Enhancing wind turbine wake mixing

Abstract

A method for controlling a wind turbine to improve wake mixing and a wind turbine controller. The method comprises the steps of monitoring a periodic component of an incoming airflow acting on at least a first blade, periodically and dynamically controlling a pitch angle of at least the first blade over time according to a wake mixing control scheme based on the monitored periodic component. For an array of at least a first wind turbine and a second, downstream wind turbine, the method comprises controlling the first wind turbine such that a wake formed downstream of the first wind turbine follows a first periodic pattern, and controlling the second wind turbine such that a wake formed by the second turbine follows a second periodic pattern, wherein at least one of a frequency, a direction and / or a phase offset of the second periodic pattern is coordinated with the first pattern.

Description

[0001] This disclosure relates to a method for controlling a wind turbine, a wind turbine controller arranged in the method for controlling the wind turbine, a wind turbine including the wind turbine controller arranged in the method for controlling the wind turbine, and an array of wind turbines, wherein at least a second wind turbine includes the wind turbine controller.

[0002] To meet climate goals, renewable energy sources such as solar and wind power are needed. The most efficient way to develop wind energy on a large scale is by placing individual wind turbines in so-called wind farms, either onshore or offshore. These wind farms optimize costs for aspects such as wiring, maintenance, and installation. The exact distribution of wind turbines can depend on several parameters, such as soil conditions or the flight path, but the prevailing wind direction plays a crucial role in this design. Typically, the wind turbines are then positioned relative to each other so that their wakes interact with each other minimally when the wind blows from the prevailing direction.

[0003] Nevertheless, the interaction between the wake generated by upstream turbines and downstream turbines occurs relatively frequently, significantly impacting power generation. The wake refers to the region of airflow change behind a turbine. Turbines in the wake typically experience lower wind speeds and increased turbulence. This, in turn, leads to lower power generation and increased fatigue loads on downstream turbines. Wake recovery refers to the phenomenon where wind speeds in the wake return to free-flow speeds due to mixing with ambient air. Wind conditions and turbine design itself determine when wake recovery occurs. The distance at which this occurs is typically greater than a multiple of the rotor diameter. It is estimated that the average power loss due to turbine wakes is approximately 10% to 20% of the total power output of a large offshore wind farm. In addition to reduced power generation, fatigue loads are estimated to increase by 5% to 15%.

[0004] To optimize power output at the wind farm level, wind farm control research in recent years has focused on controlling the wake itself. Specifically, one type of wind farm controller promotes early wake mixing with the surrounding (“free flow”) wind farm by dynamically manipulating the airflow. This method, known as Dynamic Induction Control (DIC), involves collectively pitching the blades at a certain frequency to change the magnitude of thrust. As a result, the induction factor changes, causing the airflow directly behind the turbine to consist of both fast-moving and slow-moving components. These components interact with each other due to their different velocities, thus promoting wake mixing. The resulting pulsating shape of the airflow is characteristic of this method, which is often referred to as the “pulsating” method. A negative consequence of this dynamic actuation is an increase in fatigue loads, particularly on the tower and pitch bearings.

[0005] Dynamic Individual Pitch Control (DIPC) has been proposed as an alternative to DIC. Similar to DIC, DIPC uses pitch actuators to dynamically control airflow. However, instead of co-actuating the blades, DIPC applies a phase offset to each blade. This delay causes the thrust vector to change direction rather than magnitude periodically, resulting in a helical wake behind the turbine. This method is commonly referred to as the "helical" method. This method is specifically explained in the applicant's WO2021 / 096363, and its control concept regarding DIPC is incorporated herein by reference. The "helical" method has several advantages over the "pulse" method. First, thrust variation is significantly reduced because it is more evenly distributed across the rotor disk. However, the blades experience a slightly greater increase in load compared to the "pulse" method.

[0006] As the wake of a wind turbine propagates far downwind, other wind turbines in a wind farm can be affected by it in certain wind directions. Individual turbine control is common in wind farms. This is known as greedy control, where each turbine is designed to achieve its optimal performance. As a result, downstream wake turbines will experience reduced power generation and increased fatigue loads. By following a greedy control strategy, even when a wake-mixing control scheme is applied to the upstream turbines, the wind farm will still exhibit suboptimal behavior due to the wake of the downstream turbines. The distance at which wake recovery occurs is typically much greater than the distance between turbines in a wind farm, because placing turbines close together reduces costs.

[0007] One objective of this disclosure (and possibly among others) may be to obtain a method for controlling a downstream wind turbine that reduces the wake effect on the turbine from the incoming wake and the wake effect from the outgoing wake, wherein at least one of the aforementioned problems is mitigated in part.

[0008] Among other objectives, this objective can be achieved at least in part by a method for controlling a wind turbine including at least a first blade, the method comprising the steps of: monitoring a periodic component of an incoming airflow acting on at least the first blade, and, based on the monitored periodic component, periodically and dynamically controlling the pitch angle of at least the first blade of the wind turbine over time according to a wake mixing control scheme.

[0009] Monitoring periodic components refers to determining the values ​​of periodic components regularly over time. In this way, the monitored periodic components of the incoming airflow, such as the periodic wake of an upstream turbine, can be considered in wake mixing control schemes for downstream turbines. Wake mixing control schemes are typically used to reduce wake effects downstream of turbines, and pitch control enhanced by adding a periodic component further reduces the impact of upstream wakes on the turbine's own power losses and / or fatigue loads. On the one hand, by considering the incoming wind farm, energy production and / or lifetime are thus optimized at the turbine level; on the other hand, energy production of any downstream turbines is maintained at the wind farm level. The periodic component of the incoming airflow can originate from an upstream turbine that generates a periodic wake or any natural phenomenon that generates a periodic airflow. Specifically, in the case of wake meandering, a periodic component of the incoming airflow may be present. Wake meandering refers to the undulating motion of the entire wake region in both the lateral and vertical directions. Wake meandering can involve a slowly changing frequency of the periodic component. In this case, the method may include the additional step of estimating the changing frequency.

[0010] Although designed for pitch angle control, this method can generally be applied to other wake mixing control schemes, including, for example, dynamic yaw. Therefore, the principles of the method described herein are not limited to pitch angle control, as the concept of controlling a wind turbine based on monitored periodic components disclosed herein can also be applied to other types of control.

[0011] In an alternative embodiment of the method, the step of controlling the pitch based on the monitored periodic component includes: coordinating at least one of the frequency, direction, and / or phase offset of the wake generated downstream of the wind turbine with the monitored periodic component, preferably synchronizing the wake generated downstream of the wind turbine with the monitored periodic component in frequency and with a predetermined phase offset. In this way, the wake generated by the turbine can be controlled, preferably synchronized, relative to the inflow to amplify or reduce the turbine's response to the inflow. The control parameters of the downstream wake include the wake frequency (if constant) (or slowly varying, as mentioned above for wake meandering), the wake direction (in the case of a helical wake, both clockwise CW and counterclockwise CCW directions can be selected), and the wake phase offset.

[0012] In an alternative embodiment of the method, at least one of the frequency, direction, and / or phase offset of the downstream wake is set according to the desired objective of power generation and / or load reduction. The desired objective could be increasing the power generation of the wind turbine or reducing load fatigue on the wind turbine. Depending on the desired objective, the frequency, direction, and / or phase offset of the downstream wake can be set. In an alternative embodiment of the method, a given phase offset is set to zero, such that the downstream wake of the wind turbine is in phase with the inflow. Synchronizing the inflow and downstream wake in phase implies reducing pitch actuation at the turbine. In practice, if the downstream turbine control is in phase with the inflow, a similar yaw and tilt response can be generated on the downstream turbine as on the upstream turbine, and the pitch amplitude is reduced. Furthermore, a lower pitch amplitude will reduce pitch bearing fatigue. When the desired objective is load reduction, in-phase control can therefore be selected as a preferred control strategy.

[0013] It should be noted that phase difference (phase offset) is a particularly important parameter for power generation. A predetermined phase offset can be set to a value that maximizes power generation. The optimal phase offset for maximizing power generation can be established through simulation, calculations based on sensed real data (e.g., through trial and error). Being in phase with the incoming wake, being phase-off with a given phase, or being completely out of phase can amplify or attenuate the response, directly affecting wind turbine fatigue and / or wake composition, and thus impacting the production of any other downstream turbines.

[0014] In an alternative embodiment of this method, the wake mixing control scheme is a dynamic individual pitch control scheme, in which the pitch of each blade of the wind turbine is individually controlled to vary periodically over time, thereby generating a helical wake downstream of the wind turbine. By changing the induction factor of the blades, the speed and direction of the wind leaving the turbine (rotor plane) can be locally altered, effectively changing the position of the wake itself. The change in wake position increases turbulence mixing, reducing the distance required to transfer kinetic energy into the wake, and any turbines potentially located downstream of the wind turbine are therefore much less affected by the wake. It should be noted that, more generally, the dynamic individual pitch control scheme can be used to generate a wake with a periodic component, not necessarily a fixed-frequency helix, but perhaps a meandering wake with a slowly varying frequency. Alternatively, the wake mixing control scheme can be a dynamic overall pitch control scheme (pulse control) or dynamic yaw control.

[0015] In an alternative embodiment of the method, monitoring the periodic component of the inflow acting on at least the first blade includes monitoring the phase of the inflow periodic wake. Phase as a function of time t It can be defined as (t)= ), where ω and This refers to the frequency and phase shift of the fundamental component entering the wake. Specifically, the step of monitoring the periodic component of the incoming airflow acting on at least the first blade includes monitoring what is modeled as up(t). At least one parameter of the entry periodic wake, where αi, i and ωi are the amplitude, phase shift, and frequency of each periodic (harmonic) component, and h is the number of periodic components. More specifically, the at least one parameter includes the phase shift of the component entering the periodic wake. i, preferably, is the phase shift of the fundamental component entering the periodic wake. The phase of periodic inflow (usually a pulse or spiral wake). This is an important characteristic at the wind farm level, used to coordinate the wakes of the associated turbines with those of the upstream turbines. Typically, for helical wakes, monitoring the fundamental frequency component is sufficient. More generally, estimation methods can be used to extract harmonics and other frequencies of interest. Alternatively, the phase of the periodically entering airflow can be... This frequency ω can be received by the turbine from an external controller and / or upstream turbine, rather than being monitored locally. It should be noted that the frequency ω is typically available, for example, from the upstream turbine.

[0016] In an alternative embodiment of the method, the step of monitoring the periodic component of the incoming airflow acting on at least the first blade includes estimating and tracking the periodic component. Wind field and / or periodic input disturbance estimation can allow for precise control. Estimation refers to indirect observation based on estimation techniques, typically but not necessarily using a model. Estimation techniques can be used when a model of the system is available, but the internal state of the system cannot be directly observed. Specifically, estimating and tracking the periodic component involves processing data measured at the turbine using a Kalman filter or recursive least squares. Estimation and tracking refer to updating the estimate regularly over time.

[0017] In an alternative embodiment of the method, the step of monitoring the periodic component of the incoming airflow acting on at least the first blade includes measuring at least one state of the wind turbine and preferably deriving an estimate of the periodic component based on the measured state. In this way, if the periodic component cannot be directly sensed, it can be obtained indirectly from the measurement and estimator of a state of the wind turbine. Specifically, at least one state measured on at least the first blade includes any of the following: at least root blade moment at at least one blade; at least one tower signal including, for example, at least one tower moment (top, bottom) or tower top acceleration; at least wind speed and / or wind direction at different points in the wind field in front of or behind the wind turbine (typically several seconds away) using lidar (LIDAR) (forward, backward). In this way, a preview of the wind field in front of (and behind) the wind turbine can be obtained. This allows for more precise control because it can be used to better predict the incoming wake compared to load sensors. Backward-facing lidar may be of interest because it can be used to provide feedback to the turbine controller on the composition of the wake behind the turbine.

[0018] In an alternative embodiment of the method, a wake mixing control scheme is configured to control the amplitude, location, and / or direction of the wake formed downstream of the wind turbine. In this way, the wake may follow a pulse pattern, or a spiral pattern as known in the art, or any other periodic pattern that can be conceived by those skilled in the art to increase wake mixing.

[0019] In an alternative embodiment of the method, the wind turbine includes at least two blades, and controlling the wind turbine includes independently, periodically, and dynamically changing the pitch angle of each blade over time. Specifically, when a first blade and a second blade are present, the pitch angles of both the first (and second) blades can be dynamically changed over time according to a predefined periodic function, wherein the dynamic change of the pitch angle of the second blade is phase-shifted with the dynamic change of the pitch angle of the first blade.

[0020] In an alternative embodiment of the method, a method for controlling an array of at least a first wind turbine and a second wind turbine is provided, wherein, for a given wind direction, the second wind turbine is at least partially arranged downstream of the wake of the first wind turbine, and each wind turbine includes at least a first blade. The method includes the steps of: controlling the first wind turbine such that the wake formed downstream of the first wind turbine follows a first periodic pattern having a first frequency and a first phase offset; and applying the method according to any of the above embodiments to control the second wind turbine such that the wake formed by the second turbine follows a second periodic pattern, wherein at least one of the frequency, direction, and / or phase offset of the second periodic pattern is coordinated with the first pattern. Specifically, the second periodic pattern may be synchronized with the first pattern in frequency and phase-offset relative to the first pattern by a given phase offset. In this way, when controlling the second turbine, the wake of the first turbine can be taken into account to reduce fatigue loads on the second turbine and / or increase its power output.

[0021] In a second aspect of this disclosure, a wind turbine controller is provided for controlling a wind turbine including at least a first blade. The wind turbine controller is configured to receive data relating to a periodic component of an incoming airflow acting on at least the first blade, monitor the periodic component based on the received data, and generate a control signal based on the monitored periodic component, according to a wake mixing control scheme, for dynamically and periodically controlling the pitch angle of at least one blade of the wind turbine over time. Thus, the advantages of the control method are applied to the controller.

[0022] In a third aspect of this disclosure, a wind turbine is provided, further comprising at least a first blade and a wind turbine controller according to any of the preceding wind turbine controller claims. Thus, a wind turbine is obtained that improves the mixing of the downstream wake and withstands less fatigue load and / or generates more electricity due to the intake airflow.

[0023] In an alternative embodiment of this disclosure, the wind turbine includes at least two blades, preferably three blades, wherein controlling the wind turbine includes independently, periodically, and dynamically changing the pitch angle of each blade over time. More generally, this concept can be applied to horizontal-axis wind turbines with rotors, regardless of the number of blades arranged on the rotor.

[0024] In a fourth aspect of the invention, an array of at least two wind turbines is provided, wherein, for a given wind direction, a second wind turbine is at least partially arranged downstream of the wake of a first wind turbine, wherein both the first and second wind turbines include at least a first blade, and wherein the second turbine includes a wind turbine controller according to any of the preceding wind turbine controller claims. Thus, an array of turbines, such as a wind farm, is obtained, wherein the two turbines downstream of each other are configured to improve mixing in their downstream wakes, and the downstream second turbine is further configured to reduce fatigue loads and increase its power output in view of the wake of the first turbine. Furthermore, the electrical energy production of the wind turbine array can be further increased and optimized.

[0025] The present disclosure is further illustrated by the following accompanying drawings, which illustrate exemplary embodiments of a method for controlling a wind turbine according to the present disclosure, and are not intended to limit the scope of the present disclosure in any way, wherein:

[0026] - Figure 1A A schematic diagram of a horizontal xi wind turbine including a three-bladed rotor is shown.

[0027] - Figure 1B The pitch blades are shown schematically;

[0028] - Figure 2A , Figure 2B and Figure 2C The diagram schematically illustrates the average wake velocity at different distances behind the turbine controlled by three different control schemes, where... Figure 2A Corresponding to traditional greed control, Figure 2B Corresponding to DIC control or "pulse" control, and Figure 2C This corresponds to DIPC control or "spiral" control;

[0029] - Figure 3 An array of two wind turbines is schematically shown, wherein the second wind turbine is positioned downstream of the wake of the first wind turbine;

[0030] - Figure 4A , Figure 4B and Figure 4C The illustration shows the representation as follows: Figure 3 A graph showing the average wake velocity at different distances behind the array of two wind turbines, where the upstream turbine is based on... Figure 2A , Figure 2B or Figure 2C Control is performed, and the downstream turbine is based on... Figure 2A To take control;

[0031] - Figure 5 It shows including according to Figure 2C A flowchart of the different steps in the spiral method for controlling a wind turbine;

[0032] - Figure 6 The wake of a wind turbine is schematically shown, wherein a second wind turbine is controlled according to an embodiment of a method for controlling wind turbines in an array of two wind turbines;

[0033] - Figure 7 A helical wake with helical phase and deflection is schematically shown;

[0034] - Figure 8 A flowchart is shown, illustrating different steps of a method for controlling a wind turbine according to an embodiment.

[0035] - Figure 9 This illustrates the use of a Kalman filter as... Figure 8 A flowchart of the different steps of the method in an embodiment of the estimator;

[0036] - Figure 10 It shows including according to Figure 9 A flowchart of the different steps in the method applied to screw control;

[0037] - Figure 11 A flowchart is shown, illustrating different steps of a method according to another embodiment using a recursive least squares estimator applied to spiral control;

[0038] - Figure 12A and Figure 12B The diagram schematically illustrates the wake of a wind turbine in an array of three turbines, where... Figure 12A In the middle, the second wind turbine, such as Figure 5 Control is performed, and the third turbine is based on, for example Figure 2A The greedy control scheme is used for control, and in Figure 12B In the middle, the second and third turbines are based on, as follows Figure 2A The greedy control scheme is used for control;

[0039] - Figure 13A This shows that, based on the phase shift of the second turbine relative to the first turbine, in Figure 12A and Figure 12B The difference in power generated by the second turbine between different scenarios;

[0040] - Figure 13B This shows that, based on the phase shift of the second turbine relative to the first turbine, in Figure 12A and 12B The difference in power generated by the third turbine between the scenarios.

[0041] Figure 1A The layout of a typical bladed horizontal-axis wind turbine 1 is schematically shown. The wind turbine 1 is located on top of the base 3. It should be noted that this wind turbine can be deployed both on land and at sea. In the latter case, the base 3 will typically be an offshore base, such as a seabed-fixed structure mounted to the seabed.

[0042] The nacelle 4, connected to the rotor 5, is positioned on top of the tower 2. The rotor 5 comprises three blades 51, 52, and 53, but any number of blades is possible; for example, one, two, or four blades are also conceivable. Blades 51, 52, and 53 are fixed to the hub. The rotation of the nacelle 4 about a vertical axis I that is substantially parallel to or coincides with the tower 2 and substantially perpendicular to the ground plane is called yaw rotation. The yaw angle can be defined according to the wind direction; in this case, a non-zero yaw angle means that there is a deviation between the direction of the rotor axis II and the wind direction W. The rotor 5 is arranged to rotate about the rotor axis II; this rotation is commonly referred to as azimuth rotation. Blades 51, 52, and 53 are also arranged to rotate about their respective longitudinal axes III; this rotation is called pitch rotation. The angle between the central axis V of the cross-section of blades 51, 52, and 53 and the plane of rotation IV of the rotor 5 is called the pitch angle. Figure 1B The cross-section of the first blade 51 is shown with its central axis V pitched relative to the rotor plane IV at a pitch angle θ1. Blade root torque sensors can be arranged on each blade to sense the blade root torque. The blade root torque sensors 55 are typically resistance-based strain gauges (SGs) attached to the surface at the root of the rotor blade. Multiple such sensors are typically arranged at the root of the blade to measure the blade root torque.

[0043] Figure 2A , Figure 2B and Figure 2C The diagram schematically illustrates the average wake velocity at different distances behind the turbine controlled by three different control schemes, where... Figure 2A Corresponding to traditional greed control, Figure 2B Corresponding to DIC control or "pulse" control, Figure 2C This corresponds to DIPC control or helical control. Figure 2A A baseline scenario is shown where a turbine is controlled according to a greedy control scheme that produces a wake downstream of the turbine, which is stable and can be defined as normal. By comparison, Figure 2B The wake is a result of the "pulse" method and shows the periodically detached vortex rings. Finally, Figure 2CThe wake is a result of the "spiral" method and follows a spiral pattern. The deeper portions indicate the isosurface for a specific wind speed, while the shallower portions represent the absolute wind speed. This distance is further scaled by the rotor diameter. It should be noted that both the "pulse" and "spiral" methods are qualified as wake mixing control schemes. These are more effective for wind speeds below the rated wind speed. This is because the power loss of the downstream turbine is significantly reduced above the rated speed.

[0044] Figure 3 An array of two wind turbines is schematically shown, with the second wind turbine positioned downstream of the wake of the first wind turbine. The wind direction W positions the second wind turbine 102 downstream of the wake of the first wind turbine 101. The wake can be considered as a region with increased turbulence and a decreasing (average) wind speed, as indicated by dashed lines 103 and 104. The wake generated by wind turbine 101 will slowly mix with the surrounding (unaffected) wind field, and due to this mixing, the wake effect will decrease with increasing distance from the turbine. Turbines 101 and 102 are typically positioned with a mutual distance d of three to ten times (3D-10D) the rotor diameter, where a mutual distance of ten times the rotor diameter will significantly result in a lower wake effect, such as reduced power output and reduced vibration, thereby reducing fatigue loads on different wind turbine components.

[0045] Figure 4A , Figure 4B and Figure 4C The illustration shows the representation as follows: Figure 3 A graph showing the average wake velocity at different distances behind the array of two wind turbines, where the upstream turbine is based on... Figure 2A , Figure 2B or Figure 2C Control is performed, and the downstream turbine is based on... Figure 2A Control is implemented. These figures illustrate how different wake mixing control schemes reduce wake effects, and in particular how to increase power output. These figures show power increases from 6.1 MW with greedy control to 7.2 MW with "pulse" control, and finally to 8.2 MW with "spiral" control.

[0046] However, as mentioned above, wind farms typically must be developed within limited space, and longer distances between them can reduce the overall power output of the wind farm, leading to higher costs for the generated energy. Therefore, reducing wake effects is beneficial, allowing turbines to be placed at shorter distances while optimizing power output and reducing fatigue loads.

[0047] Figure 5 It shows including according to Figure 2CThe flowchart shows the different steps of the spiral method for controlling a wind turbine.

[0048] Figure 5 A block diagram or flowchart 200 illustrates the steps of a control method for controlling a wind turbine based on a "spiral" wake mixing control scheme. In step 201, periodic yaw and roll functions 2011 and 2012 are defined, wherein the periodic yaw and roll functions 2011 and 2012 are defined as having a common predefined frequency. f The sinusoidal function, wherein the periodic tilt and yaw functions 2011, 2012 have a phase shift preferably of 90° or 270°. Therefore, in this particular embodiment, known as the helical method, both the tilt and yaw degrees of freedom are excited, but with a phase shift of π / 2 rad (90°). This will result in a time-varying torque on the rotor disk (as seen in a non-rotating coordinate system), each T = 1 / f One rotation is completed in seconds, resulting in a spiral wake, such as Figure 4C As shown.

[0049] Predetermined frequencies of periodic yaw and yaw functions in 2011 and 2012 f It can be based on a dimensionless number called the Strauhal number relative to the inflow wind speed. U ∞ and turbine rotor diameter D To determine:

[0050]

[0051] The optimal Strouhal number is preferably between 0.05 and 1.0, more preferably between 0.15 and 0.55, even more preferably between 0.2 and 0.3, and most preferably about 0.25. As explained in the previous patent application WO2021 / 096363, this optimal value has been estimated by performing a grid search for different frequencies under laminar flow conditions in a simulation program (Simulator for Wind Farm Applications (SOWFA)). The Strouhal number can be selected to determine the excitation frequency. Furthermore, the pitch amplitude... Preferably 15° or less, more preferably 10° or less, even more preferably 5° or less, and most preferably between 2° and 4°, because (preferably) an excessively large pitch amplitude of the sinusoidal pitch change will result in an increase in the load on the turbine.

[0052] The inverse multi-blade coordinate (MBC) transformation step (203) is applied to obtain the periodic variations of the pitch angles θ1, θ2, and θ3 of the corresponding blades 51, 52, and 53. The multi-blade coordinate transformation is decoupled in a non-rotating reference frame (or in other words: MappingBlade load, and is a transformation used in, for example, a separate pitch control method designed to reduce fatigue loads on wind turbines. It depends on the rotor speed per n revolutions ( n P) Load harmonics are converted to steady-state components, thus simplifying controller design. The equations for achieving this transformation are summarized. Measured out-of-plane blade root bending moment. M(t)∈ R B This is provided for a positive transformation, thereby transforming the rotating blade torque into a non-rotating reference frame in Equation A below (also as shown, for example, in step 207):

[0053] (A)

[0054] in

[0055]

[0056] in, n Z + It is the harmonic number. B∈Z + It is the total number of leaves, and ψ b R It is a leaf b Z + The azimuth angle, where ψ=0° indicates a vertical position. Common mode M 0 This represents the cumulative out-of-plane rotor torque, and M t and M y These represent the fixed coordinate system and the yaw moment and tilt moment (2071, 2072) independent of the azimuth angle, respectively. The latter two components are typically used to reduce load fatigue.

[0057] By applying the inverse MBC transformation to the non-rotating signal (in step 201), a separate pitch component is generated in the rotating (i.e., blade) coordinate system.

[0058]

[0059] in

[0060]

[0061] in, θ 0,n , θ t,n and θ y,n These are the collective pitch, tilt, and yaw / pitch signals in a fixed coordinate system, respectively. ψ o,n It is the azimuth offset of each harmonic.

[0062] The possibility of using, for example, a pitch actuator to individually drive the pitch of the rotor blades can now be employed to increase the wake recovery effect, or in other words, increase wake mixing. By individually pitching the blades, it is possible to control the turbine thrust and subsequent power generation to near... greedy Optimal (Step 205).

[0063] In the control method based on the "spiral" wake mixing control scheme, the blades are individually pitched according to the periodic changes in pitch angles θ1, θ2, and θ3 to stimulate wake mixing by individually changing the inducible factors of the blades and thus the yaw angle of attack of the turbine. As explained above, the control method enables the application of yaw and yaw moments on the rotor by applying the MBC transformation, as shown in step 207. These yaw and yaw moments 207 then result in forced wake mixing, where the changes in power and wake velocity are small. This is achieved by superimposing the periodic changes in pitch angles θ1, θ2, and θ3 (step 204) on the overall blade pitch angle of the wind turbine.

[0064] First, these mapped load signals are transformed into a rotating coordinate system using the MBC transformation explained above to obtain the desired pitch angle. For the same sinusoidal yaw and roll signals, where the roll signal has a 90° phase delay, this results in sinusoidal pitch signals with different frequencies according to common trigonometric formulas. β :

[0065]

[0066] in, ψ b It is the azimuth position of blade number b. f h It is a new spiral excitation frequency. b It is the phase shift of blade b. Therefore, it can be determined that... f h = f + f r ,in, f r It is the rotational frequency of the rotor.

[0067] For example, if the periodic yaw function 2011 is set to zero (yaw IPC), or the periodic yaw function 2012 is set to zero (yaw IPC), an alternative solution is found. In this case, the inverse MBC (step 203) and common trigonometric formulas result in periodic variations of pitch angles θ1, θ2, θ3, where these periodic variations subsequently become the superposition of two sinusoidal signals, the first of which has a first frequency. f h = f + f r The second sinusoidal signal has a second frequency. f h = f r - f .

[0068] Figure 6 The wakes of two wind turbines 301 and 302 are schematically shown, wherein the second wind turbine 302 is positioned downstream of the wake of the first wind turbine 301 and is controlled according to an embodiment of a method for controlling wind turbines in an array of two wind turbines. The first wind turbine 301 is controlled according to... Figure 5 The "spiral" wake mixing control scheme described herein is used for control. A first wind turbine 301 generates a downstream spiral wake 401 with a first spiral pattern at the location of the second turbine, the first spiral pattern having a predetermined frequency and a given phase. The second wind turbine 302 is also controlled according to the "spiral" wake mixing control scheme, thereby also generating a downstream spiral wake 402 with a second spiral pattern. The second spiral pattern has the same frequency as the first spiral pattern, and is phase-shifted relative to the first pattern at the location of the second turbine 302. Perform a phase shift. Specifically, the phase shift amount... It can be set to zero to synchronize the wake 402 of the second turbine 302 with the wake 401 of the first turbine 301, or it can be set to a value that optimizes power production, such as 270°. The second helical mode can also have the same or opposite direction as the first mode. CW is generally better used to minimize pitch bearing load, but CCW can produce a stronger power increase. Two directions can be used in this method. These directions can also be combined for upstream and downstream turbines.

[0069] Figure 7 Schematic illustration of a spiral phase The helical wake with deflection d. The phase of the helical wake. (x, t) can be defined as the deflection angle at any position x downstream of the turbine at time t. In other words, the phase. (x, t) is the position of a point in the wake at the rotor center at a distance x in a cross section at time t (i.e., in a plane perpendicular to the main propagation direction of the downstream wake of the wind turbine) relative to the vertical axis. Figure 7 The z-axis in the equation is equivalent to Figure 1A The angle between the rotor axis (I) and the rotor center wake. The deflection d is the position of a point in the wake at the rotor center relative to the rotor axis (I). Figure 7 The x-axis in the diagram is equivalent to Figure 1A The distance between the II axis and the axis.

[0070] Figure 8 A flowchart illustrating the various steps of a method for controlling a wind turbine according to an embodiment is shown. For illustrative purposes, the flowchart has been oversimplified. The wake 501 is modeled as acting on the control input signal u. k It has a known frequency ωe and an unknown phase. Input disturbance V k Control input u k and input disturbance V k All inputs are fed into a linear time-varying (LTI) wind turbine system 502. The output of the wind turbine system 502 is fed into an estimator 503, which generates an estimated phase ˆ for the input disturbance 501. Then estimate the phase ˆ Feed to generate control input signal u k The synchronization controller 504 feeds the estimated phase of the incoming wake 501 to the wind turbine system 502, so that the downstream wake generated by the wind turbine can be phase-shifted with the incoming wake 501. For example, in-phase spiral synchronization or spiral wake suppression can be envisioned. The estimation performed by the estimator 503 can take different forms. Figure 9 and Figure 10 The use of Kalman filters as estimators was explored, while Figure 11 The use of a recursive least squares estimator is illustrated. The same figure labels will be assigned... Figure 8-11 Similar components in [the text].

[0071] Figure 9 This illustrates the use of a Kalman filter as... Figure 8 A flowchart illustrating the different steps of the method in an embodiment of estimator 503. (Compared to...) Figure 8 Similarly, the wake 501 is modeled as acting on the control input channel u. c k The frequency ωe on the surface is known and the phase is unknown. Periodic wake disturbance u p k Load disturbance w kIt also acts on this channel (via adder 602) to form the input disturbance u. k u The input disturbance u k u A noise sequence containing the variance of capturing non-periodic input disturbances (such as wind speed). Similar to... Figure 5 The inverse MBC 604 (also known as reverse MBC) of component 203, the wind turbine control system 605 and similar Figure 5 The forward MBC (also known as MBC) of element 206 is formed together. Figure 8 The wind turbine system 502. The MBC transformation is used to transform the rotating coordinate system of the rotor blades to the non-rotating coordinate system of the rotor via mapping, and vice versa. k Interference and control input u k c These are fed together into the Kalman filter estimator. Therefore, the Kalman filter takes blade yaw and yawing moments, as well as yaw and yawing control pitch angles, as inputs. The Kalman filter includes an estimate of the periodic wake disturbance u. p k The required discrete-time linearized state space of the wind turbine. In other words, the Kalman filter is model-based. The wake frequency ωe is a known quantity used in the enhancement system, which produces an estimate ˆu used by the controller for phase synchronization. p k Then, control input u k c The feedback is returned to adder 603, which also receives the input disturbance u. k u As input to the wind turbine system.

[0072] Figure 10 The following is shown: including the basis for applying screw control Figure 9 The flowchart shows the different steps of the method. In the case of the "spiral" control scheme, the estimated ˆu output by the Kalman filter 608 is shown. p k Use box 709(T) dq The (ωet) transform is used to remove the ωe component. The resulting quantity contains information about the phase of the helical perturbation. The phase is then calculated using the arctangent (atan2(y,x)) in box 710. Therefore, the advantage of the Kalman filter is that it directly estimates the phase of the helical wake.

[0073] Figure 11A flowchart illustrating the different steps of a method according to another embodiment using a recursive least squares estimator applied to helical control is shown. Unlike model-based Kalman estimation, the RLS estimator is model-free. The RLS estimator utilizes the fact that the phase information entering the helical wake is contained in the DC offsets of the yaw and tilt moments in equation (A) established in the context of the resulting "helical" method. These DC offsets can be estimated using filtering methods such as recursive least squares adaptive filters. Therefore, the RLS estimator has the advantage of being easily implemented to adapt to the dynamic changes of the wind turbine. One disadvantage is that it does not directly estimate the phase of the helical wake, but rather the combined phase of the wake inflow and the controller action. Figure 10 As shown, the output y of the Park and Clarke transformations (via blocks 801 and 802) k The summation (via adder 803) is used as input to the square root RLS estimator 804. The obtained estimate is filtered by a low-pass filter 805, and then the phase is calculated. (Box 806, atan2(y,x) function). To correct for coupling and actuator delay, an optimal azimuth offset is added (via adder 807) before the phase estimate is used to employ the "spiral" method. ψ o .

[0074] Figure 12A and Figure 12B The diagram schematically illustrates the wake of a wind turbine in an array of three turbines, where... Figure 12A In the middle, the second wind turbine, such as Figure 5 Control is performed during this process, and the third turbine is based on, for example... Figure 2A The greedy control scheme is used for control, and in Figure 12B In the middle, the second and third turbines are based on, as follows Figure 2A A greedy control scheme is used for control. Figure 12A In this configuration, the first turbine 301 generates a helical wake 401, the second turbine 302 generates a helical wake 402, and the third turbine 303, controlled by greedy control, generates a (standard / aperiodic) wake 403. Figure 12B In the baseline case, the first turbine 301 generates a spiral wake 401, the second turbine 302 is controlled according to greedy control and generates a (standard / aperiodic) wake 402, and the third turbine 303, which is controlled according to greedy control, generates a wake 403.

[0075] Figure 13A This shows that, based on the phase shift of the second turbine relative to the first turbine, in Figure 12A and Figure 12BThe percentage difference in power generated by the second turbine 302 between the scenarios. The percentage is given relative to a baseline of the same turbine unit. Figure 13B This shows that, based on the phase shift of the second turbine relative to the first turbine, in Figure 12A and Figure 12B The percentage difference in power generated by the third turbine 303 between scenarios. From Figure 12A and Figure 12B In this configuration, synchronization of the in-phase helical wake in turbine 302 does not result in an increase in the power output of the three-turbine system. The second turbine 302 is able to coordinate / synchronize with the inlet helix with minimal power loss. However, on average, the third turbine 303 exhibits reduced power output relative to the baseline.

[0076] However, when the second turbine 302 is phase-shifted relative to the first turbine 301 by approximately -π / 2, the optimal power output of the third and second turbines can be found. In this setup, the third turbine 303 generates an average of +9.79% more power than the baseline, while the phase shift does not cause any power loss in the second turbine, thus implying an increase in the power generation of the three-turbine system. More generally, it can be seen that selecting appropriate phase angles between the wakes of several turbines downstream of each other can improve the power generation of the entire system including the turbines.

[0077] Although the principles of the invention have been explained above with reference to specific embodiments, it should be understood that this description is merely illustrative and not intended to limit the scope of protection defined by the appended claims.

Claims

1. A method for controlling a wind turbine, the wind turbine comprising at least a first blade, the method comprising the steps of: - Monitor the periodic component of the incoming airflow acting on at least the first blade; - Based on the monitored periodic components, the pitch angle of at least the first blade of the wind turbine is controlled periodically and dynamically over time according to the wake mixing control scheme.

2. The method according to claim 1, wherein, Pitch control based on monitored periodic components includes aligning at least one of the frequency, direction, and / or phase offsets of the wake generated downstream of the wind turbine with the monitored periodic components.

3. The method according to the preceding claim, wherein, At least one of the frequency, direction, and / or phase offset of the wake generated downstream is further set according to the desired objectives of power production and / or load mitigation.

4. The method according to any one of the preceding claims, wherein, Pitch control is based on monitored periodic components, which includes synchronizing the wake generated downstream of the wind turbine with the monitored periodic components in frequency and with a predetermined phase shift.

5. The method according to the preceding claim, wherein, The predetermined phase offset is set to zero, so that the wind turbine is in phase with the incoming airflow.

6. The method according to any one of the preceding claims, wherein, The wake mixing control scheme is a dynamic individual pitch control scheme in which the pitch of each blade of the wind turbine is independently controlled to change periodically over time, thereby generating a spiral wake downstream of the wind turbine.

7. The method according to any one of the preceding claims, wherein, Monitoring the periodic components of the inflow acting on at least the first blade includes monitoring the phase of the inflow periodic wake. .

8. The method according to any one of the preceding claims, wherein, Monitoring the periodic components of the inflow acting on at least the first blade includes monitoring at least one parameter of the inflow periodic wake, which is modeled as... up(t) Among them, αi, i and ωi are the amplitude, phase shift, and frequency of each periodic component, and h is the number of periodic components, wherein, preferably, the at least one parameter includes the phase shift of the fundamental component entering the periodic wake. .

9. The method according to any one of the preceding claims, wherein, Monitoring the periodic component of the incoming airflow acting on at least the first blade includes measuring at least one state of the turbine, and preferably deriving an estimate of the periodic component based on the measured state.

10. The method according to the preceding claim, wherein, Measuring at least one condition of a turbine includes measuring at least the root blade torque on at least the first blade.

11. The method according to any one of the preceding claims, wherein, Monitoring the periodic components of the inlet airflow acting on at least the first blade includes estimating and tracking the periodic components of the inlet airflow acting on at least the first blade.

12. The method according to the preceding claims and any one of claims 9 or 10, wherein, Estimating and tracking periodic components involves processing at least one measurement of the turbine's state using a Kalman filter or recursive least squares.

13. The method according to any one of the preceding claims, wherein, The wake mixing control scheme is configured to control the amplitude, position, frequency, phase shift, and / or direction of the wake formed downstream of the wind turbine.

14. The method according to any one of the preceding claims, wherein, The wind turbine includes at least two blades, and controlling the wind turbine includes independently, periodically and dynamically changing the pitch angle of each blade over time.

15. A method for controlling an array of at least a first wind turbine and a second wind turbine, wherein, For a given wind direction, a second wind turbine is at least partially positioned downstream of the wake of the first wind turbine, wherein each wind turbine includes at least a first blade, and the method includes the following steps: - Control the first wind turbine so that the wake formed downstream of the first wind turbine follows a first periodic pattern with a first frequency and a first phase shift. - The method according to any one of the preceding claims is applied to control the second wind turbine such that the wake formed by the second turbine follows a second periodic pattern, wherein at least one of the frequency, direction and / or phase offset of the second periodic pattern is coordinated with the first pattern.

16. A wind turbine controller for controlling a wind turbine, the wind turbine including at least a first blade, the wind turbine controller being configured to: - Receive data relating to the periodic components of the incoming airflow acting on at least the first blade. - Monitor periodic components based on received data. - Based on the monitored periodic components, a control signal is generated according to the wake mixing control scheme, which is used to dynamically and periodically control the pitch angle of at least one blade of the wind turbine over time.

17. The wind turbine controller according to any one of the preceding claims, wherein, Pitch control based on monitored periodic components includes aligning at least one of the frequency, direction, and / or phase offset of the wake generated downstream of the wind turbine with the monitored periodic components.

18. The wind turbine controller according to any one of the preceding controller claims, wherein, At least one of the frequency, direction, and / or phase offset of the wake generated downstream is set according to the desired objectives of power production and / or load mitigation.

19. The wind turbine controller according to any one of the preceding controller claims, wherein, Pitch control is based on monitored periodic components, which includes synchronizing the wake generated downstream of the wind turbine with the monitored periodic components in frequency and with a predetermined phase offset.

20. The wind turbine controller according to the preceding claim, wherein, The predetermined phase offset is zero, so that the wake downstream of the wind turbine is in phase with the incoming airflow.

21. The wind turbine controller according to any one of the preceding controller claims, wherein, The wake mixing control scheme is a dynamic individual pitch control scheme in which the pitch of each blade of the wind turbine is independently controlled to change periodically over time, thereby generating a spiral wake downstream of the wind turbine.

22. The wind turbine controller according to any one of the preceding controller claims, wherein, Monitoring the periodic components of the inlet airflow acting on at least the first blade includes monitoring the phase of the inlet periodic wake. .

23. The wind turbine controller according to any one of the preceding controller claims, wherein, Monitoring the periodic components of the inflow acting on at least the first blade includes monitoring at least one parameter of the inflow periodic wake, which is modeled as... up(t) Among them, αi, i and ωi are the amplitude, phase shift, and frequency of each periodic component, and h is the number of periodic components. Preferably, the at least one parameter includes the phase shift of the fundamental component entering the periodic wake. .

24. The wind turbine controller according to any one of the preceding controller claims, wherein, Monitoring the periodic component of the incoming airflow acting on at least the first blade includes measuring at least one state of the turbine, and preferably deriving an estimate of the periodic component based on the measured state.

25. The wind turbine controller according to the preceding claim, wherein, At least one state of the turbine includes root blade torque.

26. The wind turbine controller according to any one of the preceding controller claims, wherein, Monitoring the periodic components of the inlet airflow acting on at least the first blade includes estimating and tracking the periodic components of the inlet airflow acting on at least the first blade.

27. The wind turbine controller according to any one of the preceding claims and claim 24 or 25, wherein, Estimating and tracking the periodic components involves processing at least one measurement of the turbine's state using a Kalman filter or recursive least squares method.

28. The wind turbine controller according to any one of the preceding controller claims, wherein, The wake mixing control scheme is configured to control the amplitude, position, frequency, phase shift, and / or direction of the wake formed downstream of the wind turbine.

29. The wind turbine controller according to any one of the preceding controller claims, wherein, The controller is used for a wind turbine with at least two blades, and wherein controlling the wind turbine includes independently, periodically and dynamically changing the pitch angle of each blade over time.

30. A wind turbine, comprising at least a first blade, and further comprising a wind turbine controller according to any one of the preceding claims.

31. The wind turbine according to the preceding claim, wherein, The wind turbine includes at least two blades, preferably three blades, wherein controlling the wind turbine includes independently, periodically and dynamically changing the pitch angle of each blade over time.

32. An array of at least two wind turbines, wherein, For a given wind direction, the second wind turbine is at least partially disposed downstream of the wake of the first wind turbine, wherein both the first and second wind turbines include at least a first blade, and wherein the second turbine includes a wind turbine controller according to any one of the preceding claims for a wind turbine controller.

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