis also includes determining a velocity or deflection of a blade modal response of the rotor blade.

18. The system according to claim 17, characterized in that Determining the velocity or deflection of the blade modal response of the rotor blade also includes using Euler-Bernoulli beam theory.

19. The system according to claim 17, characterized in that Determining a velocity or deflection of a blade modal response of the rotor blade further comprises: Future blade bending moments are estimated based on future swing-wise blade tip deflections of the rotor blade for the one or more resonance modes.

20. The system according to claim 19, characterized in that Implementing the control action based on the comparison further includes adjusting the pitch angle of the rotor blade, wherein adjusting the pitch angle of the rotor blade further includes at least one of: determining an updated pitch angle limit for the rotor blade based on an expected decrease in the one or more load signals when the future blade bending moment exceeds the load threshold, or The pitch angle limit is allowed to decay exponentially to the original pitch angle limit when the future blade bending moment is below the load threshold.

Images