Method for estimating value of wind turbine operating parameter

Abstract

The present disclosure relates to a method (100, 200) for estimating an actual value (67) of an operating parameter of a wind turbine (10). The method (100) comprises determining (120) which of a plurality of sensors (61) of the wind turbine (10) are reliable and which of the plurality of sensors (61) are unreliable. The method (100) further includes estimating (130) an actual value (67) of the operating parameter based on the mathematical model and based on data (63) relating to the operating parameter measured by the reliable sensor.

Description

Technical Field

[0001] The present disclosure relates to a method for estimating a value of an operating parameter of a wind turbine. The present disclosure further relates to a wind turbine controller and a wind turbine. Background Art

[0002] Modern wind turbines are often used to supply electricity to an electrical grid. Such wind turbines generally comprise a tower and a rotor arranged on the tower. The rotor, which typically comprises a hub and a plurality of blades, is set to rotate under the influence of the wind on the blades. The rotation generates a torque, which is usually transmitted to a generator via a rotor shaft (either directly ("direct drive" or "gearless") or by using a gearbox). In this way, the generator produces electricity that can be supplied to an electrical grid.

[0003] The hub of the wind turbine may be rotatably coupled to the front of the nacelle. The hub of the wind turbine may be connected to the rotor shaft, and the rotor shaft may then be rotatably mounted in the nacelle using one or more rotor shaft bearings arranged in a frame inside the nacelle. The nacelle is a housing arranged on top of the wind turbine tower that may house and protect the gearbox (if present) and the generator (if not placed outside the nacelle) and (depending on the wind turbine) additional components such as a power converter, and auxiliary systems.

[0004] The wind turbine includes a plurality of sensors. The sensors may monitor the wind turbine and, for example, help check the health of the wind turbine or help control how the wind turbine operates. For example, the wind turbine may include temperature sensors, vibration sensors, pressure sensors, and others to check if the wind turbine is damaged or if it is at risk. The wind turbine may also include sensors such as wind speed sensors, rotor speed sensors, azimuth sensors, and others, the measurements of which may be used to control the wind turbine. Different ways of controlling a wind turbine may be implemented.

[0005] The generated power can be controlled based on the terminal speed ratio (TSR), the pitch angle and the torque. The TSR depends on the rotor speed, the rotor radius and the wind speed. Therefore, in some examples, sensors can be used to measure the wind speed, the rotor speed, the pitch angle and / or the torque to calculate the set points for the parameters (e.g., the pitch angle and the torque), and / or to check that the set points are followed.

[0006] An anemometer can measure wind speed and wind direction, and the measured wind speed and wind direction can be used, for example, to calculate a suitable pitch angle for the wind turbine blades and / or a suitable generator torque. Similarly, an encoder arranged with the generator rotor can be used to measure the rotor speed, and the measured rotor speed can also be considered when calculating the pitch angle and / or the generator torque. Appropriate actuators (e.g., pitch drives, yaw drives, power electronics, and others) can then be activated to establish the desired behavior of the wind turbine.

[0007] However, some wind turbine sensors may be noisy and unreliable. For example, an anemometer may not be reliable in measuring wind speed, because the wind speed may only be measured at hub height and behind the rotor plane and is therefore disturbed by the rotor. In addition, the sensor may become damaged and fail. If the sensor is relevant for the operation and control of the wind turbine, the actuator may be overused, and vibrations and loads may increase. This may lead to suboptimal operation of the wind turbine and, in severe cases, risks to the integrity of the wind turbine. Summary of the invention

[0008] In one aspect of the present disclosure, a method for estimating an actual value of an operating parameter of a wind turbine is provided. The method includes receiving data related to the operating 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 also includes estimating the actual value of the operating parameter based on a mathematical model and based on the data related to the operating parameter received from the reliable sensors.

[0009] According to this aspect, multiple sensors may be used to increase the accuracy in determining an operating parameter. It may be determined which of these wind turbine sensors provide reliable measurements. When estimating the actual value of a certain operating parameter of the wind turbine, measurements that are not considered reliable may be excluded. The accuracy of the value of the estimated parameter may thus be increased.

[0010] Throughout this disclosure, the term (un)reliable about sensors may at least cover both accuracy and precision. In some examples, a sensor may be considered unreliable, i.e., untrustworthy, because it is considered to be inaccurate, or imprecise, or both inaccurate and imprecise.

[0011] An operating parameter may be understood as a parameter that may determine the operation of a wind turbine, such as a part of a wind turbine or an element or component of a 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 set point for the wind turbine. In some examples, the operating parameter may not be used directly as a set point for the wind turbine, but as a value from which the set point is determined. Some examples of operating parameters are rotor speed, azimuth angle, pitch angle and generated power.

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

[0013] In another aspect of the present disclosure, a wind turbine controller is provided. The wind turbine controller includes a processor and a memory. The memory includes instructions that, when executed by the processor, cause the processor to receive data related to operating parameters 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 actual values ​​of the operating parameters based on a mathematical model and based on the data related to the operating parameters received from the reliable sensors.

[0014] In another aspect of the present disclosure, a wind turbine is provided. The wind turbine includes a tower, a nacelle on top of the tower, and a rotor connected to the nacelle. The rotor includes a hub and a plurality of blades connected to the hub through a pitch bearing. The wind turbine also includes a wind turbine controller of the previous aspect.

[0015] In another aspect of the present disclosure, a method for estimating a value of an operating parameter of a wind turbine is provided. The method includes measuring data related to the operating parameter using a plurality of wind turbine sensors, and determining which sensors are faulty or have excess noise. The method also includes performing an initial estimate of an actual value of the operating parameter using a mathematical model, and correcting the initial estimate using data directly indicative of the operating parameter based on measurements by reliable sensors.

[0016] Technical solution 1. A method for estimating an actual value of an operating parameter of a wind turbine, the method comprising:

[0017] receiving data related to the operating parameter from a plurality of sensors of the wind turbine;

[0018] determining which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable; and

[0019] An actual value of the operating parameter is estimated based on a mathematical model and based on the data related to the operating parameter received from reliable sensors.

[0020] Technical Solution 2. A method according to Technical Solution 1, wherein determining which sensors are unreliable includes analyzing noise in a series of measurement results of the sensor, or analyzing noise in a series of intermediate values.

[0021] Technical Solution 3. A method according to Technical Solution 1 or 2, wherein determining which sensors are unreliable includes comparing two or more values ​​directly indicating the operating parameters based on measurement results from different sensors with actual values ​​of the operating parameters estimated in one or more previous steps.

[0022] Technical Solution 4. The method according to any one of Technical Solutions 1-3 also includes using data related to the operating parameters from two or more sensors among the multiple sensors to determine which sensors are reliable and which sensors are unreliable.

[0023] Technical solution 5. The method according to any one of technical solutions 1-4 further includes determining at least one intermediate value of the operating parameter based on measured data related to the operating parameter measured by at least one sensor, and wherein

[0024] Estimating the actual value of the operating parameter includes estimating the actual value based on the at least one intermediate value.

[0025] Technical Solution 6. A method according to any one of Technical Solutions 1-5, wherein estimating the actual value of the operating parameter includes combining data directly indicating the operating parameter based on data received from the reliable sensor.

[0026] Technical Solution 7. A method according to Technical Solution 6, wherein estimating the actual value of the operating parameter includes using the mathematical model to perform an initial estimation of the actual value of the operating parameter, and correcting the initial estimation using the data directly indicating the operating parameter based on data received from the reliable sensor.

[0027] Technical Solution 8. The method according to Technical Solution 7 includes using a Kalman filter to perform the initial estimation and to correct the initial estimation.

[0028] Technical Solution 9. The method according to any one of Technical Solutions 1-8 also includes stopping using one or more of the unreliable sensors to measure data.

[0029] Technical Solution 10. The method according to any one of Technical Solutions 1-9, wherein the operating parameter is a set point for controlling the wind turbine.

[0030] Technical Solution 11. A method according to any one of Technical Solutions 1-10, wherein the operating parameter is one of a rotor speed or an azimuth angle.

[0031] Technical Solution 12. A method according to any one of Technical Solutions 1-11, wherein the multiple sensors include an encoder.

[0032] Technical solution 13. A wind turbine controller, comprising a processor and a memory, wherein the memory comprises instructions, which, when executed by the processor, cause the processor to:

[0033] receiving data related to operating parameters from a plurality of sensors of the wind turbine;

[0034] determining which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable; and

[0035] An actual value of an operating parameter is estimated based on a mathematical model and based on said data related to said operating parameter received from reliable sensors.

[0036] Technical Solution 14. A wind turbine comprising a tower, a nacelle on the top of the tower, a rotor connected to the nacelle, the rotor comprising a hub and a plurality of blades connected to the hub, and the wind turbine also comprising a wind turbine controller according to Technical Solution 13.

[0037] Technical Solution 15. A wind turbine according to Technical Solution 14, wherein the wind turbine is an offshore wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A perspective view showing one example of a wind turbine;

[0039] Figure 2 Show Figure 1 A simplified interior view of an example of a nacelle of a wind turbine;

[0040] Figure 3 A flow chart showing an example of a method for estimating an actual value of an operating parameter of a wind turbine;

[0041] Figure 4 schematically illustrates an example of how actual values ​​of operating parameters may be determined from measurements from wind turbine sensors;

[0042] Figure 5 An example of a rotor speed curve obtained from measurements by three wind turbine sensors and a rotor speed curve including an estimated actual value of the rotor speed is shown;

[0043] Figure 6 Show Figure 5 The measured rotor speed is related to Figure 5 An example of the difference between the estimated rotor speeds of ; and

[0044] Figure 7A flow chart showing another example of a method for estimating an actual value of an operating parameter of a wind turbine. DETAILED DESCRIPTION

[0045] Reference will now be made in detail to the embodiments of the present disclosure, one or more examples of which are shown in the drawings. Each example is provided by way of explanation only and is not intended to be limiting. In fact, it will be apparent to those skilled in the art that various modifications and variations may be made in the present disclosure. For example, a feature shown or described as a part of an embodiment may be used with another embodiment to produce yet other embodiments. Therefore, it is intended that the present disclosure cover such modifications and variations as fall within the scope of the appended claims and their equivalents.

[0046] Figure 1 is a perspective view of an example of a wind turbine 10. In the example, wind turbine 10 is a horizontal-axis wind turbine. Alternatively, wind turbine 10 may be a vertical-axis wind turbine. In the example, wind turbine 10 includes a tower 15 extending from a support system 14 on the ground 12, a nacelle 16 mounted on tower 15, and a rotor 18 coupled to nacelle 16. Rotor 18 includes a rotatable hub 20, and at least one rotor blade 22 coupled to hub 20 and extending outwardly from hub 20. In the example, rotor 18 has three rotor blades 22. In alternative embodiments, rotor 18 includes more or less than three rotor blades 22. Tower 15 may be made of tubular steel to define a cavity (not in the cavity) between support system 14 and nacelle 16. Figure 1 ). In alternative embodiments, the tower 15 is any suitable type of tower having any suitable height. According to an alternative, the tower may be a hybrid tower including a portion made of concrete and a tubular steel portion. Furthermore, the tower may be a partial or full lattice tower.

[0047] Rotor blades 22 are spaced about hub 20 to facilitate rotating rotor 18 to enable kinetic energy to be converted from the wind into usable mechanical energy and subsequently into electrical energy. Rotor blades 22 are coupled to hub 20 by coupling blade root regions 24 to hub 20 at a plurality of load transfer regions 26. Load transfer regions 26 may have hub load transfer regions and blade load transfer regions (both not in the same region). Figure 1 ). Loads induced to rotor blades 22 are transferred to hub 20 via load transfer regions 26 .

[0048] In an example, rotor blades 22 may have a length in a range 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 20 m or less, 37 m, 48.7 m, 50.2 m, 52.2 m, or a length greater than 91 m. When wind strikes rotor blades 22 from a wind direction 28, rotor 18 rotates about rotor axis 30. When rotor blades 22 rotate and are subjected to centrifugal forces, rotor blades 22 are also subjected to various forces and moments. Thus, rotor blades 22 may deflect and / or rotate from a neutral position or a non-deflected position to a deflected position.

[0049] In addition, the pitch angle of rotor blades 22 (e.g., an angle that determines the orientation of rotor blades 22 relative to the wind direction) can be changed by pitch system 32 to control the load and power generated by wind turbine 10 by adjusting the angular position of at least one rotor blade 22 relative to the wind vector. A pitch axis 34 is shown for rotor blades 22. During operation of wind turbine 10, pitch system 32 can specifically change the pitch angle of rotor blades 22 such that the angle of attack of (portions of) the rotor blades is reduced, which facilitates reducing the rotational speed and / or facilitating stalling of rotor 18.

[0050] In an example, the blade pitch of each rotor blade 22 is individually controlled by wind turbine controller 36 or by pitch control system 80. Alternatively, the blade pitch for all rotor blades 22 may be controlled simultaneously by the control system.

[0051] Furthermore, in an example, as wind direction 28 changes, the yaw orientation of nacelle 16 may be rotated about yaw axis 38 to position rotor blades 22 relative to wind direction 28 .

[0052] In the example, the wind turbine controller 36 is shown as being centralized within the nacelle 16, however, the wind turbine controller 36 may be a distributed control system throughout the wind turbine 10, on the support system 14, within 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 of the steps of the method described herein. In addition, many of the other components described herein include one or more processors. The wind turbine controller 36 may also include a memory, such as one or more memory devices. As used herein, a memory may include a memory element, which includes, but is not limited to, a computer-readable medium (e.g., a random access memory (RAM)), a computer-readable non-volatile medium (e.g., a flash memory), a floppy disk, a compact disk read-only memory (CD-ROM), a magneto-optical disk (MOD), a digital versatile disk (DVD), and / or other suitable memory elements.

[0053] Figure 2 1 is an enlarged cross-sectional view of a portion of a wind turbine 10. In the example, the wind turbine 10 includes a nacelle 16 and a rotor 18 rotatably coupled to the nacelle 16. More specifically, the hub 20 of the rotor 18 is rotatably coupled to a generator 42 positioned 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 at least partially disposed coaxially with a longitudinal axis (not shown) of the nacelle 16. The rotation of the main shaft 44 drives the gearbox 46, which then drives the high-speed shaft 48 by converting a relatively slow rotational movement of the rotor 18 and the main shaft 44 into a relatively fast rotational movement of the high-speed shaft 48. The latter is connected to the generator 42 by means of a coupling 50 for generating electrical energy. In addition, a transformer 90 and / or suitable electronics, switches and / or inverters may be arranged in the nacelle 16 in order to transform the electrical energy generated by the generator 42, which has a voltage between, for example, 400 V and 1000 V, into electrical energy having a medium voltage (e.g., 10-35 kV). An offshore wind turbine may have a generator voltage between, for example, 650 V and 3500 V, and a transformer voltage between, for example, 30 kV and 70 kV. The electrical energy is conducted from the nacelle 16 to the tower 15 via power cables.

[0054] In some examples, the wind turbine 10 may include one or more shaft sensors 51. The shaft sensor may be configured to monitor at least one of the 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 sensor may be configured to monitor at least one of the rotational speed of the generator 42 and the generator torque. The shaft sensor 51 and / or the generator sensor 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).

[0055] The gearbox 46, the generator 42 and the transformer 90 may be supported by the main support structural frame of the nacelle 16, which may optionally be implemented as a main frame 52. The gearbox 46 may include a gearbox housing connected to the main frame 52 by one or more torque arms 103. In the example, the nacelle 16 also includes a main front support bearing 60 and a main rear support bearing 62. In addition, the generator 42 may be mounted to the main frame 52 by a decoupling support device 54, in particular to prevent vibrations of the generator 42 from being introduced into the main frame 52 and thereby causing a source of noise emission.

[0056] Optionally, the main frame 52 is configured to carry the weight of the components of the rotor 18 and the nacelle 16 and the entire load caused by wind and rotational loads, and in addition, introduce these loads into the tower 15 of the wind turbine 10. The rotor shaft 44, the generator 42, the gearbox 46, the high-speed shaft 48, the coupling 50, and any associated fastening, support and / or fixing devices (which include but are not limited to the support 52 and the front support bearing 60 and the rear support bearing 62) are sometimes referred to as the drive train 64.

[0057] In some examples, the wind turbine may be a direct drive wind turbine without a gearbox 46. In a direct drive wind turbine, the generator 42 operates at the same rotational speed as the rotor 18. Therefore, they generally have a much larger diameter than the generators used in wind turbines with a gearbox 46 for providing a similar amount of power compared to a wind turbine with a gearbox.

[0058] The nacelle 16 may also include a yaw drive mechanism 56 that may be used to rotate the nacelle 16 , and thereby the rotor 18 , about the yaw axis 38 to control the viewing angle of the rotor blades 22 relative to the wind direction 28 .

[0059] To properly position nacelle 16 relative to wind direction 28, nacelle 16 may also include at least one meteorological measurement system, which may include a wind vane and anemometer. Meteorological measurement system 58 may provide information to wind turbine controller 36, which may include wind direction 28 and / or wind speed.

[0060] In the example, pitch system 32 is arranged at least partially as a pitch assembly 66 in hub 20. 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 corresponding rotor blade 22 (at Figure 1 ), for adjusting the pitch angle of the rotor blades 22 along the pitch axis 34. Figure 2 Only one of three pitch drive systems 68 is shown.

[0061] In the example, pitch assembly 66 includes at least one pitch bearing 72 coupled to hub 20 and to a corresponding rotor blade 22 (at Figure 1 34) for rotating the corresponding 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 so that the pitch drive motor 74 imparts mechanical force to the pitch drive gearbox 76. The pitch drive gearbox 76 is coupled to the pitch drive pinion 78 so 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 so that rotation of the pitch drive pinion 78 causes rotation of the pitch bearing 72.

[0062] Pitch drive system 68 is coupled to wind turbine controller 36 for adjusting the pitch angle of rotor blades 22 upon receiving one or more signals from wind turbine controller 36. In an example, pitch drive motor 74 is any suitable motor driven by electrical power and / or a hydraulic system that enables pitch assembly 66 to function as described herein. Alternatively, pitch assembly 66 may include any suitable structure, configuration, arrangement, and / or components, such as, but not limited to, a hydraulic cylinder, a spring, and / or a servo mechanism. In certain embodiments, pitch drive motor 74 is driven by energy extracted from the rotational inertia of hub 20 and / or a stored energy source (not shown) that supplies energy to components of wind turbine 10.

[0063] The pitch assembly 66 may also include one or more pitch control systems 80 for controlling the pitch drive system 68 according to control signals from the wind turbine controller 36 in the event of a particular priority situation and / or during an overspeed of the rotor 18. In an example, the pitch assembly 66 includes at least one pitch control system 80 that is communicatively coupled to a corresponding pitch drive system 68 for controlling the pitch drive system 68 independently of the wind turbine controller 36. In an example, the pitch control system 80 is coupled to the pitch drive system 68 and to the sensor 70. During normal operation of the wind turbine 10, the wind turbine controller 36 may control the pitch drive system 68 to adjust the pitch angle of the rotor blades 22.

[0064] According to an embodiment, a power generator 84 (e.g., including a battery and a capacitor) is arranged at or within the hub 20 and is coupled to the sensor 70, the pitch control system 80, and the pitch drive system 68 to provide a power source to these components. In an example, the power generator 84 provides a continuous power source 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 an electrical power loss event of the wind turbine 10. The electrical power loss event may include a power grid loss or drop, a fault in the electrical system of the wind turbine 10, and / or a failure of the wind turbine controller 36. During the electrical power loss event, the power generator 84 operates to provide electrical power to the pitch assembly 66 so that the pitch assembly 66 can operate during the electrical power loss event.

[0065] In the example, pitch drive system 68, sensor 70, pitch control system 80, cables, and power source 84 are each positioned in a cavity 86 defined by an inner surface 88 of hub 20. In alternative embodiments, the components are positioned relative to an outer surface of hub 20 and may be directly or indirectly coupled to the outer surface.

[0066] As used herein, the term "processor" is not limited to the integrated circuits known in the art as computers, but broadly refers to controllers, microcontrollers, microcomputers, programmable logic controllers (PLCs), application specific integrated circuits, and other programmable circuits, and these terms are used interchangeably herein.

[0067] In one aspect of the present disclosure, a method 100 is provided for estimating an actual value of an operating parameter of a wind turbine 10. The method 100 includes: Figure 3 The method includes receiving data related to operating parameters from a plurality of sensors of the wind turbine 10 at box 110. The method also includes determining which sensors of the plurality of sensors are reliable and which sensors of the plurality of sensors are unreliable at box 120. The method also includes estimating an actual value of the operating parameter based on a mathematical model and based on the data related to the operating parameter received from the reliable sensors at box 130.

[0068] In this way, outputs of wind turbine sensors that are not considered reliable are not taken into account when estimating the actual value of the operating parameter. The accuracy of the actual value of the operating parameter can therefore be improved. The above receiving, determining, and estimating of blocks 110, 120, and 130 may be performed, for example, by a wind turbine controller 36 (e.g., a main wind turbine controller). The mathematical model may include multiple formulas involving different operating parameters (e.g., rotor speed and pitch).

[0069] Figure 4 Schematically shows an example of how an actual value 67 of an operating parameter may be determined from measurements 63 from a plurality of wind turbine sensors 61. Figure 4 , five wind turbine sensors S1-S5 can be seen. These sensors can be arranged in suitable locations on or with the wind turbine 10. For example, a sensor can be arranged in a power converter, another in the generator 42, another in a slip ring between a fixed portion and a rotating portion of the wind turbine rotor 18, and so on. In an example, at least one of the sensors may include or may be an encoder. The encoder may be an absolute encoder or an incremental encoder. It should be clear that in other examples, different sensors in different locations and / or sensors measuring different variables and / or different numbers of sensors may be used.

[0070] The method may also include using data 63 related to operating parameters from two or more sensors of the plurality of sensors 61 to determine which sensors are reliable and which sensors are unreliable. Figure 4In a simplified example, sensors S1-S3 are configured to measure data d1-d3 associated with a first operating parameter A, and sensors S4-S5 are configured to measure data d4-d5 associated with a second operating parameter B different from the first parameter. In other examples, the sensors may measure data associated with more than one operating parameter. For example, the measurement results of one sensor may be used to determine two or more operating parameters.

[0071] The measured data 63 may directly or indirectly indicate an operating parameter. For example, the operating parameter may be the rotational speed, and the sensor may measure the rotational speed. Thus, the sensor's measurement directly indicates the operating parameter. Alternatively, the operating parameter may be the rotational speed, but the sensor may, for example, measure currents in a power converter, from which the rotor speed may be determined. The sensor's measurement thus indirectly indicates the operating parameter.

[0072] In this aspect, the method may further include determining at least one intermediate value 65 of the operating parameter based on measured data 63 related to the operating parameter measured by the at least one sensor, wherein estimating the actual value 67 of the operating parameter includes estimating the actual value 67 based on the at least one intermediate value 63. The intermediate value 65 may directly indicate the operating parameter.

[0073] exist Figure 4 In the example of , data related to an operating parameter are measured 63 and intermediate values ​​are determined 65. If parameter A is, for example, rotational speed, the measured data d1-d3 can be used to determine intermediate operating parameters IP1_A-IP3_A. A suitable mathematical formula can be used depending on the measurements made. The intermediate operating parameters IP1_A-IP3_A can be different values ​​of parameter A (rotational speed in this example).

[0074] In a non-limiting example, d1 may be a sensor for measuring the azimuthal position of the generator rotor, d2 may be a sensor for measuring the azimuthal position of the wind turbine rotor, and d3 may be a sensor for measuring the current in the converter. From these measurements, various intermediate values ​​for the rotor speed may be calculated. These intermediate values ​​may be used to determine which of the sensors are reliable and to estimate the actual value of the rotor speed.

[0075] Figure 5 An example of three rotor speeds obtained from the measurement results of three sensors is shown. Because the sensors measure multiple data during a certain period of time, Figure 5 The rotor speed curve is shown, and the rotor speed is referred to herein as the rotor speed curve obtained from each of the various sensors. These rotor speeds may be intermediate operating parameters 65. If the sensors directly measure the operating parameters, it will not be necessary to calculate or otherwise obtain the corresponding intermediate values, as the values ​​of the measured data will correspond to the values ​​of the intermediate operating parameters.

[0076] If available Figure 5 As can be seen in FIG, one of the rotational speeds obtained based on the measurements from the wind turbine sensors is more variable than the other two, e.g., has greater noise. The noise in the signal makes the sensor less reliable. If the rotational speed with the greatest noise is taken into account when estimating the actual value of the rotational speed, the actual value of the rotational speed may be further away from its true value. If it is known that the rotational speed with the greatest noise has excess noise, not including it in the estimation of the actual value of the rotational speed may help provide a value of the rotational speed that is closer to its true value, i.e., a more accurate and more precise actual value. The wind turbine 10 may therefore operate better, e.g., in some cases, avoiding or at least reducing severe pitch changes or having high pitch change activities. In another example, oscillations and vibrations in the wind turbine may also be reduced.

[0077] Determining that a sensor is unreliable may be performed in several ways within the scope of the present disclosure. For example, determining which sensors are unreliable may include comparing two values ​​that are directly indicative of an operating parameter based on measurements from different sensors, for example, comparing two intermediate values ​​65 of an operating parameter determined based on different sensors, or comparing two values ​​63 of data related to an operating parameter measured by different sensors. Because measurements may fluctuate and a sensor may not measure exactly the same value each time, a series or set of values ​​(measured values ​​63 or determined values ​​65) may be compared to a series or set of values ​​that should theoretically be equal.

[0078] For example, if a certain sensor is known to be more reliable than other sensors, the data provided by the other sensors may be compared with the data provided by the more reliable sensor. If the difference between the two data (e.g., the average difference) is above a threshold value of the difference, the corresponding sensor may be considered unreliable. Other ways of comparing data measured by two or more sensors or data obtained based on two or more sensors (i.e., values ​​of intermediate operating parameters) may be performed. It may also be possible to compare data measured by one sensor with a corresponding value of an intermediate operating parameter obtained based on a measurement result from another sensor.

[0079] Additionally or alternatively to the above, determining which sensors are unreliable may include analyzing the noise in terms of, for example, how noisy a series of measurements 63 of a sensor is, or analyzing the noise in terms of, for example, how noisy a series of intermediate values ​​65 is. Analyzing the noise may, for example, include calculating a standard deviation of a series of values ​​or calculating a root mean square deviation (RMSD) of a series of values.

[0080] A noise threshold may be defined, and if the noise threshold is reached or exceeded, the corresponding sensor may be considered unreliable. The noise threshold may be set at a certain level, depending on, for example, the available sensors or the operating parameters to be determined. In some examples, the noise threshold may be predefined for each sensor. For example, the values ​​of the noise threshold may be stored in a memory of the wind turbine controller 36. Once the wind turbine is started, the wind turbine may access and read these values. The noise threshold for each sensor may be different.

[0081] The peak-to-peak difference in a series of values ​​may also be determined. For example, if the peak-to-peak value determined in a series of values ​​is less than a threshold value, it may be determined that the sensor is providing a frozen signal and therefore the sensor is unreliable.

[0082] Yet another way of determining which sensors are unreliable may include comparing two or more values ​​directly indicative of operating parameters based on measurements from different sensors with actual values ​​of operating parameters estimated in one or more previous steps (optionally previous steps).

[0083] As a non-limiting example, it is known that the rotational speed of a wind turbine rotor cannot be changed very quickly due to the inertia of the wind turbine rotor. As a further example, if the azimuth angle and the rotor speed have been determined in a previous step, then based on these, the expected subsequent azimuth angle may also be determined. A large deviation from the expected azimuth angle received from a particular sensor may indicate reduced reliability.

[0084] As an example related to the rotor speed, the first intermediate parameter 65 obtained from the measurement result of the first sensor in the current step may have a value of 6.2. The first intermediate parameter 65 obtained from the measurement result of the second sensor in the current step may have a value of 6.5. And the first intermediate parameter 65 obtained from the measurement result of the third sensor in the current step may have a value of 5.7. In the previous step, the actual value 67 of the operating parameter was estimated to be 6.4. Therefore, by comparing the values ​​6.2, 6.5 and 5.7 with 6.4, it can be inferred that 5.7 is not a reliable value and the third sensor is therefore unreliable. A threshold value can be defined, above which the corresponding sensor will be considered unreliable.

[0085] Furthermore, if the measured or calculated data indicative of an operating parameter is above a threshold value (e.g., a predefined threshold value), the corresponding sensor may be considered invalid. For example, if it is known that the rotational speed of the rotor cannot be higher than a certain rotational speed and the measured / calculated data indicates that the rotational speed is above such threshold value, the corresponding sensor may be considered invalid.

[0086] exist Figure 4In the example of , the value of the intermediate operating parameter IP2_A is discarded and the sensor S2 is considered unreliable. Regarding parameter B, both sensors S4 and S4 are considered reliable. Data d4 directly indicates parameter B, data d5 indirectly indicates parameter B, and the intermediate operating parameter IP5_B directly indicates parameter B.

[0087] Once there are values ​​of the operating parameters that are considered reliable, these can be used to determine the actual value of the operating parameter. In particular, the actual value of the operating parameter can be estimated by combining data that is directly indicative of the operating parameter based on data received from reliable sensors 67. For example, if three values ​​of rotational speed have been determined (measured and / or calculated from data from different sensors), the three values ​​can be combined to obtain a more accurate value of rotational speed than the value of rotational speed obtained from a single sensor.

[0088] Additionally, the actual value of the operating parameter may be estimated 67 by performing an initial estimate of the actual value of the operating parameter using a mathematical model and by correcting the initial estimate using data directly indicative of the operating 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, a measurement may be taken and used to correct the initial estimate.

[0089] Data indicative of operating parameters based on data received from reliable sensors may be assigned different weights for correction of the initial estimate. The weights assigned may depend at least on the sensor noise measured or expected 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 additionally be used to define individual noise thresholds for each sensor.

[0090] 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 based on the operating parameters of one or more previous steps. If the mathematical model is considered to provide a fairly good or very good initial estimate, the weight assigned to the initial estimate of the actual value may be high.

[0091] 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, a weight of 0.7 may be assigned to the initial estimate, a weight of 0.20 may be assigned to the first intermediate value, and a weight of 0.10 may be assigned to the second intermediate value. The estimate may then be the sum of each of these values ​​multiplied by the corresponding weight.

[0092] If not all sensors are considered reliable, the corresponding measurements and weights (if assigned) are ignored.The actual value of the operating parameter may then be determined as the sum of each of the intermediate values ​​multiplied by the corresponding weight and divided by the sum of the weights.

[0093] As explained previously, if a sensor is deemed unreliable, data obtained from that sensor is not considered, and only data obtained from reliable sensors is used to correct the initial estimate. In some examples, a Kalman filter may be used. Other suitable algorithms may be used in other examples. Figure 4 Reference numeral 69 in may represent an estimation algorithm, such as a Kalman filter.

[0094] In some examples, the mathematical model may include three states, specifically position, velocity, and acceleration. In other words, the mathematical model may predict at a certain time or step (t1) the value of the position (e.g., azimuth), the value of the velocity (e.g., rotor velocity), and the value of the acceleration (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 the measurement results of multiple sensors. For example, the values ​​of position and velocity may be measured or obtained from the measurement results, and the acceleration may be calculated. These values ​​may be combined with the values ​​of position, velocity, and acceleration predicted in the previous step (t1) to obtain actual values ​​for position, velocity, and acceleration for the current step (t2).

[0095] Since speed data may be obtained from data related to position, but position data may not be obtained from data related only to speed, at least one sensor configured to measure data indicative of position and at least one sensor configured to measure data indicative of speed may be provided. In particular, at least two sensors configured to measure data indicative of position and at least two sensors configured to measure data indicative of speed may be provided. Thus, if, for example, one of the sensors configured to measure data indicative of speed is deemed unreliable, data from another sensor configured to measure data indicative of speed and / or data from at least one of the sensors configured to measure data indicative of position may still be used.

[0096] In general, the actions at blocks 110 and 120 of method 100 may be performed repeatedly. For example, once an initial estimate is corrected, a new initial estimate for a later time may be performed, and additional measurements may be performed to correct 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 value is.

[0097] The actual value of the rotor speed can be found in the Figure 5 In this example, measurements from three wind turbine sensors are used to correct the initial estimate of the rotor speed. Figure 5 In and also from Figure 6 As can be seen in , the data obtained by the sensor with the largest noise can be discarded to obtain a more accurate actual value of the rotor speed. Figure 6 Schematically shows Figure 5 The actual value of the rotor speed is plotted against the Figure 5 The differences between the curves of the values ​​of rotor speed determined by three different wind turbine sensors. Figure 6 One of the curves has more noise than the other two.

[0098] If one or more sensors are considered unreliable, the method may further include stopping measuring data using one or more of the unreliable sensors. If one or more sensors are caused to stop measuring data, the method may further include starting measuring data using one or more of the stopped unreliable sensors. After a certain period of time, it may be checked whether the sensor operates better than before. If this is the case, its output may be taken into account when determining the actual value of the operating parameter. If the sensor is still considered unreliable, it may not be used in the estimation of the actual value.

[0099] like Figure 4 As shown in the example of , there may be more than one wind turbine sensor for measuring data related to the operating parameter. Because method 100 excludes data obtained from sensors that are considered unreliable, in some examples, the method may be applied if there is more than one sensor configured to provide data related to the corresponding operating parameter whose actual value is to be estimated.

[0100] In some examples, the operating parameter may be a set point for controlling the wind turbine. For example, one or more certain set point values ​​may be determined using method 100. In other examples, the actual value of the operating parameter may be used later to calculate the set point. For example, obtaining a reliable value for the speed of rotor 18 may be particularly complex. If the actual value of the operating parameter is a rotor speed value, this value may be used as a set point and / or may be used in determining other set points (e.g., pitch angle or torque).

[0101] In some examples, the operating parameter may be an azimuth angle. Having an accurate value for the azimuth angle may, for example, assist in performing appropriate and efficient control of the pitch angles of each wind turbine blade 22. Of course, in other examples, the operating parameter may be different.

[0102] And if Figure 4 As schematically shown in , the method 100 can be used to calculate actual values ​​of more than one operating parameter. For example, the method 100 can be used to estimate actual values ​​of rotor speed and azimuth angle.

[0103] According to a further aspect of the present disclosure, a wind turbine controller 36 is provided. The wind turbine controller includes a processor and a memory. The memory includes instructions that, when executed by the processor, cause the processor to receive data related to operating parameters 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 67 of the operating parameter based on a mathematical model and based on the data related to the operating parameter received from the reliable sensors.

[0104] 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 the various steps disclosed herein (e.g., with respect to method 100) as appropriate. The memory may also be configured to store data, such as predefined data or data from measurements and / or calculations.

[0105] The wind turbine controller 36 may also 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 be used as an interface to enable the turbine controller 36 to transmit 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 performed via a wired connection and / or via a wireless connection, such as by using any suitable wireless communication protocol known in the art. In addition, the communication module may include a sensor interface, such as one or more analog-to-digital converters, so that signals transmitted from one or more sensors (e.g., a wind speed sensor) can be converted into signals that can be understood and processed by a processor.

[0106] According to a further aspect of the present disclosure, there is provided a wind turbine 10. The wind turbine comprises a tower 15, a nacelle 16 on top of the tower 12, a rotor 18 connected to the nacelle 16, the rotor comprising a hub 20 and a plurality of blades 22 connected to the hub, and a wind turbine controller 36 of the previous aspect.

[0107] In some examples, the wind turbine may be 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 may be particularly beneficial for offshore wind turbines. However, the above method may of course be performed by an onshore wind turbine.

[0108] According to a further aspect of the present disclosure, a method 200 for estimating a value of an operating parameter of a wind turbine is provided. The method 200 Figure 7The details and explanations of the previous aspects can be combined and applied to this aspect, and vice versa.

[0109] The method 200 includes, at box 210, measuring data 63 related to operating parameters using a plurality of wind turbine sensors 61; at box 220, determining which sensors are faulty or have excess noise; at box 230, performing an initial estimate of an actual value of the operating parameter using a mathematical model; and at box 240, correcting the initial estimate using data directly indicative of the operating parameter based on measurements 63 by reliable sensors.

[0110] At least two or more sensors may allow for determining data directly indicative of an operating parameter. That is, there may be at least one redundant sensor.

[0111] Determining which sensors are faulty or have excessive noise may include reaching or exceeding a noise threshold. In some examples, the noise threshold may be predefined and stored in a memory of wind turbine controller 36.

[0112] The operating parameter may be a rotational speed. In other examples, the operating parameter may be an azimuth angle. The values ​​of other operating parameters may also be determined using method 200.

[0113] A Kalman filter may be used to perform the following steps: performing an initial estimate and correcting the initial estimate. Other suitable algorithms may alternatively be used.

[0114] This written description uses examples to disclose teachings, including preferred embodiments, and also enables any person skilled in the art to put the teachings into practice, including making and using any device or system and performing any combined method. The scope of the patent application is defined by the claims and may include other examples that occur to a person skilled in the art. If such other examples have structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are not substantially different from the literal language of the claims, such other examples are intended to be within the scope of the claims. Aspects from the various embodiments described and other known equivalents for each such aspect may be mixed and matched by a person of ordinary skill in the art to construct additional embodiments and techniques according to the principles of the application. If reference symbols associated with the figures are placed in brackets in the claims, they are only intended to increase the understandability of the claims and should not be interpreted as limiting the scope of the claims.

Claims

1. A method (100) for estimating an actual value (67) of an operating parameter of a wind turbine (10), the method (100) comprising: receiving (110) data (63) related to the operating parameter 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; as well as An actual value (67) of the operating parameter is estimated (130) based on a mathematical model and based on the data (63) related to the operating parameter received from a reliable sensor.

2. The method according to claim 1, wherein: Determining (110) which sensors are unreliable includes analyzing noise in a series of measurements of the sensor (61), or analyzing noise in a series of intermediate values ​​(65).

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

4. The method according to any one of claims 1-3, further comprising using data (63) related to the operating parameters from two or more sensors of the plurality of sensors (61) to determine (120) which sensors are reliable and which sensors are unreliable.

5. The method according to any one of claims 1 to 4, further comprising determining at least one intermediate value (65) of the operating parameter based on measured data (63) related to the operating parameter measured by at least one sensor, and wherein Estimating (120) the actual value (67) of the operating parameter includes estimating the actual value (67) based on the at least one intermediate value (65).

6. The method according to any one of claims 1 to 5, wherein: Estimating (130) the actual value (67) of the operating parameter includes combining data directly indicative of the operating parameter with data received from the reliable sensor.

7. The method according to claim 6, wherein: Estimating (130) the actual value (67) of the operating parameter includes performing an initial estimate of the actual value of the operating parameter using the mathematical model and correcting the initial estimate using the data directly indicative of the operating parameter based on data received from the reliable sensor.

8. The method according to claim 7, comprising using a Kalman filter for performing the initial estimation and for correcting the initial estimation.

9. The method of any one of claims 1-8, further comprising ceasing to measure data using one or more of the unreliable sensors.

10. The method according to any one of claims 1 to 9, wherein: The operating parameters are set points for controlling the wind turbine.

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