Patent Description:
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 one or more rotor blades. The rotor blades are the primary elements for converting wind energy into electrical energy. The blades typically have the cross-sectional profile of an airfoil such that, during operation, air flows over the blade producing a pressure difference between its sides. Consequently, a lift force, which is directed from the pressure side towards the suction side, acts on the blade. The lift force generates torque on the main rotor shaft, which is connected to a generator for producing electricity.

The amount of power that may be produced by a wind turbine is typically limited by structural limitations (i.e. design loads) of the individual wind turbine components. For example, the blade root of a wind turbine may experience loads (e.g. a blade root resultant moment) associated with both average loading due to turbine operation and dynamically fluctuating loads due to environmental conditions. Such loading may damage turbine components, thereby eventually causing the turbine components to fail. The fluctuating loads can change day-to-day or 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, upflow, or similar. Specifically, for example, loads experienced by a wind turbine may vary with wind speed.

As such, it is imperative to ensure loads acting on the wind turbine do not exceed design loads. Thus, many wind turbines employ one or more sensors configured to measure the loads acting on the various wind turbine components. Though the sensors may provide the desired information, new sensor systems can be complex and expensive to install. Further, the sensors may provide inaccurate information and can be prone to fail.

Additionally, wind turbines utilize control systems configured to estimate loads acting on the wind turbine based on a wind turbine thrust. The terms "thrust," "thrust value," "thrust parameter" or similar as used herein are meant to encompass a force acting on the wind turbine due to the wind. The thrust force comes from a change in pressure as the wind passes the wind turbine and slows down. Such control strategies estimate loads acting on the wind turbine by determining an estimated thrust using a plurality of turbine operating conditions, such as, for example, pitch angle, power output, generator speed, and air density. The operating conditions are inputs for the algorithm, which includes a series of equations, one or more aerodynamic performance maps, and one or more look-up tables (LUTs). For example, the LUT may be representative of a wind turbine thrust. A +/- standard deviation of the estimated thrust may also be calculated, along with an operational maximum thrust and a thrust limit. As such, the wind turbine may be controlled based on a difference between the maximum thrust and the thrust limit.

Such existing controls, however, are tuned to minimize the blade root resultant moment irrespective of the load direction and pitch angle, thus always targeting the worst case situation. Accordingly, such controls operate conservatively using additional pitch travel and also giving up annual energy production in the process. Examples of prior art can be found in <CIT> and <CIT>.

In view of the foregoing, the art is continuously seeking new and improved systems for controlling extreme loads of wind turbine components, such as rotor blades, pitch bearings, and the hub that address the aforementioned issues.

In one aspect, the present subject matter is directed to a method for reducing extreme loads acting on a component of a wind turbine. The method includes measuring, via one or more sensors, a plurality of operating parameters of the wind turbine. Further, the method includes predicting, via a processor, at least one blade moment of at least one rotor blade of the wind turbine based on the plurality of operating parameters. The method also includes predicting, via the processor, a load (e.g. such as a blade root resultant moment) and an associated load angle of the at least one rotor blade as a function of the at least one blade moment. Moreover, the method includes predicting, via the processor, a pitch angle of the at least one rotor blade of the wind turbine. In addition, the method includes generating, via the processor, a load envelope for the component that comprises at least one load value for the pitch angle and the load angle. Thus, the method includes implementing, via a controller, a control action when the load is outside of the load envelope.

In an embodiment, the component may include, for example, the rotor blade, a pitch bearing, or a hub of the wind turbine. In another embodiment, the plurality of operating parameters of the wind turbine may include any one of or a combination of the following: rotor position, thrust, loads, power, speed, torque, blade weight, gravity, pitch angle, nodding moment, overhang moment, bearing lubrication schedule, a rotor azimuth angle, and/or a yawing moment.

In further embodiments, predicting the blade moment(s) of the rotor blade of the wind turbine may include calculating an edgewise blade moment of the rotor blade as a function of the plurality of operating parameters and estimated states of the wind turbine. In addition, predicting the blade moment(s) of the rotor blade of the wind turbine may include calculating a blade flap moment of the rotor blade as a function of the rotor position, the blade weight, and the torque.

In several embodiments, predicting the load and the associated load angle as a function of the blade moment(s) may include calculating the load and the associated load angle as a function of the edgewise blade moment of the rotor blade and the blade flap moment of the rotor blade. In such embodiments, calculating the load and the associated load angle as a function of the edgewise blade moment of the rotor blade and the blade flap moment of the rotor blade may include calculating the associated load angle by dividing the blade flap moment of the rotor blade by the edgewise blade moment of the rotor blade and calculating the load as a function of the associated load angle.

In particular embodiments, predicting the pitch angle of the rotor blade(s) of the wind turbine may include calculating the pitch angle of the rotor blade(s) of the wind turbine based on one or more controller commands.

In further embodiments, implementing the control action when the load is outside of the load envelope may include pitching the rotor blade(s). In such embodiments, pitching the rotor blade(s) may include collective pitching of a plurality of rotor blades of the wind turbine, independently pitching each of the plurality of rotor blades, and/or cyclically pitching each of the plurality of rotor blades.

In another aspect, the present disclosure is directed to a system for reducing extreme loads acting on a component of a wind turbine. The system includes one or more sensors configured to measure a plurality of operating parameters of the wind turbine and a controller configured with the one or more sensors. The controller includes a processor configured to perform a plurality of operations, including but not limited to predicting at least one blade moment of at least one rotor blade of the wind turbine based on the plurality of operating parameters, predicting a load and an associated load angle of the rotor blade(s) as a function of the blade moment(s), the load corresponding to a blade root resultant moment of the rotor blade(s), predicting a pitch angle of the rotor blade(s) of the wind turbine, generating a load envelope for the component that includes at least one load value for the pitch angle and the load angle, and implementing a control action when the load is outside of the load envelope.

Generally, the present disclosure is directed to improved systems and methods for improved extreme load control for wind turbine components, such as the rotor blades, pitch bearings, and the hub. More specifically, the method aims to use an extreme component envelope at each load angle and pitch angle. For example, the load magnitude and load angles are predicted using the imbalance load measurements, thrust estimates, and the rotor position, along with pitch angle predictions. The predicted load magnitude is compared against the load envelope to determine the necessary control action. Thus, the present disclosure limits unnecessary pitching and energy loss associated with controlling for a single extreme load.

In a particular embodiment, for example, margins on certain wind turbine components are determined using a load envelope of load angles and blade pitch angles. The data is used in the controller to determine how close the wind turbine is operating to the stress limit. The controller uses proximity sensor information and estimated states to predict the edgewise blade load. Similarly, the twisting moment may be predicted based on the rotor position, stored weight data, and rotor torque. The combined information is used to predict the load angle and magnitude. The pitch angle may also be predicted based on controller commands. Such information may then be used to compare against the envelope information. The controller then acts to reduce the load using this information when an exceedance is predicted.

Referring now to <FIG>, a perspective view of one embodiment of a wind turbine <NUM> that may implement the control technology according to the present disclosure is illustrated. As shown, the wind turbine <NUM> generally includes a tower <NUM> extending from a support surface <NUM>, a nacelle <NUM> mounted on the tower <NUM>, and a rotor <NUM> coupled to the nacelle <NUM>. The rotor <NUM> includes a rotatable hub <NUM> and at least one rotor blade <NUM> coupled to and extending outwardly from the hub <NUM>. For example, in the illustrated embodiment, the rotor <NUM> includes three rotor blades <NUM>. However, in an alternative embodiment, the rotor <NUM> may include more or less than three rotor blades <NUM>. Each rotor blade <NUM> may be spaced about the hub <NUM> to facilitate rotating the rotor <NUM> to enable kinetic energy to be transferred from the wind into usable mechanical energy, and subsequently, electrical energy. For instance, the hub <NUM> may be rotatably coupled to an electric generator <NUM> (<FIG>) positioned within the nacelle <NUM> to permit electrical energy to be produced.

The wind turbine <NUM> may also include a wind turbine controller <NUM> centralized within the nacelle <NUM>. However, in other embodiments, the controller <NUM> may be located within any other component of the wind turbine <NUM> or at a location outside the wind turbine. Further, the controller <NUM> may be communicatively coupled to any number of the components of the wind turbine <NUM> in order to control the operation of such components and/or to implement a correction action. As such, the controller <NUM> may include a computer or other suitable processing unit. Thus, in several embodiments, the controller <NUM> may include suitable computer-readable instructions that, when implemented, configure the controller <NUM> to perform various different functions, such as receiving, transmitting and/or executing wind turbine control signals. Accordingly, the controller <NUM> may 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 turbine <NUM> as will be discussed in more detail below.

Referring now to <FIG>, a simplified, internal view of one embodiment of the nacelle <NUM> of the wind turbine <NUM> shown in <FIG> is illustrated. As shown, the generator <NUM> may be coupled to the rotor <NUM> for producing electrical power from the rotational energy generated by the rotor <NUM>. For example, as shown in the illustrated embodiment, the rotor <NUM> may include a rotor shaft <NUM> coupled to the hub <NUM> for rotation therewith. The rotor shaft <NUM> may, in turn, be rotatably coupled to a generator shaft <NUM> of the generator <NUM> through a gearbox <NUM>. As is generally understood, the rotor shaft <NUM> may provide a low speed, high torque input to the gearbox <NUM> in response to rotation of the rotor blades <NUM> and the hub <NUM>. The gearbox <NUM> may then be configured to convert the low speed, high torque input to a high speed, low torque output to drive the generator shaft <NUM> and, thus, the generator <NUM>.

Each rotor blade <NUM> may also include a pitch adjustment mechanism <NUM> configured to rotate each rotor blade <NUM> about its pitch axis <NUM>. Further, each pitch adjustment mechanism <NUM> may include a pitch drive motor <NUM> (e.g., any suitable electric, hydraulic, or pneumatic motor), a pitch drive gearbox <NUM>, and a pitch drive pinion <NUM>. In such embodiments, the pitch drive motor <NUM> may be coupled to the pitch drive gearbox <NUM> so that the pitch drive motor <NUM> imparts mechanical force to the pitch drive gearbox <NUM>. Similarly, the pitch drive gearbox <NUM> may be coupled to the pitch drive pinion <NUM> for rotation therewith. The pitch drive pinion <NUM> may, in turn, be in rotational engagement with a pitch bearing <NUM> coupled between the hub <NUM> and a corresponding rotor blade <NUM> such that rotation of the pitch drive pinion <NUM> causes rotation of the pitch bearing <NUM>. Thus, in such embodiments, rotation of the pitch drive motor <NUM> drives the pitch drive gearbox <NUM> and the pitch drive pinion <NUM>, thereby rotating the pitch bearing <NUM> and the rotor blade <NUM> about the pitch axis <NUM>. Similarly, the wind turbine <NUM> may include one or more yaw drive mechanisms <NUM> communicatively coupled to the controller <NUM>, with each yaw drive mechanism(s) <NUM> being configured to change the angle of the nacelle <NUM> relative to the wind (e.g., by engaging a yaw bearing <NUM> of the wind turbine <NUM>).

Still referring to <FIG>, the wind turbine <NUM> may also include one or more sensors <NUM>, <NUM> for measuring various operating parameters that may be required to various blade moments as described in more detail below. For example, in various embodiments, the sensors may include blade sensors <NUM> for measuring a pitch angle of one of the rotor blades <NUM> or for measuring a load acting on one of the rotor blades <NUM>; generator sensors (not shown) for monitoring the generator <NUM> (e.g. torque, rotational speed, acceleration and/or the power output); sensors for measuring the imbalance loading in the rotor (e.g. main shaft bending sensors); and/or various wind sensors <NUM> for measuring various wind parameters, such as wind speed, wind peaks, wind turbulence, wind shear, changes in wind direction, air density, or similar. Further, the sensors may be located near the ground of the wind turbine, on the nacelle, or on a meteorological mast of the wind turbine. 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 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, 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 may be configured to provide a direct measurement of the parameters being monitored or an indirect measurement of such parameters. Thus, the sensors may, for example, be used to generate signals relating to the parameter being monitored, which can then be utilized by the controller <NUM> to determine the actual parameter.

Referring now to <FIG>, there is illustrated a block diagram of one embodiment of various components of the controller <NUM> according to the present disclosure. As shown, the controller <NUM> may include one or more processor(s) <NUM> and associated memory device(s) <NUM> configured 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 controller <NUM> may also include a communications module <NUM> to facilitate communications between the controller <NUM> and the various components of the wind turbine <NUM>. Further, the communications module <NUM> may include a sensor interface <NUM> (e.g., one or more analog-to-digital converters) to permit signals transmitted from the sensors <NUM>, <NUM> to be converted into signals that can be understood and processed by the processors <NUM>. It should be appreciated that the sensors <NUM>, <NUM> may be communicatively coupled to the communications module <NUM> using any suitable means. For example, as shown in <FIG>, the sensors <NUM>, <NUM> are coupled to the sensor interface <NUM> via a wired connection. However, in other embodiments, the sensors <NUM>, <NUM> may be coupled to the sensor interface <NUM> via a wireless connection, such as by using any suitable wireless communications protocol known in the art.

As used herein, the term "processor" refers not only to integrated circuits referred to in the art as being included in a computer, but also refers to a controller, a microcontroller, a microcomputer, a programmable logic controller (PLC), an application specific integrated circuit, and other programmable circuits. Additionally, the memory device(s) <NUM> may generally comprise memory element(s) including, but not limited to, computer readable medium (e.g., random access memory (RAM)), computer readable non-volatile medium (e.g., a flash memory), a floppy disk, a compact disc-read only memory (CD-ROM), a magneto-optical disk (MOD), a digital versatile disc (DVD) and/or other suitable memory elements. Such memory device(s) <NUM> may generally be configured to store suitable computer-readable instructions that, when implemented by the processor(s) <NUM>, configure the controller <NUM> to perform various functions including, but not limited to, determining one or more current wind turbine parameters of the wind turbine <NUM> based on the plurality of operating data, determining a maximum wind turbine parameter, transmitting suitable control signals to implement control actions to reduce loads acting on the wind turbine, and various other suitable computer-implemented functions.

Referring now to <FIG>, a flow diagram of method <NUM> for reducing extreme loads acting on a component of a wind turbine according to one embodiment of the present disclosure is illustrated. In an embodiment, for example, the component may include, for example, one of the rotor blades <NUM>, the pitch bearing <NUM>, or the hub <NUM> of the wind turbine <NUM>. The method <NUM> is described herein as implemented using, for example, the wind turbine <NUM> described above. However, it should be appreciated that the disclosed method <NUM> may be implemented using any other suitable wind turbine now known or later developed in the art. In addition, although <FIG> depicts steps performed in a particular order for purposes of illustration and discussion, the methods described herein are not limited to any particular order or arrangement. One skilled in the art, using the disclosures provided herein, will appreciate that various steps of the methods can be omitted, rearranged, combined and/or adapted in various ways.

As shown at (<NUM>), the method <NUM> includes measuring, via one or more sensors, a plurality of operating parameters of the wind turbine <NUM>. For example, in one embodiment, sensors <NUM>, <NUM> are configured to measure or otherwise monitor the various operating parameters of the wind turbine <NUM>. More specifically, as mentioned, the operating parameters may include any one of or a combination of the following: rotor position, thrust, loads, power, speed, torque, blade weight, gravity, pitch angle, nodding moment, overhang moment, bearing lubrication schedule, a rotor azimuth angle, and/or a yawing moment.

Thus, as shown at (<NUM>), the method <NUM> includes predicting, via the processor <NUM>, at least one blade moment of the rotor blade(s) <NUM> of the wind turbine <NUM> based on the plurality of operating parameters. For example, as shown in <FIG>, an exploded view of one embodiment of the wind turbine <NUM> is shown, particularly illustrating various axes of rotation and corresponding forces and moments acting on the wind turbine <NUM>. The peak loads of the wind turbine <NUM> may vary between turbines, but in general, typically correspond to at least one of the following: the blade root resultant moment (e.g. MrB, which includes pitch and hub loads MxB, Myb, and Mz3), main shaft loads (e.g. Myr, Mzr), main bearing loads (e.g. Mxr, Myr), yaw drive loads (e.g. Mxk), yaw bolts/bearing/flange loads (e.g. Myk, Mzk) or tower bending loads (e.g. Mxt, Myt, and Mzt). It should be understood that the peak loads as described herein may also include any additional loads experienced by the wind turbine <NUM> and that the loads illustrated in <FIG> are provided for example purposes only.

Thus, in particular embodiments, the processor <NUM> may be configured to calculate an edgewise blade moment (MyB) of the rotor blade(s) <NUM> as a function of the operating parameters and estimated states of the wind turbine <NUM>. In addition, the processor <NUM> may be configured to predict calculate blade flap moment (MzB) of the rotor blade(s) <NUM> as a function of the rotor position, the blade weight, and the torque.

Referring back to <FIG>, as shown at (<NUM>), the method <NUM> includes predicting, via the processor <NUM>, a load (e.g. such as the blade root resultant moment, MrB) and an associated load angle of the rotor blade(s) <NUM> as a function of the blade moments described herein. For example, in several embodiments, the processor <NUM> may be configured to calculate the load and the associated load angle as a function of the edgewise blade moment of the rotor blade(s) <NUM> and the blade flap moment of the rotor blade(s) <NUM>. More specifically, in such embodiments, the processor <NUM> may be configured to calculate the associated load angle by dividing the blade flap moment of the rotor blade(s) <NUM> by the edgewise blade moment of the rotor blade(s) <NUM> and calculating the load as a function of the associated load angle.

As shown at (<NUM>), the method <NUM> includes predicting, via the processor <NUM>, a pitch angle of the rotor blade(s) <NUM> of the wind turbine <NUM>. In particular embodiments, for example, the processor <NUM> is configured to predict the pitch angle of the rotor blade(s) <NUM> by calculating the pitch angle of the rotor blade(s) of the wind turbine as a function of one or more controller commands.

As shown at (<NUM>), the method <NUM> includes generating, via the processor <NUM>, a load envelope for the component that includes one or more load values for the pitch angle and the load angle. For example, <FIG> each illustrate examples of a load envelope according to the present disclosure.

Referring back to <FIG>, as shown at (<NUM>), the method <NUM> includes implementing, via the controller <NUM>, a control action when the load is outside of the load envelope. For example, in particular embodiments, the control action may include pitching the rotor blade(s) <NUM>. More specifically, in such embodiments, pitching the rotor blade(s) <NUM> may include collective pitching of a plurality of rotor blades <NUM> of the wind turbine <NUM>, independently pitching each of the plurality of rotor blades <NUM>, and/or cyclically pitching each of the plurality of rotor blades <NUM>.

Advantages of the present disclosure can be better understood with respect to <FIG>. More specifically, as shown, graphs <NUM>, <NUM> illustrate the blade resultant moment (MrB) (y-axis) versus the load angle (x-axis) from a time series near rated wind speed according to the present disclosure. The graph <NUM> of <FIG> illustrates a scenario with RIC always on, whereas the graph <NUM> of <FIG> illustrates a scenario with without RIC on. The conventional load thresholds are represented as lines <NUM>, <NUM>, respectively, in each of <FIG>, whereas the load thresholds of the present disclosure are represented as lines <NUM>, <NUM>, respectively. Thus, as shown, the load thresholds <NUM>, <NUM> of the present disclosure avoid MrB control activations for all points within areas <NUM>, <NUM>. This is advantageous as the number of activations correlates to energy loss and additional pitching from MrB control.

It should be further understood that the control action as described herein may encompass any suitable command or constraint by the controller <NUM>. For example, in several embodiments, the control action may include temporarily de-rating or up-rating the wind turbine to prevent excessive loads on one or more of the wind turbine components. 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 or prevent loading. De-rating the wind turbine may include speed de-rating, torque de-rating or a combination of both. Further, as mentioned, the wind turbine <NUM> may be de-rated by pitching one or more of the rotor blades <NUM> about its pitch axis <NUM>. More specifically, the controller <NUM> may generally control each pitch adjustment mechanism <NUM> in order to alter the pitch angle of each rotor blade <NUM> between <NUM> degrees (i.e., a power position of the rotor blade <NUM>) and <NUM> degrees (i.e., a feathered position of the rotor blade <NUM>). As such, in one embodiment, the controller <NUM> may command a new pitch setpoint (e.g. from <NUM> degrees to <NUM> degrees), whereas in another embodiment, the controller <NUM> may specify a new pitch constraint (e.g. a constraint to ensure that subsequent pitch commands are at least <NUM> degrees).

In still another embodiment, the wind turbine <NUM> may be temporarily de-rated by modifying the torque demand on the generator <NUM>. 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 generator <NUM> may be controlled using the controller <NUM> by transmitting a suitable control signal/command to the generator <NUM> in order to modulate the magnetic flux produced within the generator <NUM>.

The wind turbine <NUM> may also be temporarily de-rated by yawing the nacelle <NUM> to change the angle of the nacelle <NUM> relative to the direction of the wind. In further embodiments, the controller <NUM> may be configured to actuate one or more mechanical brake(s) in order to reduce the rotational speed of the rotor blades <NUM>, thereby reducing component loading. In still further embodiments, the controller <NUM> may be configured to perform any appropriate control action known in the art. Further, the controller <NUM> may implement a combination of two or more control actions.

Referring now to <FIG>, a schematic flow diagram of a particular embodiment of a system <NUM> for reducing extreme loads acting on a component of a wind turbine according to the present disclosure is illustrated. As shown, the system <NUM> may include a controller <NUM> that receives D and Q moments <NUM>, a rotor azimuth angle <NUM>, and a gravitational load <NUM>. The controller <NUM> may then determine the MyB and the MzB moments <NUM>, <NUM> based on the received inputs. As shown at <NUM>, the controller <NUM> may determine the MrB load using the MyB and the MzB moments <NUM>, <NUM>. Further, as shown at <NUM>, the controller <NUM> may also determine the load angle using the MyB and the MzB moments <NUM>, <NUM>. As shown at <NUM>, the controller <NUM> can also predict the pitch angle. Thus, as shown at <NUM>, the controller <NUM> can determined the MrB threshold/envelope based on the load angle and the pitch angle. The MrB load <NUM> and the MrB threshold/envelope <NUM> can then be used to determine the pitch action (e.g. collective/independent/cyclic).

Claim 1:
A method for reducing extreme loads acting on a component of a wind turbine, the method comprising:
measuring, via one or more sensors, a plurality of operating parameters of the wind turbine;
predicting, via a processor, at least one blade moment of at least one rotor blade of the wind turbine based on the plurality of operating parameters;
predicting, via the processor, a load and an associated load angle of the at least one rotor blade as a function of the at least one blade moment;
predicting, via the processor, a pitch angle of the at least one rotor blade of the wind turbine;
generating, via the processor, a load envelope for the component that comprises at least one load value for the pitch angle and the load angle; and,
implementing, via a controller, a control action when the load is outside of the load envelope.