BLADE PITCH CONTROLLER FOR A WIND TURBINE

Abstract

A blade pitch controller for a wind turbine includes a nominal control system and a tower feedback loop. The tower feedback loop includes a filtering system. The filtering system is arranged to control wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine which is above a filter frequency of the filtering system.

Claims

1. A blade pitch controller for a wind turbine, the blade pitch controller comprising a nominal control system and a tower feedback loop, wherein the tower feedback loop comprises a filtering system, and the tower feedback loop is arranged to control wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine above a filter frequency of the filtering system.

2. A blade pitch controller as claimed in claim 1, wherein the filtering system comprises one or more of a high-pass filter, a low-pass filter and a notch filter.

3. A blade pitch controller as claimed in claim 2, wherein the filter frequency of the filtering system is the filter frequency of the high-pass filter.

4. A blade pitch controller as claimed in claim 1, wherein the tower feedback loop is arranged to control wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to both wave- and wind-induced motion of the wind turbine; and/or in response to motion of the wind turbine within a bandwidth of a blade pitch actuator.

5. (canceled)

6. A blade pitch controller as claimed in claim 1, wherein position and/or velocity measurements and/or estimates of the wind turbine are provided as input to the filtering system.

7. A blade pitch controller as claimed in claim 6, wherein the position and/or velocity measurements and/or estimates are provided from one or more sensors located on a tower or foundation of the wind turbine.

8. A blade pitch controller as claimed in claim 7, wherein the one or more sensors are located at or near a water line on the wind turbine.

9. A blade pitch controller as claimed in claim 1, wherein the filtering system is arranged to output filtered position and/or velocity measurements and/or estimates of the wind turbine.

10. A blade pitch controller as claimed in claim 1, wherein the filtering system is arranged to filter position and velocity measurements and/or estimates of the wind turbine differently.

11. A blade pitch controller as claimed in claim 1, wherein the filtering system is arranged to filter out static and/or quasi-static motion; and/or motion at a blade passing frequency.

12. (canceled)

13. A blade pitch controller as claimed in claim 1, wherein the tower feedback loop further comprises a feedback controller.

14. A blade pitch controller as claimed in claim 13, wherein the feedback controller is arranged to determine a blade pitch reference signal from filtered position and/or velocity measurements and/or estimates of the wind turbine output from the filtering system.

15. A method of controlling blade pitch of a wind turbine, the method comprising using a blade pitch controller with a with a filtering system to control the blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine above a filter frequency of the filtering system.

16. A method as claimed in claim 15, the method comprising controlling wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to both wave- and wind-induced motion of the wind turbine.

17. A method as claimed in claim 15, the method comprising controlling wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine within a bandwidth of a blade pitch actuator.

18. A method as claimed in claim 15, the method comprising using the filtering system to filter position and/or velocity measurements and/or estimates of the wind turbine.

19. A method as claimed in claim 15, the method comprising: filtering position and velocity measurements and/or estimates of the wind turbine differently; filtering out static and/or quasi-static motion; and/or filtering out motion at a blade passing frequency.

20. A method as claimed in claim 15, the method comprising determining a blade pitch reference signal from filtered position and/or velocity measurements and/or estimates of the wind turbine.

21. A wind turbine comprising a blade pitch controller as claimed in claim 1.

22. A tower feedback controller for a blade pitch controller for a wind turbine, wherein the tower feedback controller comprises a filtering system and the filtering system is arranged to control wind turbine blade pitch so as to provide additional effective stiffness to the wind turbine in response to motion of the wind turbine above a filter frequency of the filtering system.

Description

[0054] Preferred embodiments of the invention will now be described by way of example only and with reference to the accompanying drawings, in which:

[0055] FIG. 1 is a schematic diagram of a typical fixed foundation offshore wind turbine;

[0056] FIG. 2 is a schematic diagram of a known blade pitch control system;

[0057] FIG. 3 is a schematic diagram of an embodiment of a blade pitch control system according to the invention;

[0058] FIG. 4 is a graph comparing unfiltered signals and filtered signals according to an embodiment of the invention;

[0059] FIG. 5 is a lifetime comparison plot of the accumulation of fatigue damage in the wind turbine foundation; and

[0060] FIGS. 6a-d are plots showing the results of a simulation illustrating the effectiveness of a blade pitch controller according to the invention compared with conventional damping control.

[0061] The present invention relates to a blade pitch controller 20 for a fixed foundation offshore wind turbine 1, as illustrated schematically in FIGS. 3 and 1, respectively.

[0062] In order to better understand the blade pitch controller 20 of the present invention, it is helpful to first consider a prior art blade pitch controller 10, as illustrated schematically in FIG. 2.

[0063] The blade pitch controller 10, which is described in more detail in Smilden, 2018, consists of two parts: a nominal control system 11 and a tower feedback loop 12.

[0064] The nominal control system 11 comprises a basic controller 13 which receives signals from and sends signals to an offshore wind turbine 14. The basic controller 13 of the nominal control system 11 adjusts the blade pitch of the wind turbine in order to optimise power production.

[0065] The nominal control system 11 is combined with a tower feedback loop 12, which adjusts the blade pitch of the wind turbine to reduce or minimise tower motions.

[0066] The tower feedback loop 12 receives measurements (signals) directly from the offshore wind turbine 14. The main objective of the tower feedback loop 12 is to reduce wave-induced fatigue loads in the tower 5. Proportional-derivative collective pitch control is employed to provide the tower 5 with additional damping and stiffness in the fore-aft direction. Proportional action on the tower displacement with a zero reference input would introduce a steady-state rotor speed error. Therefore, a reference model 16 is employed to produce a non-zero reference trajectory representing the wind-induced tower displacement. In effect, the tower feedback loop 12 only provides stiffness against wave-induced tower displacements in a frequency range about the frequencies of significant turbulent wind variations. Typically, information about the tower displacements is not available with standard wind turbine measurements. In addition, the reference model requires information about the rotor wide effective wind speed, which cannot be measured directly. As such, a state estimator 15 is required in the tower feedback look 12 to determine (or estimate) these variables. A discrete-time extended Kalman filter is formulated to calculate the required state estimates.

[0067] A feedback controller 17 receives the outputs from the state estimator 15 and reference model 16, and feeds this back to the wind turbine 14 in combination with the output from the basic controller 13.

[0068] Thus, the tower feedback loop 12 operates in such a way that stiffness is only increased in response to wave induced motion (as opposed to wind-induced motion). This is because there will normally be a degree of wind-induced tower displacement—i.e. the tower will bend in the wind (and stay bent to some degree as long as the wind does not change). The state estimator 15 serves to estimate the tower motions and the reference model 16 provides a tower displacement value (which is not or cannot be directly measured) which can be subtracted so that the normal wind-induced displacement does not cause an error. Put simply, the tower feedback loop 12 determines what the wind turbine movements are relative to an actual bent position (caused by the wind) rather than relative to an upright position (which the tower may not necessarily be in).

[0069] However, this controller 10 is relatively complex and has various disadvantages as mentioned above.

[0070] The blade pitch controller 20 of the present invention, as illustrated in FIG. 3, provides a simplified and improved blade pitch controller compared with that illustrated in FIG. 2.

[0071] In the blade pitch controller 20, the nominal control system 11 is unchanged from that of FIG. 2. However, a new tower feedback loop 22 is provided, instead of the tower feedback loop 12 of the controller 10.

[0072] The tower feedback loop 22 contains a filtering system 25 instead of the state estimator 15 and reference model 16. The filtering system 25 comprises a high-pass filter and operates to provide additional effective stiffness to the wind turbine in response to all measured dynamic motion of the tower above the filter frequency of the high pass filter that is within the bandwidth of the blade pitch actuator, i.e. in response to both wave- and wind-induced motion. In contrast to this, the tower feedback loop 12 provides stiffness only to the wave-induced part of the dynamic motions of the tower 5.

[0073] As the filtering system 25 operates to provide additional effective stiffness to all measured dynamic motion of the tower above the filter frequency of the high pass filter that is within the bandwidth of the blade pitch actuator, this will exclude any influence due to the tower 5 bending due to a steady wind or gentle changes in the wind (zero or low frequency) but will act on motion caused by the relatively high frequency of waves hitting the tower 5.

[0074] The tower feedback loop 22 contains a feedback controller 17′. The structure of this feedback controller 17′ is the same as that of the feedback controller 17 of FIG. 2. Their parameters could also be the same. However, typically, their parameters are not the same as (when) for the feedback controller 17′ the motion sensors are located closer to the waterline than for the feedback controller 17.

[0075] The feedback controller 17′ outputs a signal β.sub.TFC, which is an additional blade pitch reference signal that is added to the nominal blade pitch reference signal u.sub.B from the basic controller 13.

[0076] The output β.sub.TFC from the feedback controller 17 can be expressed as:

[00004]$\begin{array}{cc}{\beta }_{\mathrm{TFC}}=\frac{1}{F_A^{\beta }\left(\omega ,\beta \right)}\left(K_p^{\text{?}}{x}_{f1}+K_D^{\text{?}}{\stackrel{\text{?}}{x}}_{f2}\right).& \left(2\right)\end{array}$$\text{?}\text{indicates text missing or illegible when filed}$

where K.sub.P.sup.χ is the proportional gain, and K.sub.D.sup.χ is the derivative gain. F.sub.A.sup.β(ω,β) is implemented as an estimate of the derivative from pitch angle to aerodynamic thrust force:

[00005]$\begin{array}{cc}{F}_A^{\beta }\left(\omega ,\beta \right)=\frac{\partial F_A}{\partial \beta }{.Math.}_{\left(\omega ,\beta \right)}<0,& \left(3\right)\end{array}$

where ω is the rotor speed and β is the blade pitch angle.

[0077] Furthermore: [0078] χ.sub.f1 is the filtered position measurement/estimate χ, which could relate either to a translation (surge) or angular motion (pitch) in the nacelle direction. It could be measured directly or it could be calculated based on position, velocity and/or acceleration measurements. [0079] {dot over (χ)}.sub.f2 is the filtered velocity measurement/estimate {dot over (χ)}, which could relate either to a translation velocity or angular velocity in the nacelle direction. It could be measured directly or it could be calculated based on position, velocity and/or acceleration measurements.

[0080] The x direction with respect to the wind turbine is as indicated in FIG. 1.

[0081] Filtering is provided by the filtering system 25. Different filtering could be used on the position and velocity measurements and filtering may not be required at all on the {dot over (χ)}.sub.f2 measurement.

[0082] The filtering applied to the measurements χ and {dot over (χ)} could typically be: [0083] Filtering the static and quasi-static motion (which will typically be low frequency wind-induced motion). This could be achieved with a second order Butterworth high-pass filter with Laplace transform:

[00006]$\begin{array}{cc}{h}_{\text{?}}\left(s\right)=\frac{s^2}{s^2+\sqrt{2}{\omega }_{\text{?}}s+{\omega }_{\text{?}}^2}.& \left(1\right)\end{array}$$\text{?}\text{indicates text missing or illegible when filed}$ [0084] where h.sub.fa is the Laplace transform function, ω.sub.fa is the high pass filter frequency in rad/s and s is the Laplace variable. [0085] Filtering of the 3P frequency corresponding to the blade passing frequency of a three-bladed wind turbine (2P frequency for a two-bladed wind turbine). This could be achieved with a second order notch filter of the form:

[00007]$\begin{array}{cc}{h}_{\mathrm{fb}}\left(s\right)=\frac{\text{?}+2{\zeta }_n{\omega }_{\mathrm{fb}}s+\text{?}}{s^2+2{\zeta }_d{\omega }_{\mathrm{fb}}s+{\omega }_{\mathrm{fb}}^2}\text{?}& \left(4\right)\end{array}$$\text{?}\text{indicates text missing or illegible when filed}$ [0086] where h.sub.fb is the Laplace transform function and s is the Laplace variable. ω.sub.fb is the notch filter frequency in rad/s and ζ.sub.n and ζ.sub.d are the relative damping in the nominator and denominator, respectively. [0087] Conventional low-pass filtering (with a sufficiently high filter frequency) of possible high frequency noise/response could be required, for example by using a second order Butterworth low-pass filter.

[0088] Motion sensors (not shown) are provided on the wind turbine 1 to measure the position χ and the velocity {dot over (χ)}. These sensors are advantageously located near or at the water line 8 (e.g. as opposed to being closer to/at the nacelle 4) in order to better capture wave-induced motion and less wind-induced noise such as the blade passing frequency effect. The platform deck (not shown) of an offshore wind turbine 1 could be a practical and advantageous location for such motion sensors.

[0089] Such selection of sensor location may then advantageously not require filtering of the 3P (or 2P) frequency, and one possible controlled configuration from equation (1) could be:

χ.sub.f1(s)=h.sub.fa(s)χ(s)  (5)

{dot over (χ)}.sub.f2(s)={dot over (χ)}(s),  (6)

where the high-pass filter frequency of h.sub.fa(s) could be selected as, for example:

[00008]$\text{?}=\frac{2\pi }{80}\mathrm{rad}/s.$$\text{?}\text{indicates text missing or illegible when filed}$

[0090] FIG. 4 is a graph of simulated data showing tower displacement plotted against time for an unfiltered signal χ (blue, upper line) and a filtered signal χ.sub.f1 (red, lower line). The unfiltered signal contains wave frequency excitation as well as static and quasi-static wind frequency excitation. The filtered signal is based on equation (5) above with

[00009]$\text{?}=\frac{2\pi }{80}\mathrm{rad}/s.$$\text{?}\text{indicates text missing or illegible when filed}$

[0091] As can be seen, the filtered signal shows an average displacement centred around zero whereas the unfiltered signal shows a displacement increasing with time.

[0092] The blade pitch controller 20 has a significantly simpler implementation compared to the prior art controller 10 of FIG. 2, whilst providing very similar results.

[0093] The table below presents a lifetime comparison of a “Basic” controller (i.e. the nominal control system 11) with the blade pitch controller 10 of FIG. 2 (labelled as “Advanced” in the table) and the blade pitch controller 20 of the present invention and shown in FIG. 3 (labelled as “Simplified” in the table). Eleven different controller performance comparison parameters are compared.

[0094] All performance comparison parameters show that the simplified controller (blade pitch controller 20 of the present invention) yields similar performance as the advanced controller (prior art blade pitch controller 10 of FIG. 2). The results shaded in blue (the first five results columns) are desirable effects of tower feedback control. The results shaded in red (the sixth, seventh, and ninth result columns) are undesirable effects of tower feedback control.

[0095] The controller performance comparison parameters that are assessed are defined as follows:

TABLE-US-00001 Performance Desired Component parameter Description trend Support D.sub.Max.sup.20 Maximum fatigue damage ⬇ structure D.sub.FA.sup.20 Fore-aft fatigue damage ⬇ D.sub.SS.sup.20 Side-side fatigue damage ⬇ Blade DEL.sub.Edge.sup.20 Edgewise equivalent fatigue ⬇ roots load DEL.sub.F Flapwise equivalent fatigue ⬇ load Pitch DEL .sup.20 Equivalent fatigue load in ⬇ actuators bearing ADC .sup.0 Actuator duty cycle ⬇ Drive- DEL.sub.Gear.sup.20 Equivalent fatigue load in ⬇ train gearing DEL.sub.Shaft.sup.20 Equivalent fatigue load in the ⬇ main shaft Generator P .sup.0 Lifetime energy yield ⬆ IAE .sup.20 Intergrated absolute generator ⬇ speed error indicates data missing or illegible when filed

[0096] FIG. 5 presents a lifetime comparison of the accumulation of fatigue damage in the wind turbine foundation with the blade pitch controller 20 of the present invention (labelled as “Proposed simplified controller) compared with the prior art blade pitch controller 10 of FIG. 2 (labelled as “Advanced controller”) and the nominal control system 11 (labelled as “Basic control w/o [without] load reduction”). As can been seen, the blade pitch controller 20 of the present invention provides similar performance in terms of fatigue reduction as the prior art blade pitch controller 10 of FIG. 2.

[0097] The results of a simulation illustrating the effectiveness of the blade pitch controller 20 of the present invention compared to conventional damping control are presented in FIGS. 6a-d. In these graphs, the black line represents the blade pitch controller 20 of the present invention (labelled as “Proposed damping+stiffness controller), the blue line represents a prior art conventional damping controller (labelled as “Conventional damping controller”), and the red line represents using just the nominal control system 11 (labelled as “Basic controller w/o [without] load reduction”).

[0098] FIG. 6(a) is a plot of power density measured in m.sup.2/Hz as a function of frequency, showing power spectral density of the tower top displacement.

[0099] FIG. 6(b) is a plot of power density measured in deg.sup.2/Hz as a function of frequency, showing power spectral density of the blades' pitch angle.

[0100] FIG. 6(c) is a plot of tower top displacement as a function of time.

[0101] FIG. 6(d) is a plot of the blades' collective pitch angle as a function of time.

[0102] From these plots, it can be seen that both tower motion and the blades' pitch activity are significantly increased in a frequency range around 0.1 Hz with the prior art conventional damping controller. However, the blade pitch controller 20 of the present invention (proposed damping+stiffness controller) eliminates this undesirable behaviour.

[0103] The blade pitch controller 20 of the present invention (proposed damping+stiffness controller) could also provide additional stiffness for excitation mechanisms other than waves, if their excitation frequency is above the selected high pass filter frequency and within the bandwidth of the blade pitch actuator (and outside the notch filter frequency area if this is applied).

REFERENCES

[0104] 1. Van der Hooft E, Schaak P, Van Engelen T. Wind turbine control algorithms. DOWEC project-DOWEC-F1W1-EH-03-094/0, Task-3 report 2003. (Van der Hooft, 2003) [0105] 2. Bossanyi E. Wind turbine control for load reduction. Wind Energy 2003; 6(3):229-244. (Bossanyi, 2003) [0106] 3. Smilden E, Bachynski E E, Sorensen A J, Amdahl J. Wave disturbance rejection for monopile offshore wind turbines. Wind Energy 2018. https://doi.org/10.1002/we.2273. (Smilden, 2018).