System and method for preventing excessive loading on a wind turbine

Systems and methods for preventing excessive loading on a wind turbine are disclosed. The method includes: measuring an actual wind parameter upwind from the wind turbine using one or more sensors; providing the measured wind parameter to a processor; providing a plurality of wind turbine operating data to the processor; utilizing the plurality of operating data to determine an estimated wind turbine condition at the wind turbine; generating a control wind profile based on the actual wind parameter and the estimated wind turbine condition; and, implementing a control action based on the control wind profile to prevent excessive loading from acting on the wind turbine.

FIELD OF THE INVENTION

The present invention relates generally to wind turbines, and more particularly, to systems and methods for preventing excessive loading from acting on a wind turbine.

BACKGROUND OF THE INVENTION

Wind power is considered one of the cleanest, most environmentally friendly energy sources presently available, and wind turbines have gained increased attention in this regard. A modern wind turbine typically includes a tower, a generator, a gearbox, a nacelle, and a rotor. The rotor typically includes a rotatable hub having one or more rotor blades attached thereto. A pitch bearing is typically configured operably between the hub and the rotor blade to allow for rotation about a pitch axis. The rotor blades capture kinetic energy of wind using known airfoil principles. The rotor blades transmit the kinetic energy in the form of rotational energy so as to turn a shaft coupling the rotor blades to a gearbox, or if a gearbox is not used, directly to the generator. The generator then converts the mechanical energy to electrical energy that may be deployed to a utility grid.

Changes in atmospheric conditions, for example, wind speed, wind turbulence, wind gusts, wind direction, and density may significantly influence power produced by the generator. A power output of the generator increases with wind speed until the wind speed reaches a rated wind speed for the turbine. At and above the rated wind speed, the generator operates at a rated power. The rated power is an output power at which the generator can operate with a level of fatigue or extreme load to turbine components that is predetermined to be acceptable. At wind speeds higher than a certain speed, typically referred to as a “trip limit” or “monitor set point limit,” the wind turbine may implement a control action, such as shutting down or de-rating the wind turbine in order to protect wind turbine components from damage. A static rated power and static trip limit are typically determined during a design stage of the wind turbine and therefore are not dependent upon changing wind conditions that may be present during operation of the wind turbine, such as high wind turbulence intensity or sudden wind gusts.

Conventional systems and methods for controlling wind turbines during such transient wind conditions utilize one or more sensors positioned on the wind turbine to detect wind conditions. For example, a wind speed sensor positioned on the wind turbine will measure a wind gust at substantially the same time as the wind gust strikes the rotor blades. As such, wind turbine operation adjustments are subject to a time lag between measurement of the wind gust and the control action. As a result, the wind gust may cause rotor acceleration that will create excessive turbine loading and fatigue. In some instances, the wind gust may cause the rotor speed or power output to exceed a trip limit, before a wind turbine operation adjustment is completed, causing a wind turbine shut down.

Other systems and methods have utilized upwind measuring sensors, such as LIDAR sensors, to address the aforementioned time lag. As such, a change in wind acceleration may be measured upwind from the wind turbine, and the control action may be preemptively adjusted to compensate for the change in wind speed once the wind reaches the wind turbine. Still further control technologies estimate a wind condition experienced by the wind turbine using various algorithms. Inputs to such algorithms may change slowly causing a time lag between estimating the wind condition and implementing the control action.

Accordingly, an improved system and method for detecting a transient wind condition upwind of a wind turbine so as to reduce loads acting on the wind turbine would be desired in the art. Further, a system and method that incorporated existing hardware and software would be advantageous.

BRIEF DESCRIPTION OF THE INVENTION

In one aspect, a method for preventing excessive loading from acting on a wind turbine is disclosed. The method includes measuring an actual wind parameter upwind from the wind turbine using one or more sensors; providing the measured actual wind parameter to a processor; providing operating data indicative of current wind turbine operation to the processor; determining an estimated wind turbine condition at the wind turbine based at least partially on the operating data; generating a control wind profile based on the actual wind parameter and the estimated wind turbine condition; and, implementing a control action based on the control wind profile to prevent excessive loading from acting on the wind turbine.

In such an embodiment, the actual wind parameter and the estimated wind turbine condition may be reflective of any of the following: a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, or similar such that the control wind profile reflects a direct comparison of the measured actual wind parameter and the estimated wind turbine condition.

In another embodiment, the method may include determining a future loading condition based at least partially on the actual wind parameter. Further, the method may further include determining a current loading condition based at least partially on the estimated wind turbine condition. As such, the method may then compare the current loading condition and the future loading condition and generate the control wind profile based at least partially on the comparison. In such an embodiment, the estimated wind turbine condition may be reflective of any of the following: a wind turbine thrust, a blade loading, a tower loading, a shaft loading, a nacelle loading, a hub loading or similar.

In another embodiment, the method may include implementing the control action when the control wind profile exceeds a predetermined threshold to protect the wind turbine from excessive loading. In addition, the control action may be a function of a magnitude of a difference between the control wind profile and the predetermined threshold. Alternatively, the control wind profile may represent an error between the actual wind parameter and the estimated wind turbine condition. As such, implementing the control action may be based on a magnitude of the error.

In various embodiments, the operating data may include a pitch angle, a generator speed, a power output, a torque output, an air density, a temperature, a pressure, or similar. Further, the step of measuring the actual wind parameter using one or more sensors may include utilizing at least one Light Detecting and Ranging (LIDAR) sensor. In still additional embodiments, the method may include utilizing one or more aerodynamic performance maps and one or more look-up tables to determine the estimated wind turbine condition.

Further, the control action as described herein may include at least one of: altering the pitch angle of a rotor blade, modifying a generator torque, modifying the generator speed, modifying the power output, yawing a nacelle of the wind turbine, braking one or more wind turbine components, activating an airflow modifying element on a rotor blade, or any other appropriate control action.

In another aspect, a method for preventing excessive loading from acting on a wind turbine is disclosed. The method includes measuring an actual wind parameter upwind of the wind turbine using one or more sensors; providing the measured actual wind parameter to a processor; determining an estimated future loading condition based at least partially on the measured actual wind parameter; and implementing a control action on the wind turbine based on the future loading condition to prevent excessive loading from acting on the wind turbine.

In another embodiment, the step of determining the future loading condition based at least partially on the actual wind parameter further includes utilizing one or more aerodynamic performance maps and one or more look-up tables. In another embodiment, the method may include implementing the control action when the future loading condition exceeds a predetermined threshold. Further, the method may include determining an error between the future loading condition and the predetermined threshold and implementing the control action based on a magnitude of the error to protect the wind turbine from excessive loading.

In still another aspect, a system for preventing excessive loading from acting on a wind turbine is disclosed. The system includes one or more sensors configured to measure an actual wind parameter upwind of the wind turbine; a processor communicatively coupled to the one or more sensors, and a controller communicatively coupled to the processor. The processor may be configured to: receive the measured actual wind parameter; receive operating data indicative of current wind turbine operation, determine an estimated wind turbine condition based on the operating data; and generate a control wind profile based on the actual wind parameter and the estimated wind turbine condition. The controller may then implement a control action based on the control wind profile to prevent excessive loading from acting on the wind turbine.

In further embodiments, the one or more sensors may include at least one Light Detecting and Ranging (LIDAR) sensor. Further, the processor may further include a wind turbine condition estimator. The wind turbine condition estimator having one or more aerodynamic performance maps and one or more look-up tables. As such, the one or more aerodynamic performance maps and the one or more look-up tables are configured to utilize the operating data to calculate the estimated wind turbine condition.

DETAILED DESCRIPTION OF THE INVENTION

Generally, the present subject matter is directed to a system and method for preventing excessive loading from acting on a wind turbine by detecting a wind condition before it reaches the wind turbine and implementing a corresponding corrective action. More specifically, one or more sensors may be used to detect an actual wind parameter upwind of the wind turbine. For example, in several embodiments, one or more Light Detecting and Ranging (LIDAR) sensors may be used to detect the actual wind parameter, such as a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, or similar. Further, operating data indicative of current wind turbine operation are also provided to a processor to determine an estimated wind turbine condition. The plurality of wind turbine operating data may include: a pitch angle, a generator speed, a power output, a torque output, an air density, a temperature, a pressure, or similar. In one embodiment, the estimated wind turbine condition may be representative of a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, or similar. In an alternative embodiment, the estimated wind turbine condition may be representative of a wind turbine thrust, a blade loading, a tower loading, a shaft loading, a nacelle loading, a hub loading, or similar. The method then generates a control wind profile based on the actual wind parameter and the estimated wind turbine condition. In one embodiment, for example, a transient wind condition, such as a wind gust, may be detected when the control wind profile exceeds a predetermined threshold. Alternatively, a transient wind condition may be detected when an error between the actual wind parameter and the estimated wind turbine condition is of a certain magnitude. Accordingly, the system and method may implement a control action to protect the wind turbine from excessive loading due to the transient wind condition.

Referring now to the drawings,FIG. 1illustrates a wind turbine10in accordance with aspects of the present disclosure. The wind turbine10comprises a rotor12having a plurality of wind turbine blades14mounted on a hub20. The wind turbine10also comprises a nacelle22that is mounted atop a tower16. The rotor12is operatively coupled to an electrical generator via drive train (not shown) housed within the nacelle22. The tower16exposes the blades14to the wind (directionally represented by arrow26), which causes the blades14to rotate about an axis28. The blades14transform the kinetic energy of the wind into a rotational torque, which is further transformed into electrical energy via the electrical generator.

Referring now toFIG. 2, a simplified, internal view of one embodiment of the nacelle22of the wind turbine10shown inFIG. 1is illustrated. As shown, a generator24may be disposed within the nacelle22. In general, the generator24may be coupled to the rotor12for producing electrical power from the rotational energy generated by the rotor12. For example, as shown in the illustrated embodiment, the rotor12may include a rotor shaft34coupled to the hub20for rotation therewith. The rotor shaft34may, in turn, be rotatably coupled to a generator shaft36of the generator24through a gearbox38. As is generally understood, the rotor shaft34may provide a low speed, high torque input to the gearbox38in response to rotation of the rotor blades14and the hub20. The gearbox38may then be configured to convert the low speed, high torque input to a high speed, low torque output to drive the generator shaft36and, thus, the generator24.

The wind turbine10may also include a controller30centralized within the nacelle22. Alternatively, the controller30may be located within any other component of the wind turbine10or at a location outside the wind turbine. Further, the controller30may be communicatively coupled to any number of the components of the wind turbine10in order to control the operation of such components and/or implement various correction actions as described herein. As such, the controller30may include a computer or other suitable processing unit. Thus, in several embodiments, the controller30may include suitable computer-readable instructions that, when implemented, configure the controller30to perform various different functions, such as receiving, transmitting and/or executing wind turbine control signals. Accordingly, the controller30may generally be configured to control the various operating modes (e.g., start-up or shut-down sequences), de-rate the wind turbine, and/or control various components of the wind turbine10as will be discussed in more detail below.

Still referring toFIG. 2, each rotor blade14may also include a pitch adjustment mechanism32configured to rotate each rotor blade14about its pitch axis33. Further, each pitch adjustment mechanism32may include a pitch drive motor40(e.g., any suitable electric, hydraulic, or pneumatic motor), a pitch drive gearbox42, and a pitch drive pinion44. In such embodiments, the pitch drive motor40may be coupled to the pitch drive gearbox42so that the pitch drive motor40imparts mechanical force to the pitch drive gearbox42. Similarly, the pitch drive gearbox42may be coupled to the pitch drive pinion44for rotation therewith. The pitch drive pinion44may, in turn, be in rotational engagement with a pitch bearing46coupled between the hub20and a corresponding rotor blade14such that rotation of the pitch drive pinion44causes rotation of the pitch bearing46. Thus, in such embodiments, rotation of the pitch drive motor40drives the pitch drive gearbox42and the pitch drive pinion44, thereby rotating the pitch bearing46and the rotor blade14about the pitch axis33. Similarly, the wind turbine10may include one or more yaw drive mechanisms66communicatively coupled to the controller30, with each yaw drive mechanism(s)66being configured to change the angle of the nacelle22relative to the wind (e.g., by engaging a yaw bearing68of the wind turbine10).

Referring toFIGS. 1-3, the wind turbine10may include one or more sensors48,50,52,54for measuring various wind parameters upwind of the wind turbine10. For example, as shown inFIG. 1, sensor48is located on the hub20so as to measure an actual wind parameter upwind from the wind turbine10. The actual wind parameter may be any of the following: a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, or similar. Further, the one or more sensors may include at least one LIDAR sensor for measuring upwind parameters. For example, as shown inFIG. 1, LIDAR sensor48is a measurement radar configured to scan an annular region around the wind turbine10and measure wind speed based upon reflection and/or scattering of light transmitted by the LIDAR sensor from aerosol. The cone angle (θ) and the range (R) of the LIDAR sensor48may be suitably selected to provide a desired accuracy of measurement as well as an acceptable sensitivity. In the illustrated embodiment, the LIDAR sensor48is located on the hub20whereupon the blades14are mounted. In further embodiments, the one or more LIDAR sensors may also be located near the base of the wind turbine tower16, on one or more of the wine turbine blades, on the nacelle, one a meteorological mast of the wind turbine, or at any other suitable location. In still further embodiments, the LIDAR sensor48may be located in any suitable location on or near the wind turbine10. Further, the LIDAR sensor48may be configured to measure a wind parameter ahead of at least one specific portion, typically the most significant sections of the blades14in terms of contributions of those sections to aerodynamic torque on the blades14. These sections may include, for example, sections close to the tip of the blade. The points ahead of the blades14at which wind speed is measured by the LIDAR sensor48is represented by plane72as shown inFIG. 1.

In alternative embodiments, the sensors48,50,52,54may be any other suitable sensors capable of measuring wind parameters upwind of the wind turbine10. For example, the sensors may be accelerometers, pressure sensors, angle of attack sensors, vibration sensors, MIMU sensors, camera systems, fiber optic systems, anemometers, wind vanes, Sonic Detection and Ranging (SODAR) sensors, infra lasers, radiometers, pitot tubes, rawinsondes, other optical sensors, and/or any other suitable sensors. It should be appreciated that, as used herein, the term “monitor” and variations thereof indicates that the various sensors of the wind turbine may be configured to provide a direct measurement of the parameters being monitored or an indirect measurement of such parameters. Thus, the sensors48,50,52,54may, for example, be used to generate signals relating to the parameter being monitored, which can then be utilized by the controller30to determine the actual condition.

Referring specifically toFIG. 3, there is illustrated a block diagram of one embodiment of the controller30according to the present disclosure. As shown, the controller30may include one or more processor(s)58, a wind turbine condition estimator56, and associated memory device(s)60configured to perform a variety of computer-implemented functions (e.g., performing the methods, steps, calculations and the like and storing relevant data as disclosed herein). Additionally, the controller30may also include a communications module62to facilitate communications between the controller30and the various components of the wind turbine10. Further, the communications module62may include a sensor interface64(e.g., one or more analog-to-digital converters) to permit signals transmitted from the sensors48,50,52,54to be converted into signals that can be understood and processed by the processors58. It should be appreciated that the sensors48,50,52,54may be communicatively coupled to the communications module62using any suitable means. For example, as shown inFIG. 3, the sensors48,50,52,54are coupled to the sensor interface64via a wired connection. However, in other embodiments, the sensors48,50,52,54may be coupled to the sensor interface64via a wireless connection, such as by using any suitable wireless communications protocol known in the art. As such, the processor58may be configured to receive one or more signals from the sensors48,50,52,54.

The wind turbine condition estimator56may be considered software that utilizes the plurality of operating data to calculate, in real-time, the estimated wind turbine condition. Further, the wind turbine condition estimator56may comprise firmware that includes the software, which may be executed by the processor58. Further, the wind turbine condition estimator56may be in communication with the various sensors and devices of the wind turbine10, which may provide the plurality of operating data to the wind turbine condition estimator56.

Referring now toFIGS. 4-5, several flow diagrams are depicted to illustrate various embodiments of the present disclosure. As shown in the embodiment illustrated inFIG. 4, a method100includes step102of measuring an actual wind parameter upwind from the wind turbine10using a sensor. The next step104includes providing the measured actual wind parameter to the processor58. Further, the method100includes a step106of providing operating data indicative of current wind turbine operation to the processor58. A next step108includes determining an estimated wind turbine condition at the wind turbine10based at least partially on the operating data. Further, the method includes step110of generating a control wind profile based on the actual wind parameter and the estimated wind turbine condition. The controller may then implement a control action based on the control wind profile (step114). More specifically, as shown, if the control wind profile exceeds a predetermined threshold, then the controller may implement the correction action (step114). Alternatively, if the control wind profile is below the predetermined threshold, then the method100is repeated beginning with step102. In various embodiments, the predetermined threshold may be pre-programmed within the controller30. Further, the predetermined threshold may be a constant threshold or may vary with wind speed and/or other operating parameters.

Referring nowFIG. 5, method200includes steps202,204,206,208, and210, which are similar to the embodiment ofFIG. 4. Rather than implementing a control action based on the predetermined threshold, however, the method200determines an error between the actual wind parameter and the estimated wind turbine condition (step212). The method200then implements the control action based on the magnitude of the error (step214). In such an embodiment, the predetermined threshold may be eliminated.

In each of the embodiments described above, the wind turbine condition estimator56may be configured to determine the estimated wind turbine condition as described herein. For example, in one embodiment, the wind turbine condition estimator56receives the operating data which may consist of any of the following: a pitch angle, a generator speed, a power output, a torque output, a temperature, a pressure, a tip speed ratio, an air density, or other similar operation condition. The wind turbine condition estimator56then calculates the estimated wind turbine condition as a function of various combinations of the operating data. In one embodiment, for example, the wind turbine condition estimator56may implement a control algorithm having a series of equations to determine the estimated wind turbine condition as a function of the pitch angle, the generator speed, the power output, and the air density. Further, the equations may be solved using the operating data and one or more aerodynamic performance maps. In one embodiment, the aerodynamic performance maps are dimensional or non-dimensional tables that describe rotor loading and performance (e.g. power, thrust, torque, or bending moment, or similar) under given conditions (e.g. density, wind speed, rotor speed, pitch angles, or similar). As such, the aerodynamic performance maps may include: power coefficient, thrust coefficient, torque coefficient, and/or partial derivatives with respect to pitch angle, rotor speed, or tip speed ratio. Alternatively, the aerodynamic performance maps can be dimensional power, thrust, and/or torque values instead of coefficients.

Further, the wind turbine estimator56may also include one or more look-up tables (LUTs). In various embodiments, at least some of the LUTs may include: a wind turbine thrust, a blade loading, a tower loading, a shaft loading, a nacelle loading, a hub loading, or any other wind turbine loading condition. As such, depending on the embodiment, the estimated wind turbine condition may be representative of wind parameters near the wind turbine or loading conditions of the wind turbine. As mentioned, the wind parameters may include a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, or similar. Loading conditions may include a wind turbine thrust, a blade loading, a tower loading, a shaft loading, a nacelle loading, a hub loading, or similar. The wind turbine condition estimator56then provides or communicates the estimated wind turbine condition to the processor58.

Once the estimated wind turbine condition is calculated, the processor58may use the estimated wind turbine condition in various ways. For example, in one embodiment, where the estimated wind turbine condition is reflective of a wind parameter, the estimated wind turbine condition may be compared to the actual wind parameter directly to generate the control wind profile. Alternatively, where the estimated wind turbine condition represents a current turbine loading condition, the actual wind parameter may be used to determine a future loading condition, such that the current and future loading conditions may be compared. More specifically, the actual wind parameter may be used in combination with the aerodynamic performance maps and/or LUTs of the wind turbine condition estimator56to determine the future loading condition. In such an embodiment, the current loading condition and the future loading condition are compared and the control wind profile may be generated based at least partially on the comparison.

In still another embodiment, the processor58may use only the actual wind parameter and the aerodynamic performance maps and/or LUTs to calculate the future loading condition. In other words, determining the estimated wind turbine condition may be eliminated altogether. This embodiment may be further understood with respect to method300illustrated inFIG. 6. As shown, the method300includes measuring an actual wind parameter upwind from the wind turbine10using a sensor (step302). A next step304includes providing the actual wind parameter to the processor58. Further, the method300includes determining a future loading condition based at least partially on the actual wind turbine parameter (step306). In this embodiment, the controller30may then implement a control action based on the future loading condition (step308). Such an embodiment is capable of reducing loads acting on the wind turbine without utilizing current loading conditions (i.e. the estimated wind turbine condition).

The control action(s) as described herein may be any suitable control action so as to reduce loads acting on the wind turbine. For example, in several embodiments, the control action may include temporarily de-rating or up-rating the wind turbine to permit the loads acting on or more of the wind turbine components to be reduced or otherwise controlled. Up-rating the wind turbine, such as by up-rating torque, may temporarily slow down the wind turbine and act as a brake to help reduce loads. De-rating the wind turbine may include speed de-rating, torque de-rating or a combination of both. Further, the wind turbine may be de-rated by reducing speed and increasing torque, which can be beneficial so as to maintain power. In another embodiment, the wind turbine10may be de-rated by pitching one or more of the rotor blades14about its pitch axis33. More specifically, the controller30may generally control each pitch adjustment mechanism32in order to alter the pitch angle of each rotor blade14between −10 degrees (i.e., a power position of the rotor blade14) and 90 degrees (i.e., a feathered position of the rotor blade14). In still another embodiment, the wind turbine10may be temporarily de-rated by modifying the torque demand on the generator24. In general, the torque demand may be modified using any suitable method, process, structure and/or means known in the art. For instance, in one embodiment, the torque demand on the generator24may be controlled using the controller30by transmitting a suitable control signal/command to the generator24in order to modulate the magnetic flux produced within the generator24.

The wind turbine10may also be temporarily de-rated by yawing the nacelle22to change the angle of the nacelle22relative to the direction of the wind. In other embodiments, the controller30may be configured to actuate one or more mechanical brake(s) or activate an airflow modifying element on a rotor blade in order to reduce the rotational speed and/or load of the rotor blades14, thereby reducing component loading. In still further embodiments, the controller30may be configured to perform any appropriate control action known in the art. Further, the controller30may implement a combination of two or more control actions.

The system and method described herein may be better understood with reference toFIGS. 7-11, which illustrate a plurality of graphs according to the present disclosure. For purposes of example only, graphs7-8are illustrative of the actual wind parameter and the estimated wind turbine parameter being indicative of wind speed. As shown inFIG. 7, curve500illustrates the actual wind speed as obtained from a LIDAR sensor, whereas curve502illustrates the estimated wind speed (e.g. as determined by the wind turbine condition estimator56). Curve504illustrates the control wind profile (e.g. a comparison) based on the actual wind speed and the estimated wind speed. Curve508represents a predetermined threshold, which is typically reflective of an allowable design load. As mentioned, the processor58may be configured to determine if the control wind profile504exceeds the predetermined threshold508, and if it does, the controller may implement an appropriate control action. As illustrated, the control wind profile504exceeds the predetermined threshold508between time T1and T2, thereby indicating that a transient wind condition is likely occurring. As such, an appropriate control action may be implemented so as to prevent excessive loading from acting on the wind turbine.FIG. 8illustrates the same actual wind speed500and the same estimated wind speed502, however, the control wind profile506is based on an error between the actual wind speed and the estimated wind speed, such that the wind turbine may be controlled based on the error. As such, the predetermined threshold may be eliminated.

Referring now toFIG. 9, various advantages of controlling the wind turbine based on a future loading condition is illustrated. As shown, curve500again illustrates the actual wind speed. Curve510illustrates the estimated future loading experienced by the wind turbine. Curve508illustrates a predetermined threshold set to prevent excessive loading from acting on the wind turbine. At time T1, the system recognizes that the future loading condition is likely to exceed the predetermined threshold. As such, the system implements appropriate control action, wherein the load510is reduced below the predetermined threshold. Such an embodiment illustrates an advantage of predicting a future loading condition based on the actual wind parameter and controlling the wind turbine based on the future loading condition. In other words, in one embodiment, the present disclosure is capable of preventing excessive loading from acting on the wind turbine without utilizing current loading conditions (i.e. the estimated wind turbine condition).

Referring now toFIGS. 10 and 11, the graph illustrates various advantages of the present disclosure in regards to generator speed and wind turbine component loading. As shown, the actual wind speed500begins to increase prior to time T1, which indicates that a transient wind condition is occurring. Curve512illustrates the generator speed of the wind turbine without any control technology to detect a transient wind condition. Curve514represents the generator speed of a wind turbine implementing the control technology of the present disclosure. As shown in reference to baseline curve512, the generator speed increases due the transient wind condition, thereby causing a corresponding increase in wind turbine component loading516(FIG. 11), which may cause damage to various wind turbine components. In contrast, curves514and518illustrate an advantage of implementing the control technology of the present disclosure. As shown, the wind turbine condition estimator56as described herein detected the increase in actual wind speed early and implemented an appropriate control action before it reached the wind turbine to avoid potential damage caused by excess loading. More specifically, the present disclosure decreased generator speed (curve514) before the increase in actual wind speed reached the wind turbine, thereby preventing the corresponding loading (curve510) from increasing above design loads.

It should also be appreciated that an advantage of the present invention is that the system and method may be implemented using existing components of the wind turbine10. As such, a user is not required to purchase, install, and maintain new equipment. Further, the controller30may be integrated with a broader control system, such as, but not limiting of, a wind turbine control system, a plant control system, a remote monitoring system, or combinations thereof.