GB2598376A

GB2598376A - Alignment of wind turbine

Info

Publication number: GB2598376A
Application number: GB2013578.6A
Authority: GB
Inventors: Hardisty Jack
Original assignee: Vortex Wind Tech Ltd
Current assignee: Vortex Wind Tech Ltd
Priority date: 2020-08-28
Filing date: 2020-08-28
Publication date: 2022-03-02
Also published as: GB202013578D0

Abstract

A method is provided for determining an angle of misalignment between an operational direction of a wind turbine and a wind direction. The method comprises: obtaining wind measurements 801, wherein the wind measurements are taken behind turbine blades of the turbine downstream of the wind, processing at least some of the wind measurements to reduce or remove a component of the wind measurements in the frequency domain located at a certain frequency 802, 803, 804, determining the wind direction based at least partially on the processed wind measurements 805, and determining the angle of misalignment based on a difference between the determined wind direction and the operational direction of the wind turbine 806. The sensor measurements may be wind velocity measure in the time domain and the analysis may manipulating those readings using Fourier Transformation, which may include FFT, DFT, IDFT.

Description

ALIGNMENT OF WIND TURBINE

Field

Certain examples of the present disclosure provide a technique for aligning a wind turbine with the direction of wind. Certain examples of the present disclosure provides a technique for correcting misalignment of a wind turbine relative to the direction of wind by adjusting the yaw of the turbine.

Backqround The use of wind turbines to generate electricity has increased rapidly over recent years. For example, new wind turbines with a total capacity of about 54 GWwere installed in 2018. The current total global installation capacity is more than 600 GW generated from more than 250,000 turbines. The efficiency of a wind turbine (and thus the revenue generated) depends upon the wind speed and is very sensitive to the turbine yaw and alignment to the true wind. Figure 1 is a graph illustrating the relationship between peak power output against degree of misalignment for a 3.5 MW turbine. It can be seen from Figure 1 that a 100 misalignment reduces the peak power output of a 3.5 MW turbine to 3.35 MW with a corresponding reduction in revenue.

Therefore, what is desired is a technique to identify any misalignment in a wind turbine, and to correct any misalignment, to thereby improve the power generation efficiency of the turbine.

The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.

Summary

It is an aim of certain examples of the present disclosure to address, solve, mitigate or obviate, at least partly, at least one of the problems and/or disadvantages associated with the related art, for example at least one of the problems and/or disadvantages mentioned herein. Certain examples of the present disclosure aim to provide at least one advantage over the related art, for example at least one of the advantages mentioned herein.

The present invention is defined in the independent claims. Advantageous features are defined in the dependent claims.

Embodiments or examples disclosed in the description and/or figures falling outside the scope of the claims are to be understood as examples useful for understanding the present invention.

Various aspects, advantages, and salient features of the present disclosure will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the accompanying drawings, disclose examples of the present disclosure.

Brief Description of the Figures

Figure 1 is a graph illustrating the relationship between peak power output against degree of misalignment for a 3.5 MW turbine; Figures 2a and 2b illustrate a rotating cup and vane anemometer and a typical mounting location on a turbine; Figure 3 illustrates an exemplary turbulent structure in the downstream wind flow behind turbine blades generated by the rotation of the blades (modified from www.ivanell.se); Figure 4a illustrates a typical theoretical power curve of a wind turbine and Figure 4b illustrates a power curve including scatter; Figure 5 illustrates the structure of a typical wind turbine; Figure 6 illustrates an apparatus according to an example of the present disclosure; Figures 7a and 7b illustrate the geometric relationship between the measured (apparent) wind, the true wind and the cross wind in the cases that the true wind is (i) aligned, and (ii) not aligned, respectively, with the turbine axis Figure 8 is a flow chart of a method according to an example of the present disclosure; and Figure 9 illustrates an exemplary spectrum obtained from the Fourier transform of cross wind measurements.

Description

The following description of examples of the present disclosure, with reference to the accompanying drawings, is provided to assist in a comprehensive understanding of the present invention, as defined by the claims. The description includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made.

The terms and words used in this specification are not limited to the bibliographical meanings, but are merely used to enable a clear and consistent understanding of the present disclosure.

The same or similar components may be designated by the same or similar reference numerals, although they may be illustrated in different drawings.

Detailed descriptions of elements, features, components, structures, constructions, functions, operations, processes, characteristics, properties, integers and steps known in the art may be omitted for clarity and conciseness, and to avoid obscuring the subject matter of the present disclosure.

Throughout this specification, the words "comprises", "includes", "contains" and "has", and variations of these words, for example "comprise" and "comprising", means "including but not limited to", and is not intended to (and does not) exclude other elements, features, components, structures, constructions, functions, operations, processes, characteristics, properties, integers, steps and/or groups thereof.

Throughout this specification, the singular forms "a", "an" and "the" include plural referents unless the context dictates otherwise. For example, reference to "an object" includes reference to one or more of such objects.

By the term "substantially" it is meant that the recited characteristic, parameter or value need not be achieved exactly, but that deviations or variations, including for example, tolerances, measurement errors, measurement accuracy limitations and other factors known to those of skill in the art, may occur in amounts that do not preclude the effect the characteristic, parameter or value was intended to provide.

Throughout this specification, language in the general form of "X for Y" (where Y is some action, process, function, activity, operation or step and X is some means for carrying out that action, process, function, activity, operation or step) encompasses means X adapted, configured or arranged specifically, but not exclusively, to do Y. Elements, features, components, structures, constructions, functions, operations, processes, characteristics, properties, integers, steps and/or groups thereof described herein in conjunction with a particular aspect, embodiment, example or claim are to be understood to be applicable to any other aspect, embodiment, example or claim disclosed herein unless incompatible therewith. It will be appreciated that examples of the present disclosure can be realized in the form of hardware, software or any combination of hardware and software. Any such software may be stored in any suitable form of volatile or non-volatile storage device or medium, for example a ROM, RAM, memory chip, integrated circuit, or an optically or magnetically readable medium (e.g. CD, DVD, magnetic disk or magnetic tape).

Certain examples of the present disclosure may provide a computer program comprising instructions or code which, when executed, implement a method, system and/or apparatus in accordance with any aspect, claim, example and/or embodiment disclosed herein. Certain examples of the present disclosure provide a machine-readable storage storing such a program. The techniques described herein may be implemented using any suitably configured apparatus and/or system. Such an apparatus and/or system may be configured to perform a method according to any aspect, embodiment, example or claim disclosed herein. Such an apparatus may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and/or method steps for implementing the techniques described herein. For example, an operation/function of X may be performed by a module configured to perform X (or an X-module). The one or more elements may be implemented in the form of hardware, software, or any combination of hardware and software.

A conventional wind turbine typically uses a rotating cup and vane anemometer mounted behind the turbine blades to measure wind speed and direction. Figures 2a and 2b illustrate a rotating cup and vane anemometer 201 and a typical mounting location 203 on a turbine 205. These measurements are used to identify, and if necessary correct, any misalignment between the turbine and the wind direction. However, for the reasons discussed below, this arrangement can result in inaccurate measurements of both the wind speed and direction. This in turn results in misalignment of the turbine, a reduction of efficiency, and loss of revenue.

The rotation of the turbine blades generates turbulent structures in the downstream wind flow behind the blades, including tip and hub vortices. An exemplary turbulent structure is illustrated in Figure 3 (modified from www.ivanell.se). The tip vortices are well-structured close to the blades but start to interact and break down into turbulence further downwind. The hub vortices quickly become a sheet of vorticity spread over the cylindrical nacelle of the turbine.

The turbulent structures mentioned above cause a turbulent cross wind behind the blades, including at the location at which a wind measuring sensor (e.g. a rotating cup and vane anemometer) is typically mounted. However, a conventional rotating cup and vane anemometer cannot detect such a cross wind. In particular, this type of anemometer measures the apparent wind rather than the true wind. The apparent wind is the vector sum of the true wind and cross wind (see Figures 7a and 7b) and typically has a larger magnitude than, and different direction to, the true wind. This may lead to an over-estimation of the true wind speed as well as inaccuracy in the measurement of the true wind direction. As a result, even after the alignment of the turbine has been corrected based on the measurements, the turbine may still be misaligned, resulting in a significant reduction of efficiency and loss of revenue.

Furthermore, the turbulent cross wind discussed above can result in problems associated with the turbine's power curve. A power curve defines the transfer function between the mean wind speed and the mean turbine power output. Figure 4a illustrates a typical theoretical power curve of a wind turbine. A wind turbine power curve is typically obtained by the turbine manufacturer by performing measurements under certain standardised conditions. Once the turbine is deployed, the operator can use the power curve to estimate or forecast power generation, based on the assumption of the conditions under which the power curve was obtained. However, the turbulent cross wind discussed above can result in scatter in the actual power curve applicable during use, as illustrated in Figure 4b. This can lead to inaccuracies in the estimation and/or forecasting of power generation.

Accordingly, certain examples of the present disclosure provide a technique to identify and correct any misalignment in a wind turbine, to thereby improve the power generation efficiency of the turbine. In particular, certain examples of the present disclosure provide a technique for aligning a wind turbine with the direction of the wind. Certain examples of the present disclosure provides a technique for correcting misalignment of a wind turbine relative to the direction of wind by adjusting the yaw of the turbine.

A typical wind turbine 501, as illustrated in Figure 5, comprises a vertical tower 501 supported at its lower end by a foundation 503, a nacelle 505 provided at the upper end of the tower 501, a rotatable shaft 507 housed within the nacelle 505 and having an axis located substantially in the horizontal plane, a number of blades 509 attached to the front end of the shaft 507 and extending perpendicularly from the shaft 507, an electrical generator 511 coupled to the rear end of the shaft 507, and a pivoting system 513 for adjusting the direction of the turbine (i.e. the direction of the nacelle 505, shaft 507 and blades 509). In particular, the pivoting system 513 is configured for adjusting the yaw of the turbine. Some turbines may be configured for adjusting the turbine in other directions as well, for example the pitch of the turbine. In certain examples, a "direction of the turbine" may be regarded as the direction of the rotation axis of the turbine blades 509 (i.e. the direction of the shaft 507). This may be referred to as the "operational direction of the turbine" or similar. Accordingly, the pivoting system 513 is configured to change the operational direction of the turbine.

A typical turbine also comprises other elements such as power cables, power transformer, gear box and brake (not shown).

An apparatus 600 according to an example of the present disclosure is illustrated in Figure 6. The apparatus comprises a wind sensor 601 and a processor 603. The apparatus 1 may be installed at any suitable position on a wind turbine, for example on the nacelle of the turbine behind the blades downstream of the wind flow, for example the mounting location 203 illustrated in Figure 2b.

The wind sensor 601 is configured for measuring the wind flow to enable the wind speed to be determined in two directions: a first direction parallel with the axis of the turbine, and a second direction that is perpendicular to the first direction. The axis of a turbine, and hence the first direction, typically lies substantially in the horizontal plane. In some examples, the second direction may lie in the horizontal plane as well. In certain examples, the wind sensor 601 may comprise a two-dimensional ultrasonic anemometer, which directly measures wind speed in two (typically orthogonal) directions 607. In other examples, the wind sensor 601 may comprise one or more sensors (e.g. wind vane and rotating cup anemometer) that measure the magnitude and direction of the wind, from which the wind speed in the two directions can be derived.

Figure 7a illustrates the geometric relationship between the measured (apparent) wind, the true wind and the cross wind in the case that the true wind is aligned with the turbine axis. Figure 7b illustrates the geometric relationship between the measured (apparent) wind, the true wind and the cross wind in the case that the true wind is not aligned with the turbine axis. For example, Figures 7a and 7b relate to a cross-section S-S indicated in Figure 5 when viewed from above the turbine in the case that the turbine blades are rotating clockwise when viewed from the front of the blades (i.e. in direction D indicated in Figures 5, 7a and 7b).

In Figure 7b, the turbine axis is indicated with a vertical dotted line (corresponding to an x-direction or the first direction), and the plane of the turbine blades is indicated with a horizontal dotted line (corresponding to an y-direction or the second direction). The incoming true wind is indicated with a dotted arrow, and is illustrated as having a direction that is misaligned by an angle a relative to the turbine axis. The measured wind speed in the first direction (x-direction) is denoted U and the measured wind speed in the second direction (y-direction) is denoted V. The magnitude of the true wind is denoted T, the component of the true wind in the first direction is denoted Tx and the component of the true wind in the second direction is denoted T. The magnitude of the cross wind is denoted C. In this example, the cross wind is assumed to lie in the second direction only with no component in the first direction. The magnitude of the apparent wind is denoted A and the direction of the apparent wind relative to the turbine axis is denoted p. As illustrated in Figure 7b, the measured wind in the first direction, U, is equal to the component of the true wind in the first direction, T. However, the measured wind in the second direction, V, is not equal to the component of the true wind in the second direction, Ty, but rather is equal to the sum of Ty and the cross wind, C. It can be seen that, as a result of the presence of the cross wind, C, as a component in the measured wind in the second direction, V, the magnitude of the apparent wind, A, is not equal to the magnitude of the true wind, T, and the direction of the apparent wind relative to the turbine axis, p, is different from the direction of the true wind relative to the turbine axis, a. In particular, in this example, the magnitude of the apparent wind, A, overestimates the magnitude of the true wind, T, and the apparent wind direction overestimates the degree of misalignment, f3, relative to the turbine axis.

A conventional wind vane and rotating cup anemometer would measure the direction, p, and magnitude, A, of the apparent wind. However, what is needed for proper and accurate correction of the misalignment of the turbine relative to the true wind are measurements of the direction, a, and magnitude, T, of the true wind.

In the scenario illustrated in Figure 7b it is difficult to remove the cross wind component, C, from the wind measurement in the second direction, V, in the spatial domain since the cross wind component is unknown and cannot easily be independently measured in the spatial domain. This means that it is difficult to derive T and a from U and V, or alternatively from A and p, in the spatial domain.

Certain examples of the present disclosure provide a technique in which the cross wind, C, can be removed from the wind measurement in the second direction, V, thereby allowing proper and accurate correction of the misalignment of the turbine relative to the true wind. In particular, since the cross wind, C, is caused by rotation of the turbine blades, the cross wind exhibits a periodic characteristic. Accordingly, in certain examples of the present disclosure, the cross wind can be removed, or at least reduced, in the frequency domain. Once the cross wind component has been removed or reduced, the true wind magnitude and direction can be determined more accurately from the adjusted wind measurements.

The wind sensor 601 is configured to sample the wind speed in the first and second directions at any suitable sampling rate to obtain wind speed samples 1.1; and V. In certain examples, the wind measurements may be sampled at a rate that is twice the Nyquist Frequency of the turbulent events occurring at the turbine. Certain turbulent events are caused by the rotation of the turbine blades, as discussed above, and so the frequency of such turbulent events is dependent on the rotation speed of the turbine blades as well as the number of turbine blades. For example, if such turbulent events occur at a frequency of 1 Hz then the sampling frequency may be set as 4 Hz. In certain examples, the sampling frequency may be adjustable. The samples of wind speed measurements Ui and Vi are provided to the processor 603 via any suitable connection or interface.

The processor 603 is configured to process the wind measurements obtained by the wind sensor 601 to calculate a misalignment value. The misalignment value indicates any degree of misalignment between the wind turbine and the true wind direction. For example, the misalignment value may be a value representing the yaw angle between the wind turbine direction and the true wind direction (i.e. the angle a in Figure 7b). Certain exemplary techniques for obtaining the misalignment value described further below.

The processor 603 may provide the misalignment value to an apparatus for adjusting the direction of alignment of the turbine, for example a pivoting system 513 (Figure 5) of the turbine for adjusting the turbine yaw. Upon receiving the misalignment value, the pivoting system 513 may automatically adjust the turbine direction (e.g. yaw) to correct the misalignment.

Alternatively, the misalignment value may be output by the processor 603 and transmitted to a remote device (e.g. a server) using a transceiver 605. Upon receiving the misalignment value, a decision whether to adjust the direction of the turbine may be made (e.g. automatically or at least partially by a person) based on the received misalignment value and possibly also based on other data (e.g. weather data). If it is decided to adjust the turbine direction then a suitable control signal may be transmitted to the turbine, which receives the signal using the transceiver 605.

In certain examples, the processor may be configured to output the misalignment value in a form that is consistent with the output of conventional equipment. For example, the misalignment value may be output in the format of a signal that is output by a conventional rotating cup and vane anemometer, where the determined misalignment is factored into the output signal such that any yaw adjustment of the turbine based on the output signal properly aligns the turbine with the true wind. This avoids the need for modifications to a turbine pivoting system that is configured to receive an output from conventional equipment, when the conventional equipment is replaced with equipment according to examples of the present disclosure.

An example of operations performed by the processor 603 to determine the misalignment value will now be described with reference to Figure 8, which is a flow chart of a method according to an example of the present disclosure.

In a first operation 801, the processor 603 receives samples of the wind speed in the first direction (parallel with the axis of the turbine) and the second direction (perpendicular to the first direction) at any suitable sampling rate (e.g. 4Hz) to obtain time series U1 and Vi. As mentioned above, the measured wind speed in the first direction, U, corresponds to the component of the true wind aligned with the axis of the turbine (first direction), while the measured wind speed in the second direction, V, corresponds to the sum of (i) the component of the true wind perpendicular to the axis of the turbine, and (ii) the cross wind resulting from rotation of the blades. If the rate of change (speed and direction) of the true wind is relatively small in comparison to the sampling window (i.e. the true wind is approximately constant over the sampling window), then the U measurement will be approximately constant. On the other hand, since the cross wind (caused by the rotating blades) has a varying (i.e. periodic) characteristic, then the V measurement (which includes the cross wind as well as a true wind component) will also have a periodic characteristic over the sampling window.

In a second operation 802, the Discrete Fourier Transform (DFT) of the time series, Vi, is computed, for example according to the following equation: The DFT may be computed based on any suitable number, N1, of samples. For example, Ni may be selected so as to span a time period (time window) corresponding to approximately 10 revolutions of a turbine blade. For example, if the rotational period of a blade is 4 seconds and the sample rate is 4 Hz then Ni may be set to a value of 160.

The resulting spectrum includes a first peak (typically a relatively sharp peak) at substantially zero frequency due to the (approximately constant) true wind component, and one or more peaks at one or more non-zero frequencies. For example, a spectrum typically includes a second peak (typically a relatively sharp peak) corresponding to the angular frequency of the blades due to the cross wind component. In certain examples, the spectrum may include one or more additional peaks; for example corresponding to one or more harmonics (or "overtones"). For example, if the second peak corresponds to a fundamental frequency, then the one or more harmonics may correspond to frequencies that are one or more integer multiples of the fundamental frequency.

Figure 9 illustrates an exemplary spectrum obtained from the Fourier transform of cross wind measurements. The spectrum of Figure 9 includes a first peak at substantially zero frequency, a second peak at a fundamental frequency corresponding to the angular frequency of the blades, and a third peak corresponding to a first harmonic frequency that is twice the fundamental frequency In a third operation 803; the spectrum obtained in the second operation 802 is filtered using any suitable filter (e.g. low-pass filter or band-reject filter) to remove the peaks at non-zero frequencies to remove the component corresponding to the cross wind. The peaks at the non-zero frequencies may include a peak at a fundamental frequency and/or one or more peaks at one or more harmonic (or overtone) frequencies.

If the frequency of the turbulent events caused by rotation of the turbine blades occurs at a frequency f (or in frequency band with centre frequency of]) then the filter may be configured to remove or reduce at least the frequency component at frequency f (or the frequency band with centre frequency of 1). For example, the filter may comprise a low-pass filter or a band-reject filter having a stop-band that includes the frequency / (or the frequency band with centre frequency I).

If turbulent events cause peaks at two or more frequencies, for example including a fundamental frequency to and one or more harmonic (overtone) frequencies /1, then all such peaks may be filtered using one or more lifters. A certain filter may be used to filter a single peak only, or may be used to filter two or more (or ail) peaks together.

The frequency f (or frequencies Jo, 11, /2, ...) may be determined by prior measurements andior theoretically. For example, if each turbine blade takes a time to perform a single revolution then the rotational frequency is equal to 111. If there are N turbine blades (e.g. 3) then the frequency f (or frequency Jo) of the turbulent events may be estimated as NIT. The frequencies 1.1,12, ... may be estimated as multiples of Jo. Alternatively, or in addition, prior measurements may be made to identify the frequency f (or frequencies Jo, /1, 12, ...) experimentally.

In a fourth operation 804, the Inverse Discrete Fourier Transform (IE)FT) of the filtered spectrum obtained in the third operation 803 is computed, for example according to the following equation: The result of the fourth operation 804 is a time series, Vi*, with the cross wind component removed, or at least reduced.

In subsequent operations, a misalignment value (e.g. misalignment angle a) may be computed based on the filtered time series VI and the time series U. For example, in a fifth operation 805, a mean values and <V> (or any other suitable statistical values) may be calculated based on the filtered time series V,* and the time series U,, respectively. The mean (or other suitable statistical values) values may be calculated in any suitable manner For example, the mean may be the arithmetic mean of N2 consecutive samples, where N2 may be any suitable number. For example, N2 may be selected so as to span a time period corresponding to approximately 10 revolutions of a turbine blade. For example, if the rotational period of a blade is 4 seconds and the sample rate is 4 Hz then N2 may be set to a value of 160.

The mean value provides an estimate of the component of the true wind aligned with the turbine axis (i.e. in the first direction), T. In view of the removal of the cross wind as described above, the mean value <V> provides an estimate of the component of the true wind perpendicular to the turbine axis (i.e. in the second direction), T. In a sixth operation 806, the misalignment angle, a, may be calculated using trigonometry based on the mean values and <V>. For example, the misalignment angle, a, may be calculated based on the following equation: < V > a = catai In the fifth operation 805 and the sixth operation 806 described above, the mean values and <V> are calculated and then the misalignment angle, a, is calculated based on the mean values.

In an alternative example, a misalignment angle sample, ai, may be calculated using trigonometry based on individual time series values U, and V,*, for example based on the following equation: Vt* ai= COtart = j Then, a mean value <a> may be calculated based on the samples, oft in a similar manner to the calculation of and <V> described above. The mean value <a> may then be used as the misalignment angle a.

The misalignment angle, a, computed as described above may be used as the misalignment value for adjusting the direction (i.e. yaw) of the turbine.

Some or all of the values measured and/or calculated in the various operations described above (e.g. Ui, Vi, , <V>, a, eft <a>) may be transmitted to a remote server or other entity, using the transceiver 605 (Figure 6), for logging and/or for performing further analysis.

The technique described above removes scatter from the power curve allowing improved offline power output forecasting, and, by comparison with stored results, allow both directional power curves and calibration coefficients to be determined.

In certain examples, the processor 603 may be provided within the same apparatus 600 as the wind sensor 601. That is, the wind sensor 601 and the processor 603 may be combined within a single hardware unit or module deployed on the turbine. Alternatively, the wind sensor 601 and the processor 603 may be provided as separate units or modules, with both units or modules being deployed on the turbine. Alternatively, the processor 603 may be a unit or module that is located remotely from the wind sensor 601 and wind turbine. For example, the wind measurements made by the wind sensor 601 may be transmitted, using the transceiver 605, to a remote device (e.g. a server) including the processor 603 to perform the necessary calculations. The resulting misalignment value may be transmitted back to the turbine for correcting any misalignment. In this case, the turbine may receive the misalignment value using the transceiver 605.

In the examples described above, it was assumed that the cross wind was confined to the second direction, with no component in the first direction aligned with the turbine axis. However, in the case that a component of the cross wind does appear in the measurements, U, in the first direction then the time series U; may be filtered in the frequency domain to obtain a filtered time series Ui* in the same manner as described above in relation to measurements, V, in the second direction. This process removes or reduces the cross wind component in the measurements, U, in the first direction. Subsequent operations for calculating the misalignment angle, a, may be based on the filtered time series Ui* rather than the original time series U. In the examples described above, it was assumed that the wind sensor 601 measures the wind speed in a first direction parallel with the axis of the turbine and a second direction that is perpendicular to the first direction. However, in other examples, the wind sensor 601 may measure the wind speed in any two suitable non-parallel directions. These directions do not necessarily need to be orthogonal and do not necessarily need to include a direction aligned to the turbine axis or a direction perpendicular to the turbine axis.

In general, the true wind may be denoted by vector T, the cross wind may be denoted by vector C and the apparent (measured) wind may be denoted by vector A, where A=T+C. Measurements of the apparent wind may be processed (e.g. by a filter function CD) to remove or reduce the cross wind component C. Ideally, the processing of the apparent wind A should result in the true wind T: (1)(A)=(1)(1+C)=T.

The apparent wind A may be filtered by filtering one or more components thereof For example, the wind sensor 601 may measure wind in two non-parallel directions, denoted by unit basis vectors ei and ez. That is, the wind sensor 601 measures components of the apparent wind with respect to the basis vectors, given by the dot products Ai=A. ei and A2=A-ez. One or both of the values Ai and A2 may be filtered in the frequency domain to remove or reduce any cross wind component(s), in the manner described above. The resulting values represent estimates of components of the true wind with respect to the basis vectors given by the dot products Ti=T.Qi and -12=-1-ez.

The true wind vector T may be a three-dimensional vector In some examples, three components of T in three dimensions may be measured, and the misalignment value may be determined based on measurements in three dimensions (with filtering applied to one or more of the three components). However, in other examples it is not necessary to measure three components of T in three dimensions. For example, in certain examples, two components of T lying in a plane having a normal that is orthogonal to the rotational axis of the turbine blades may be measured.

In certain examples, it is not necessary to filter some measured components of T. For example, in certain examples, components of T (e.g. components in a direction parallel to the rotational axis of the turbine blades) that are unlikely to include significant contributions from the cross wind C may not be filtered.

The direction of the turbine axis may be denoted by (unit) vector D, and components of the turbine axis direction with respect to the basis vectors are given by the dot products Di=a ei and D2=D-ez. Since the orientation of the measurement directions of the wind sensor 601 relative to the turbine axis is known, then the values Di and 02 are also known.

The angle of misalignment, a, between the true wind T and the turbine axis direction D is given by the angle between the vectors land D, which can be computed using vector analysis from the known values of Di and Dz, and the obtained estimated values of Ti and Tz.

Each estimated component of T may be obtained based on a corresponding component of A, either after filtering (for example if that component includes, or is likely to include, a component of C), or without filtering (for example if that component does not include, or is not likely to include, any component of C, or any significant contribution from g As exemplified further above, the misalignment angle, a, may be calculated based on one or statistical values (e.g. mean values) computed from time series of estimates of components of the true wind T. The statistical value(s) may be computed either before or after the application of a trigonometric equation to compute an angle. For example, conceptually the misalignment angle, a, may be computed according to: a=Trig(Stat([t])) or a=Stat(ai=Trigrit where "Trig" denotes a trigonometric function (e.g. the cotan function) to compute a misalignment angle, "Stat" denotes a statistical function to compute a statistical value (e.g. a mean value), [T*] denotes time series of estimates of one or more components of the true wind T, and ai denotes a misalignment angle time series.

Certain examples of the present disclosure provide a method for determining an angle of misalignment between an operational direction of a wind turbine and a wind direction, the method comprising: obtaining wind measurements, wherein the wind measurements are taken behind turbine blades of the turbine downstream of the wind; processing at least some of the wind measurements to reduce or remove a component of the wind measurements in the frequency domain located at a certain frequency; determining the wind direction based at least partially on the processed wind measurements; and determining the angle of misalignment based on a difference between the determined wind direction and the operational direction of the wind turbine.

In certain examples, obtaining the wind measurements may comprise sampling, in the time domain, at least two spatial components of the wind velocity.

In certain examples, the at least two spatial components may comprise a wind speed in a first direction and a wind speed in a second direction, wherein the first and second directions may be non-parallel.

In certain examples, the first and second directions may be located in a plane having a normal that is orthogonal to the operational direction of the wind turbine.

In certain examples, the first direction may be a direction parallel to the operational direction of the wind turbine and the second direction may be a direction perpendicular to the first direction.

In certain examples, the sampling may be done with a sampling rate determined based on a rotational frequency of the turbine blades and a number of turbine blades.

In certain examples, the wind measurements may be taken by one or more sensors located on a nacelle of the wind turbine.

In certain examples, processing at least some of the wind measurements may comprise filtering at least some of the wind measurements in the frequency domain.

In certain examples, the filtering may comprise filtering at least one spatial component of the wind measurements.

In certain examples, the at least one spatial component may comprise a spatial component that is not parallel with the operational direction of the wind turbine.

In certain examples, the filtering may be performed using a low-pass filter and/or a band-reject filter.

In certain examples, the certain frequency may be determined based on a rotational frequency of the turbine blades and a number of turbine blades.

In certain examples, the method may further comprise adjusting the operational direction of the wind turbine based on the determined angle of misalignment.

In certain examples, the wind direction may be determined based on: a first value representing a wind speed in a first direction, the first value based on one or more first wind measurements corresponding to the first direction; and a second value representing a wind speed in a second direction, the second value based on one or more second wind measurements corresponding to the second direction, wherein at least one of the first and second wind measurements have been processed.

Certain examples of the present disclosure provide a system for determining an angle of misalignment between an operational direction of a wind turbine and a wind direction, the system comprising a processor configured for: obtaining wind measurements, wherein the wind measurements are taken behind turbine blades of the turbine downstream of the wind; processing at least some of the wind measurements to reduce or remove a component of the wind measurements in the frequency domain located at a certain frequency; determining the wind direction based at least partially on the processed wind measurements; and determining the angle of misalignment based on a difference between the determined wind direction and the operational direction of the wind turbine.

In certain examples, the system may further comprise one or more sensors for taking the wind measurements.

Certain examples of the present disclosure provide a computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out any method disclosed herein.

Certain examples of the present disclosure provide a computer or processor-readable data carrier having stored thereon such a computer program.

Examples of the present disclosure allow a wind turbine to be aligned more accurately with respect to the true wind, thereby improving the turbine efficiency and power output, leading to higher revenue. For example, certain examples of the present disclosure may achieve an increase in turbine power output of around 5-10% compared with some conventional techniques.

While the invention has been shown and described with reference to certain examples, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention, as defined by the appended claims.

Claims

Claims 1. A method for determining an angle of misalignment between an operational direction of a wind turbine and a wind direction, the method comprising: obtaining wind measurements, wherein the wind measurements are taken behind turbine blades of the turbine downstream of the wind; processing at least some of the wind measurements to reduce or remove a component of the wind measurements in the frequency domain located at a certain frequency; determining the wind direction based at least partially on the processed wind measurements; and determining the angle of misalignment based on a difference between the determined wind direction and the operational direction of the wind turbine.
2. A method according to claim 1, wherein obtaining the wind measurements comprises sampling, in the time domain, at least two spatial components of the wind velocity.
3. A method according to claim 2, wherein the at least two spatial components comprise a wind speed in a first direction and a wind speed in a second direction, wherein the first and second directions are non-parallel.
4. A method according to claim 3, wherein the first and second directions are located in a plane having a normal that is orthogonal to the operational direction of the wind turbine.
5. A method according to claim 4, wherein the first direction is a direction parallel to the operational direction of the wind turbine and the second direction is a direction perpendicular to the first direction.
6. A method according to any of claims 2 to 5, wherein the sampling is done with a sampling rate determined based on a rotational frequency of the turbine blades and a number of turbine blades.
7. A method according to any preceding claim, wherein the wind measurements are taken by one or more sensors located on a nacelle of the wind turbine.
8. A method according to any preceding claim, wherein processing at least some of the wind measurements comprises filtering at least some of the wind measurements in the frequency domain.
9. A method according to claim 8, wherein the filtering comprises filtering at least one spatial component of the wind measurements.
10. A method according to claim 9, wherein the at least one spatial component comprises a spatial component that is not parallel with the operational direction of the wind turbine.
11. A method according to claim 8, 9 or 10, wherein the filtering is performed using a low-pass filter and/or a band-reject filter.
12. A method according to any preceding claim, wherein the certain frequency is determined based on a rotational frequency of the turbine blades and a number of turbine blades.
13. A method according to any preceding claim, further comprising adjusting the operational direction of the wind turbine based on the determined angle of misalignment.
14. A method according to any preceding claim, wherein the wind direction is determined based on: a first value representing a wind speed in a first direction, the first value based on one or more first wind measurements corresponding to the first direction; and a second value representing a wind speed in a second direction, the second value based on one or more second wind measurements corresponding to the second direction, wherein at least one of the first and second wind measurements have been processed.
15. A system for determining an angle of misalignment between an operational direction of a wind turbine and a wind direction, the system comprising a processor configured for: obtaining wind measurements, wherein the wind measurements are taken behind turbine blades of the turbine downstream of the wind; processing at least some of the wind measurements to reduce or remove a component of the wind measurements in the frequency domain located at a certain frequency; determining the wind direction based at least partially on the processed wind measurements; and determining the angle of misalignment based on a difference between the determined wind direction and the operational direction of the wind turbine.
16. A system according to claim 15, wherein the system further comprises one or more sensors for taking the wind measurements.
17. A computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out a method according to any of claims 1 to 14
18. A computer or processor-readable data carrier having stored thereon a computer program according to claim 17.