Methods for estimating values of wind turbine operational parameters

Abstract

To provide methods for estimating values of wind turbine operational parameters.SOLUTION: The present disclosure relates to methods (100, 200) for estimating an actual value of an operational parameter (67) of a wind turbine (10). A method (100) comprises determining (120) which sensors of a plurality of sensors (61) of the wind turbine (10) are reliable and which sensors of the plurality of sensors (61) are unreliable. The method (100) further comprises estimating (130) the actual value of the operational parameter (67) based on a mathematical model and on data related to the operational parameter (63) measured by the reliable sensors.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to a method for estimating values ​​of operational parameters of a wind turbine, and further to a wind turbine controller and a wind turbine. [Background technology]

[0002] Modern wind turbines are commonly used to provide electricity to the power grid. This type of wind turbine generally includes a tower and a rotor disposed on the tower. The rotor typically includes a hub and a number of blades, which rotate under the influence of the wind on the blades. This rotation generates a torque, which is typically transferred via the rotor shaft to a generator, either directly ("direct drive" or "gearless") or using a gearbox. In this way, the generator produces electricity, which can be provided to the power grid.

[0003] The wind turbine hub may be rotatably coupled to the front of the nacelle. The wind turbine hub is coupled to a rotor shaft, which is rotatably mounted to the nacelle using one or more rotor shaft bearings located in a frame within the nacelle. The nacelle is a housing located on top of the wind turbine tower that can house and protect the gearbox and generator (if not located outside the nacelle) and, depending on the wind turbine, other components such as power converters and auxiliary systems.

[0004] Wind turbines are equipped with several sensors. The sensors monitor the wind turbine and help to check, for example, the health of the wind turbine or to control the way in which the wind turbine is operated. For example, a wind turbine may consist of temperature sensors, vibration sensors, pressure sensors, etc., which can check if the wind turbine is damaged or if there is a danger to the wind turbine. Also, a wind turbine may have built-in sensors such as wind speed sensors, rotor speed sensors, azimuth sensors, etc., and the measurements of these sensors can be used to control the wind turbine. There are various ways in which a wind turbine can be controlled.

[0005] The generated power can be controlled based on the tip speed ratio (TSR), pitch angle and torque. TSR depends on rotor speed, rotor radius and wind speed. Therefore, in some cases sensors are used to measure wind speed, rotor speed, pitch angle and / or torque and to calculate the setpoints of parameters, e.g. pitch angle and torque, and / or to check that the setpoints are adhered to.

[0006] An anemometer can measure wind speed and direction, which can be used to calculate, for example, an appropriate pitch angle of the wind turbine blades and / or an appropriate generator torque. Similarly, an encoder located on the generator rotor can be used to measure rotor speed, which can also be taken into account in calculating the pitch angle and / or generator torque. Appropriate actuators, such as pitch drives, yaw drives, power electronics, etc., can then be actuated to establish the desired behavior of the wind turbine.

[0007] However, some wind turbine sensors can be noisy and unreliable. For example, anemometers can be unreliable in measuring wind speed because they can only measure wind speed at hub height and behind the rotor plane, which can be disturbed by the rotor. Sensors can also be damaged and fail. If the sensor is related to the operation and control of the wind turbine, actuators can be overworked, resulting in increased vibrations and loads. This can result in suboptimal operation of the wind turbine and, in extreme cases, the integrity of the wind turbine can be compromised. Summary of the Invention

[0008] In one aspect of the disclosure, a method for estimating an actual value of an operational parameter of a wind turbine is provided. The method comprises receiving data related to the operational parameter from a plurality of sensors of the wind turbine and determining which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable. The method further comprises estimating the actual value of the operational parameter based on a mathematical model and on the data related to the operational parameter received from the reliable sensors.

[0009] According to this aspect, multiple sensors can be used to improve the accuracy of the determination of the operating parameter. It can be determined which of these wind turbine sensors provide reliable measurements. Measurements determined to be less reliable can be excluded when estimating the actual value of a particular operating parameter of the wind turbine. Thus, the accuracy of the estimated parameter value is improved.

[0010] Throughout this disclosure, the term (un)reliable with respect to sensors may cover at least both accuracy and precision aspects. In some examples, a sensor may be deemed unreliable, i.e. not trustworthy, because it is deemed not accurate, or not precise, or not precise and not accurate.

[0011] An operating parameter may be understood as a parameter that determines the operation of a wind turbine, for example a portion of the wind turbine or an element or component of the wind turbine. The operating parameter may be determined for use in controlling the wind turbine, for example the (actual) value of the operating parameter may be used as a setpoint for the wind turbine. In some examples the operating parameter may not be used directly as a setpoint for the wind turbine, but rather as a value against which the setpoint is determined. Examples of operating parameters are rotor speed, azimuth angle, pitch angle, generated power, etc.

[0012] Data related to an operating parameter may refer to data that directly or indirectly indicates the value of the operating parameter. For example, if the operating parameter is a rotational speed, data related to the operating speed may be the rotational speed itself, or may be, for example, position measurements from an encoder (the speed may be determined based on a one-time derivative of the position), currents measured in a converter (the rotational speed may be determined based on these currents), or other data from which the rotational speed can be derived or estimated.

[0013] In a further aspect of the disclosure, a wind turbine controller is provided comprising a processor and a memory including instructions that, when executed by the processor, cause the processor to receive data related to an operating parameter from a plurality of sensors of the wind turbine, determine which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable, and estimate an actual value of the operating parameter based on a mathematical model and the data related to the operating parameter received from the reliable sensors.

[0014] In a further aspect of the disclosure, there is provided a wind turbine comprising a tower, a nacelle provided on the top of the tower, and a rotor coupled to the nacelle, the rotor comprising a hub and a number of blades coupled to the hub via pitch bearings, the wind turbine further comprising the wind turbine controller of the previous aspect.

[0015] In a further aspect of the disclosure, a method for estimating a value of an operating parameter of a wind turbine is provided, the method comprising measuring data related to the operating parameter with a plurality of wind turbine sensors and determining which sensors are faulty or excessively noisy. The method further includes performing an initial estimate of an actual value of the operating parameter using a mathematical model and revising the initial estimate with data directly indicative of the operating parameter based on measurements by reliable sensors. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a perspective view of an example wind turbine. [Diagram 2] FIG. 2 is a simplified internal view of an example nacelle of the wind turbine of FIG. 1. [Diagram 3] 1 is a flow chart illustrating an example of a method for estimating actual values ​​of operating parameters of a wind turbine. [Figure 4]2 illustrates a schematic diagram of an example of a method for determining actual values ​​of operating parameters from measurements from wind turbine sensors; [Diagram 5] An example of a rotor speed curve from measurements by three wind turbine sensors and including actual rotor speed estimates is shown. [Figure 6] 6 shows an example of the difference between the measured rotor speed in FIG. 5 and the estimated rotor speed in FIG. [Figure 7] 5 is a flow chart illustrating another example of a method for estimating actual values ​​of operating parameters of a wind turbine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Reference will now be made in detail to the embodiments of the present disclosure, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation only, and not by way of limitation. Indeed, it will be apparent to those skilled in the art that various modifications and variations can be made in the present disclosure. For example, features illustrated or described as part of one embodiment can be used with another embodiment to yield still further embodiments. Thus, it is intended that the present disclosure cover such modifications and variations as come within the scope of the appended claims and their equivalents.

[0018] FIG. 1 is a perspective view of an example of a wind turbine 10. In this example, the wind turbine 10 is a horizontal axis wind turbine. Alternatively, the wind turbine 10 may be a vertical axis wind turbine. In this example, the wind turbine 10 includes a tower 15 extending from a support system 14 on a ground 12, a nacelle 16 attached to the tower 15, 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. In this example, the rotor 18 has three rotor blades 22. In alternative embodiments, the rotor 18 includes more or less than three rotor blades 22. The tower 15 may be fabricated from tubular steel to define a cavity (not shown in FIG. 1) between the support system 14 and the nacelle 16. In alternative embodiments, the tower 15 may be any suitable type of tower having any suitable height. According to an alternative, the tower may be a hybrid tower including a concrete portion and a steel tubular portion. It may also be a partial or complete lattice tower.

[0019] The rotor blades 22 are spaced relative to the hub 20 to rotate the rotor 18 and convert kinetic energy from the wind into usable mechanical energy, and therefore electrical energy. The rotor blades 22 are mated to the hub 20 by coupling blade root regions 24 to the hub 20 at a number of load transfer regions 26. The load transfer regions 26 may include hub load transfer regions and blade load transfer regions (both not shown in FIG. 1 ). Loads induced in the rotor blades 22 are transferred to the hub 20 via the load transfer regions 26.

[0020] In examples, rotor blades 22 may have a length ranging from about 15 meters (m) to about 90 m or more. Rotor blades 22 may have any suitable length that enables wind turbine 10 to function as described herein. For example, non-limiting examples of blade lengths include lengths of 20 m or less, 37 m, 48.7 m, 50.2 m, 52.2 m, or greater than 91 m. When wind strikes rotor blades 22 from wind direction 28, rotor 18 rotates about rotor axis 30. As rotor blades 22 rotate and experience centrifugal forces, rotor blades 22 also experience various forces and moments. As such, rotor blades 22 may deflect and / or rotate from a neutral, i.e., unbiased, position to a biased position.

[0021] Additionally, the pitch angles of the rotor blades 22, e.g., angles determining the orientation of the rotor blades 22 relative to the wind direction, may be varied by the pitch system 32 to control the load and power generated by the wind turbine 10 by adjusting the angular position of at least one rotor blade 22 relative to the wind vector. A pitch axis 34 of the rotor blades 22 is shown. During operation of the wind turbine 10, the pitch system 32 may vary the pitch angles of the rotor blades 22, among other things, to reduce the angle of attack of (some of) the rotor blades, which may facilitate reducing the rotational speed and / or facilitate stalling of the rotor 18.

[0022] In this embodiment, the blade pitch of each rotor blade 22 is individually controlled by the wind turbine controller 36 or the pitch control system 80. Alternatively, the blade pitch of all rotor blades 22 may be simultaneously controlled by these control systems.

[0023] Furthermore, in this embodiment, as the wind direction 28 changes, the yaw direction of the nacelle 16 can be rotated about a yaw axis 38 to position the rotor blades 22 relative to the wind direction 28 .

[0024] In this example, the wind turbine controller 36 is shown as being centrally located in the nacelle 16, but the wind turbine controller 36 may be a distributed control system located throughout the wind turbine 10, on the support system 14, in the wind farm, and / or at a remote control center. The wind turbine controller 36 may include one or more processors configured to perform one or more steps of the methods described herein. Additionally, many of the other components described herein include one or more processors. The wind turbine controller 36 may also include memory, e.g., one or more memory devices. As used herein, memory may 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 disks-read only memory (CD-ROM), magneto-optical disks (MOD), digital versatile disks (DVD), and / or other suitable memory elements.

[0025] FIG. 2 is an enlarged cross-sectional view of a portion of the wind turbine 10. In this example, the wind turbine 10 includes a nacelle 16 and a rotor 18 rotatably coupled to the nacelle 16. More specifically, a hub 20 of the rotor 18 is rotatably coupled to a generator 42 disposed within the nacelle 16 by a main shaft 44, a gearbox 46, a high-speed shaft 48, and a coupling 50. In the example, the main shaft 44 is disposed at least partially coaxially with a longitudinal axis (not shown) of the nacelle 16. Rotation of the main shaft 44 drives a gearbox 46, which drives the high-speed shaft 48 by converting the relatively slow rotational motion of the rotor 18 and main shaft 44 into a relatively fast rotational motion of the high-speed shaft 48. The latter is connected, with the aid of the coupling 50, to a generator 42 for generating electrical energy. Further, a transformer 90 and / or suitable electronics, switches and / or inverters may be arranged in the nacelle 16 to convert the electrical energy generated by the generator 42 having a voltage of, for example, 400V to 1000V into electrical energy having a medium voltage (for example, 10 to 35 kV). An offshore wind turbine may have a generator voltage of, for example, 650V to 3500V, and the transformer voltage may be, for example, 30 kV to 70 kV. Said electrical energy is conducted from the nacelle 16 to the tower 15 via a power cable.

[0026] In some examples, the wind turbine 10 may include one or more shaft sensors 51. The shaft sensors may be configured to monitor at least one of a torque load acting on the main shaft 44 and / or the high speed shaft 48 and the rotational speed of the shafts 44, 48. In some examples, the wind turbine 10 may include one or more generator sensors 53. The generator sensors may be configured to monitor at least one of a rotational speed of the generator 42 and a generator torque. The shaft sensors 51 and / or the generator sensors 53 may include, for example, one or more torque sensors (e.g., strain gauges or pressure sensors), optical sensors, accelerometers, magnetic sensors, speed sensors, and Micro-Inertial Measurement Units (MIMUs).

[0027] The gearbox 46, the generator 42 and the transformer 90 may be supported by a main support structural frame of the nacelle 16, optionally embodied as a main frame 52. The gearbox 46 may include a gearbox housing coupled to the main frame 52 by one or more torque arms 103. In an embodiment, the nacelle 16 also includes a main forward support bearing 60 and a main aft support bearing 62. Additionally, the generator 42 may be mounted to the main frame 52 by a decoupling support means 54, particularly to prevent vibrations of the generator 42 from being introduced into the main frame 52 and thereby causing a source of noise emissions.

[0028] Optionally, the main frame 52 is configured to carry the weight of the rotor 18 and nacelle 16 components, as well as the overall loads caused by wind and rotational loads, and to introduce these loads into the tower 15 of the wind turbine 10. The rotor shaft 44, generator 42, gearbox 46, high speed shaft 48, coupling 50, and supports 52, and any associated fastening, supporting, and / or fastening devices, including, but not limited to, forward and aft support bearings 60, 62, may be referred to as a drive train 64.

[0029] In some embodiments, the wind turbine may be a direct drive wind turbine without a gearbox 46. The generator 42 operates at the same rotational speed as the rotor 18 of a direct drive wind turbine and therefore generally has a much larger diameter than the generator used in a wind turbine with a gearbox 46 to provide the same amount of power as a wind turbine with a gearbox 46.

[0030] The nacelle 16 may also include a yaw drive mechanism 56 that is used to rotate the nacelle 16, and thereby the rotor 18, about the yaw axis 38 to control the approach or approach of the rotor blades 22 relative to the wind direction 28.

[0031] To properly position the nacelle 16 relative to the wind direction 28, the nacelle 16 may also include at least one meteorological measurement system including a wind vane and anemometer. The meteorological measurement system 58 may provide information including the wind direction 28 and / or wind speed to the wind turbine controller 36.

[0032] In this embodiment, pitch system 32 is disposed, at least in part, within hub 20 as a pitch assembly 66. Pitch assembly 66 includes one or more pitch drive systems 68 and at least one sensor 70. Each pitch drive system 68 is coupled to a respective rotor blade 22 (shown in FIG. 1 ) for modulating the pitch angle of rotor blade 22 along pitch axis 34. Only one of the three pitch drive systems 68 is shown in FIG. 2.

[0033] In this embodiment, the pitch assembly 66 includes at least one pitch bearing 72 coupled to the hub 20 and each rotor blade 22 (shown in FIG. 1 ) to rotate each rotor blade 22 about the pitch axis 34. The pitch drive system 68 includes a pitch drive motor 74, a pitch drive gearbox 76, and a pitch drive pinion 78. The pitch drive motor 74 is coupled to the pitch drive gearbox 76 such that the pitch drive motor 74 provides a mechanical force to the pitch drive gearbox 76. The pitch drive gearbox 76 is coupled to the pitch drive pinion 78 such that the pitch drive pinion 78 is rotated by the pitch drive gearbox 76. The pitch bearing 72 is coupled to the pitch drive pinion 78 such that rotation of the pitch drive pinion 78 causes rotation of the pitch bearing 72.

[0034] The pitch drive system 68 is coupled to the wind turbine controller 36 for adjusting the pitch angle of the rotor blades 22 in response to one or more signals from the wind turbine controller 36. In this example, the pitch drive motor 74 is any suitable motor driven by an electrical power and / or hydraulic system that enables the pitch assembly 66 to function as described herein. Alternatively, the pitch assembly 66 may include any suitable structure, configuration, arrangement, and / or components, such as, but not limited to, hydraulic cylinders, springs, and / or servo mechanisms. In certain embodiments, the pitch drive motor 74 is driven by the rotational inertia of the hub 20 and / or energy extracted from a stored energy source (not shown) that provides energy to components of the wind turbine 10.

[0035] The pitch assembly 66 may also include one or more pitch control systems 80 for controlling the pitch drive systems 68 in accordance with control signals from the wind turbine controller 36 in case of certain preferred conditions and / or upon overspeed of the rotor 18. In an example embodiment, the pitch assembly 66 includes at least one pitch control system 80 communicatively coupled to each pitch drive system 68 for controlling the pitch drive systems 68 independently from the wind turbine controller 36. In an example embodiment, the pitch control system 80 is coupled to the pitch drive systems 68 and to the sensors 70. During normal operation of the wind turbine 10, the wind turbine controller 36 may control the pitch drive systems 68 to adjust the pitch angle of the rotor blades 22.

[0036] According to one embodiment, a generator 84, comprised of, for example, a battery and an electrical capacitor, is disposed at or within the hub 20 and is coupled to the sensors 70, the pitch control system 80, and the pitch drive system 68 to provide a source of electrical power to these components. In this example, the power source 84 provides a continuous source of electrical power to the pitch assembly 66 during operation of the wind turbine 10. In an alternative embodiment, the power source 84 provides power to the pitch assembly 66 only during a power loss event of the wind turbine 10. A power loss event may include a loss or dip in the electrical grid, a malfunction of the electrical system of the wind turbine 10, and / or a failure of the wind turbine controller 36. During a power loss event, the generator 84 operates to provide electrical power to the pitch assembly 66 such that the pitch assembly 66 can operate during the power loss event.

[0037] In this example, pitch drive system 68, sensor 70, pitch control system 80, cables, and power supply 84 are each disposed within a cavity 86 defined by an inner surface 88 of hub 20. In alternative embodiments, these components may be disposed relative to and directly or indirectly coupled to an outer surface of hub 20.

[0038] As used herein, the term "processor" is not limited to integrated circuits referred to in the art as computers, but refers broadly to controllers, microcontrollers, microcomputers, programmable logic controllers (PLCs), application specific integrated circuits, and other programmable circuitry, and these terms are used interchangeably herein.

[0039] In one aspect of the disclosure, a method 100 is provided for estimating an actual value of an operating parameter of a wind turbine 10. The method 100 is illustrated generally in a flow chart in FIG. 3. The method comprises receiving data related to the operating parameter from a plurality of sensors of the wind turbine 10, at block 110. The method further comprises determining which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable, at block 120. The method further comprises estimating the actual value of the operating parameter based on the mathematical model and the data related to the operating parameter received from the reliable sensors, at block 130.

[0040] In this way, outputs of wind turbine sensors that are determined to be unreliable are not taken into account when estimating the actual measured value of the operating parameter. Thus, the accuracy of the actual value of the operating parameter can be improved. The above receiving, determining and estimating of blocks 110, 120, 130 may be performed, for example, by the wind turbine controller 36, e.g., the main wind turbine controller. The mathematical model may consist of multiple equations relating different operating parameters, e.g., rotor speed and pitch.

[0041] FIG. 4 shows diagrammatically an example of a method for determining an actual value of an operating parameter 67 from measurements 63 from a number of wind turbine sensors 61. In FIG. 4 five wind turbine sensors S1-S5 are visible. The sensors may be located on the wind turbine 10 or at any suitable location of the wind turbine 10. For example one sensor may be located on the power converter, another on the generator 42 and yet another on a slip ring between the stationary and rotating parts of the wind turbine rotor 18. In an embodiment at least one of the sensors may consist of or be an encoder. The encoder may be an absolute or incremental encoder. It will be apparent that in other embodiments different sensors at different locations and / or sensors measuring different variables and / or a different number of sensors may be used.

[0042] The method may further include using data related to the operational parameter 63 from two or more sensors of the plurality of sensors 61 to determine which sensors are reliable and which sensors are unreliable. In the simplified example of FIG. 4, sensors S1-S3 are configured to measure data d1-d3 related to a first operational parameter A, and sensors S4-S5 are configured to measure data d4-d5 related to a second operational parameter B, different from the first parameter. In other examples, the sensors may measure data related to multiple operational parameters. For example, measurements of one sensor may be used to determine two or more operational parameters.

[0043] The measurement data 63 may be indicative of the operating parameter directly or indirectly. For example, the operating parameter may be rotational speed and the sensor may measure the rotational speed. Thus, the sensor measurement is indicative of the operating parameter directly. Alternatively, the operating parameter may be rotational speed and the sensor may measure, for example, the current in a power converter and determine the rotor speed therefrom. Thus, the sensor measurement is indirectly indicative of the operating parameter.

[0044] In this regard, the method may further include determining at least one intermediate value 65 of the operational parameter based on measurement data associated with the operational parameter 63 measured by the at least one sensor, and estimating the actual value 67 of the operational parameter includes estimating the actual value 67 based on the at least one intermediate value 63. The intermediate value 65 may be directly indicative of the operational parameter.

[0045] In the example of Fig. 4, data relating to operating parameter 63 is measured and an intermediate value 65 is determined. If parameter A is for example a rotation speed, the measured data d1 to d3 can be used to determine intermediate operating parameters IP1_A to IP3_A. Depending on the measured values ​​appropriate formulas can be used. The intermediate operating parameters IP1_A to IP3_A can be different values ​​of parameter A (in this example the rotation speed).

[0046] In a non-limiting example, d1 is a sensor that measures the azimuth position of the generator rotor, d2 is a sensor that measures the azimuth position of the wind turbine rotor, and d3 is a sensor that measures the converter current. From these measurements, individual intermediate values ​​of the rotor speed may be calculated. These intermediate values ​​can be used to determine which sensor is reliable and to estimate the actual value of the rotor speed.

[0047] FIG. 5 shows three example rotor speeds obtained from measurements by three sensors. Because the sensors measure multiple data over a period of time, FIG. 5 shows rotor speed curves, and rotor speed in this specification refers to the rotor speed curves obtained from the individual sensors. These rotor speeds may be intermediate operating parameters 65. When the sensors directly measure the operating parameters, the values ​​of the measured data correspond to the values ​​of the intermediate operating parameters, and it is not necessary to calculate or otherwise derive the corresponding intermediate values.

[0048] As can be seen from FIG. 5, one of the rotational speeds obtained based on measurements from the wind turbine sensors is more variable, e.g. noisier, than the other two. The noise in the signal reduces the reliability of the sensor. If the noisiest rotational speed is taken into account when estimating the actual value of the rotational speed, the actual value of the rotational speed may be far from the true value. If this noisiest rotational speed is known to be an excessively noisy rotational speed, not including it in the estimation of the actual value of the rotational speed may provide a value of the rotational speed closer to the true value, i.e. a more accurate and precise actual value. Thus, the wind turbine 10 may behave better, e.g. aggressive pitching and high pitching activity may be avoided or in some cases at least reduced. Vibrations and oscillations of the wind turbine may also be reduced in further examples.

[0049] Within the scope of the present disclosure, determining that a sensor is unreliable may be performed in a number of ways. For example, determining which sensor is unreliable may include comparing two values ​​directly indicative of the operational parameter based on measurements from different sensors, such as comparing two intermediate values ​​of the operational parameter 65 determined based on different sensors, or comparing two values ​​of data related to the operational parameter 63 measured by different sensors. Because measurements may vary and sensors may not measure the exact same value every time, a range or group of values ​​(either measured 63 or determined 65) may be compared to a range or group of values ​​that should theoretically be equal.

[0050] For example, if a sensor is known to be more reliable than another sensor, the data provided by the other sensor can be compared with the data provided by the more reliable sensor. If the difference between both data (e.g. the average difference) exceeds a difference threshold, the corresponding sensor is determined to be less reliable. Other methods of comparing data measured by or obtained based on two or more sensors (i.e. values ​​of intermediate operating parameters) can also be implemented. It would also be possible to compare data measured by one sensor with a corresponding value of an intermediate operating parameter obtained based on measurements from another sensor.

[0051] Determining which sensors are unreliable may additionally or alternatively include analyzing the noise, e.g., how noisy the range of measurements of the sensor 63 is, or analyzing the noise, e.g., how noisy the range of mean values ​​65 is. Analyzing the noise may include, e.g., calculating the standard deviation of the range of values, or calculating the root-mean-square deviation (RMSD) of the range of values.

[0052] A noise threshold is defined, and if the noise threshold is reached or overcome, the corresponding sensor is determined to be unreliable. For example, the noise threshold may be set at a certain level depending on the sensors available and the operational parameters to be determined. In some examples, the noise threshold may be predefined for each sensor. For example, the noise threshold values ​​may be stored in a memory of the wind turbine controller 36. When the wind turbine starts up, the wind turbine can access and read these values. The noise threshold for each sensor may be different.

[0053] Peak-to-peak differences in a range of values ​​may also be determined. For example, if the peak-to-peak values ​​determined in a range of values ​​are less than a threshold, it may be determined that the sensor is not reliable because it is providing a frozen signal.

[0054] Yet another method of determining which sensors are unreliable may include comparing two or more values ​​directly indicative of the operational parameter based on measurements from different sensors with the actual value of the operational parameter estimated in one or more previous steps.

[0055] As a non-limiting example, it is known that due to the inertia of the wind turbine rotor, the rotational speed of the wind turbine rotor does not change very quickly. As a further example, if the azimuth angle and rotor speed were determined in a previous step, based on them, the expected subsequent azimuth angle may also be determined. If the azimuth angle received from a particular sensor deviates significantly from the expected azimuth angle, then reliability may be reduced.

[0056] As an example related to rotor speed, a first intermediate parameter 65 obtained from the measurements of a first sensor in a current step may have a value of 6.2. A first intermediate parameter 65 obtained from the measurements of a second sensor in a current step may have a value of 6.5. And a first intermediate parameter 65 obtained from the measurements of a third sensor in a current step may have a value of 5.7. In a previous step, the actual value of the operating parameter 67 was estimated to be 6.4. Thus, by comparing the values ​​6.2, 6.5, 5.7 with 6.4, it can be concluded that 5.7 is not a reliable value and therefore the third sensor is unreliable. A threshold value may be defined below which the corresponding sensor is deemed to be unreliable.

[0057] Also, if the measured or calculated data indicative of an operating parameter exceeds a threshold (e.g., a predefined threshold), the corresponding sensor may be considered invalid. For example, if it is known that the rotational speed of a rotor cannot exceed a certain threshold, and the measured / calculated data indicates that the rotational speed exceeds that threshold, the corresponding sensor may be considered invalid.

[0058] In the example of Figure 4, the value of intermediate operating parameter IP2_A has been discarded and sensor S2 has been determined to be unreliable. For parameter B, both sensors S4 and S4 have been determined to be reliable. Data d4 directly indicates parameter B, data d5 indirectly indicates parameter B, and intermediate operating parameter IP5_B directly indicates parameter B.

[0059] Once values ​​of the operating parameters that are considered reliable are present, these can be used to determine the actual value of the operating parameter. In particular, the actual value of the operating parameter 67 can be estimated based on data received from reliable sensors by combining data that directly indicate the operating parameter. For example, if three values ​​of the rotation speed are determined (measured and / or calculated from data from different sensors), the three values ​​can be combined to obtain a rotation speed value that is more accurate than a rotation speed value obtained from a single sensor.

[0060] Additionally, the actual value of the operational parameter 67 may be estimated by performing an initial estimate of the actual value of the operational parameter using a mathematical model and correcting the initial estimate with data directly indicative of the operational parameter based on data received from a reliable sensor. For example, an initial estimate for time (or step) t2 may be performed at time t1 (before time t2), and at time t2, measurements may be taken and used to correct the initial estimate.

[0061] Data indicative of the operational parameters based on data received from a reliable sensor may be assigned different weights for correction of the initial estimate. The weights assigned may depend at least on the measured or expected sensor noise for each sensor. For example, if a first sensor is noisier than a second sensor, data obtained from the first sensor may be assigned a smaller weight than data obtained from the second sensor. This may be used in addition to defining individual noise thresholds for each sensor.

[0062] A weight may also be assigned to the initial estimate of the actual value. In some examples, a weight may be assigned to the initial estimate of the actual value of the operating parameter based on one or more previous steps. If the mathematical model is deemed to provide a fairly good or very good initial estimate, the weight assigned to the initial estimate of the actual value may be high.

[0063] For example, if estimating the actual value of the operating parameter includes combining an initial estimate of the actual value, a first intermediate value, and a second intermediate value, the initial estimate may be assigned a weight of 0.7, the first intermediate value may be assigned a weight of 0.20, and the second intermediate value may be assigned a weight of 0.10, and the estimate may be the sum of each of these values ​​multiplied by their corresponding weights.

[0064] If all sensors are not determined to be reliable, they are ignored if the corresponding measurements and weights have already been assigned. The actual value of the operating parameter may then be determined as the sum of each intermediate value multiplied by its corresponding weight and divided by the sum of the weights.

[0065] As explained above, if a sensor is determined to be unreliable, data from that sensor is not considered and only data from reliable sensors is used to revise the initial estimate. In some examples, a Kalman filter may be used. In other examples, other suitable algorithms may be used. Reference numeral 69 in FIG. 4 may represent an estimation algorithm such as a Kalman filter.

[0066] In some examples, the mathematical model may consist of three states, specifically position, velocity and acceleration. That is, at one time or step (t1), the mathematical model may predict a position value, e.g. azimuth angle, a velocity value, e.g. rotor speed, and an acceleration value, e.g. rotor acceleration, for the next time or step (t2). Then, at the next time or step (t2), the values ​​of the three states may be obtained based on measurements of multiple sensors. For example, the position and velocity values ​​may be measured or derived from measurements, and the acceleration may be calculated. These values ​​may be combined with the position, velocity and acceleration values ​​predicted at the previous step (t1) to obtain the actual values ​​of position, velocity and acceleration at the current step (t2).

[0067] Since speed data may be derived from data related to the position, but position data may not be derived only from data related to the speed, at least one sensor configured to measure data indicative of the position and at least one sensor configured to measure data indicative of the speed may be provided. In particular, at least two sensors configured to measure data indicative of the position and at least two sensors configured to measure data indicative of the speed may be provided. Thus, for example, if one of the sensors configured to measure data indicative of the speed is determined to be unreliable, data from the other sensor configured to measure data indicative of the speed and / or data from at least one of the sensors configured to measure data indicative of the position can still be used.

[0068] In general, the operations at blocks 110 and 120 of method 100 may be performed iteratively. For example, if the initial estimate is revised, a new initial estimate for a later time may be performed, additional measurements may be performed to refine the new initial estimate, etc. If a Kalman filter is used, the covariance matrix may be monitored to determine how good the estimate of the actual values ​​is.

[0069] The curves of the actual rotor speed measurements are shown in Figure 5. In this example, measurements from three wind turbine sensors were used to correct the initial estimate of the rotor speed. However, as can be seen from Figure 5 and also from Figure 6, the data obtained from the noisiest sensor could have been discarded in order to obtain a more accurate actual rotor speed measurement. Figure 6 shows a schematic of the difference between the curves of the actual rotor speed measurements in Figure 5 and the curves of the rotor speed values ​​obtained from three different wind turbine sensors in Figure 5. One of the curves in Figure 6 is noisier than the other two curves.

[0070] If one or more sensors are determined to be unreliable, the method may further include stopping data measurement by one or more of the unreliable sensors. If more than one sensor are stopped from measuring data, the method may further include starting data measurement with one or more of the stopped unreliable sensors. After a period of time, it is checked whether the sensor works better than before. In this case, its output may be taken into account when determining the actual value of the operating parameter. If the sensor is still determined to be unreliable, it is not used in estimating the actual value.

[0071] There may be multiple wind turbine sensors for measuring data related to the operating parameters, as shown in the example of Figure 4. Because method 100 filters out data obtained from sensors determined to be unreliable, in some examples, the method may be applied when there are one or more sensors configured to provide data related to the corresponding operating parameters for which an actual value is to be estimated.

[0072] The operating parameter may in some examples be a set point for controlling the wind turbine. For example, one or more specific set points may be determined in the method 100. In other examples, the actual value of the operating parameter may be used later to calculate a set point. For example, it may be particularly complicated to obtain a reliable value for the speed of the rotor 18. If the actual value of the operating parameter is a rotor speed value, this value may be used as the set point and / or may be used in determining other set points, such as pitch angle and torque.

[0073] The operating parameter may in some examples be an azimuth angle. Having an accurate value of the azimuth angle can be useful, for example, to properly and effectively control the pitch angle of individual wind turbine blades 22. Of course, in other examples, the operating parameter may be different.

[0074] 4, the method 100 may be used to calculate actual values ​​of a number of operating parameters, for example, the method 100 may be used to estimate actual values ​​of rotor speed and azimuth angle.

[0075] According to a further aspect of the disclosure, a wind turbine controller 36 is provided. The wind turbine controller comprises a processor and a memory. The memory comprises instructions that, when executed by the processor, cause the processor to receive data related to an operating parameter from a plurality of sensors of the wind turbine, determine which sensors of the plurality of sensors 61 are reliable and which sensors of the plurality of sensors 61 are unreliable, and estimate an actual value of the operating parameter 67 based on a mathematical model and the data related to the operating parameter received from the reliable sensors.

[0076] The memory may generally be configured to store suitable computer readable instructions that, when executed by the processor, configure the wind turbine controller 36 to perform or trigger the execution of various steps disclosed herein, such as steps related to method 100. The memory may also be configured to store data, such as predefined data or data from measurements and / or calculations.

[0077] The wind turbine controller 36 may further include a communication module. The communication module may facilitate communication between the controller 36 and various components of the wind turbine 10. For example, the communication module may function as an interface to enable the turbine controller 36 to send control signals to the pitch drive system 66 for controlling the pitch angle of the rotor blades 22. The communication module may be configured to communicatively connect the controller 36 to other elements of the wind turbine 10. The connection may be implemented via a wired connection and / or via a wireless connection, e.g., by using any suitable wireless communication protocol known in the art. Additionally, the communication module may include a sensor interface, e.g., one or more analog-to-digital converters, to enable signals transmitted from one or more sensors (e.g., wind speed sensors) to be converted into signals that can be understood and processed by the processor.

[0078] According to a further aspect of the present disclosure, there is provided a wind turbine 10 comprising a tower 15, a nacelle 16 mounted on the tower 12, and a rotor 18 connected to the nacelle 16, the rotor comprising a hub 20 and a number of blades 22 connected to the hub, the wind turbine further comprising a wind turbine controller 36 of the previous aspect.

[0079] In some examples, the wind turbine is an offshore wind turbine. Because offshore wind turbines do not include a gearbox between the rotor 18 and the generator 42, it may be particularly difficult to determine some operating parameters, such as the rotational speed of the wind turbine rotor 18. Therefore, the above method is particularly useful for offshore wind turbines. Of course, the above method can also be implemented for onshore wind turbines.

[0080] According to a further aspect of the present disclosure, there is provided a method 200 for estimating values ​​of an operating parameter of a wind turbine. The method 200 is illustrated in the flow chart of Figure 7. The details and descriptions of the previous aspect may be combined and applied to this aspect and vice versa.

[0081] The method 200 comprises, in block 210, measuring data related to an operating parameter 63 using a plurality of wind turbine sensors 61, determining which sensors are faulty or excessively noisy in block 220, making an initial estimate of the actual value of the operating parameter using a mathematical model in block 230, and revising the initial estimate using data directly indicative of the operating parameter based on reliable sensor measurements 63 in block 240.

[0082] At least two or more sensors may allow for determination of data directly indicative of the operating parameter, i.e., there may be at least one redundant sensor.

[0083] Determining which sensor is faulty or excessively noisy may include reaching or exceeding a noise threshold, which in some examples is predefined and stored in the memory of the wind turbine controller 36.

[0084] The operating parameter may be a rotational speed. In another example, the operating parameter may be an azimuth angle. Values ​​of other operating parameters may also be determined by method 200.

[0085] A Kalman filter may be used to perform the steps of making an initial estimate and correcting the initial estimate. Other suitable algorithms may also be used.

[0086] This specification uses examples to disclose the teachings, including preferred embodiments, and to enable one of ordinary skill in the art to practice the teachings, including making and using any device or system, and performing the incorporated methods. The patentable scope is defined by the claims, and may include other examples that occur to those of ordinary skill in the art. Such other examples are intended to be included in the claims if they have structural elements that do not differ from the language of the claims, or if they include equivalent structural elements that do not differ substantially from the language of the claims. Aspects from the various embodiments described, and other known equivalents to each such aspect, can be mixed and matched by those of ordinary skill in the art to construct additional embodiments and techniques according to the principles of this application. When reference signs related to the drawings are placed in parentheses in the claims, they are merely intended to improve the clarity of the claims, and should not be construed as limiting the scope of the claims. [Explanation of symbols]

[0087] 10: Wind turbine 12: Ground 14: Support system 15: Tower 16: Nacelle 18: Rotor 20: Hub 22: Rotor blade 24: Blade root area 26: Load transfer area 28: Wind direction 30: Rotor shaft 32: Pitch system 34: Pitch axis 36: Wind turbine controller 8: Yaw axis 42: Generator 44: Main shaft 46: Gearbox 48: High speed shaft 50: Coupling 51: Shaft sensor 52: Main frame 53: Generator sensor 54: Decoupling support means 56: Yaw drive mechanism 58: Meteorological measurement system 60: Main forward support bearing 61, S1 to S5: Wind turbine sensors 62: Main rear support bearing 63: Measurement value / measurement data 64: Drive train 65: Intermediate value / first intermediate parameter 66: Pitch assembly 67: Operating parameter / actual value 68: Pitch drive system 69: Estimation algorithm 70: Sensor 72: Pitch bearing 74: Pitch drive motor 76: Pitch drive gearbox 78: Pitch drive pinion 80: Pitch control system 84: Power source / generator 86: Cavity 88: Inner surface 90: Transformer 101: Wind power plant busbar 102: Utility grid 103: Torque arm d1~d3: Data 67

Claims

1. A method (100) for estimating an actual value of an operating parameter (67) of a wind turbine (10), comprising: receiving (110) data relating to operational parameters (63) from a plurality of sensors (61) of the wind turbine (10); determining (120) which sensors of the plurality of sensors (61) are reliable and which sensors of the plurality of sensors (61) are unreliable; and estimating (130) an actual value of the operating parameter (67) based on the mathematical model and data related to the operating parameter (63) received from a reliable sensor.

2. The method of claim 1 , wherein determining (110) which sensors are unreliable comprises analyzing noise in a range of sensor measurements (61) or analyzing noise in a range of intermediate values ​​(65).

3. 2. The method of claim 1, wherein the step of determining (110) which sensors are unreliable comprises comparing two or more values ​​directly indicative of the operating parameter based on measurements from different sensors (61) with an actual value (67) of the operating parameter estimated in one or more previous steps.

4. 2. The method of claim 1, further comprising: using data relating to the operational parameter (63) from two or more of the plurality of sensors (61) to determine (120) which sensors are reliable and which sensors are unreliable.

5. determining at least one intermediate value of the operational parameter (65) based on measurement data related to the operational parameter (63) measured by the at least one sensor; The method of claim 1 , wherein estimating (120) an actual value of the operating parameter (67) comprises estimating the actual value (67) based on at least one intermediate value (65).

6. The method of claim 1 , wherein estimating (130) the actual value of the operating parameter (67) comprises combining data directly indicative of the operating parameter based on data received from a reliable sensor.

7. 7. The method of claim 6, wherein estimating (130) the actual value of the operating parameter (67) comprises performing an initial estimate of the actual value of the operating parameter using a mathematical model, and revising the initial estimate with data directly indicative of the operating parameter based on data received from a reliable sensor.

8. The method of claim 7 including using a Kalman filter to make an initial estimate and to refine the initial estimate.

9. The method of claim 1 , further comprising the step of stopping data measurements from one or more sensors that are unreliable.

10. The method of claim 1 , wherein the operating parameters are set points for controlling a wind turbine.

11. The method of claim 1 , wherein the operating parameter is one of rotor speed or azimuth angle.

12. The method of claim 1 , wherein the plurality of sensors (61) includes encoders.

13. A wind turbine controller (36) including a processor and a memory, the memory, when executed by the processor, causing the processor to: receiving data relating to operational parameters (63) from a plurality of sensors (61) of the wind turbine (10); determining which sensors of the plurality of sensors (61) are reliable and which sensors of the plurality of sensors (61) are unreliable; - estimating an actual value of the operating parameter (67) based on the mathematical model and on data on the operating parameter (63) received from a reliable sensor; a wind turbine controller (36) including instructions to:

14. A wind turbine (10), comprising:

14. A wind turbine (10) comprising a tower (15), a nacelle (16) provided on top of the tower (15), and a rotor (18) connected to the nacelle (16), the rotor (18) comprising a hub (20) and a number of blades (22) connected to the hub (20), the wind turbine (10) further comprising a wind turbine controller (36) according to claim 13.

15. 15. The wind turbine of claim 14, wherein the wind turbine (10) is an offshore wind turbine.

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