Feedback-feedforward individual pitch control design for wind turbines with uncertain measurements

Ungurán, Róbert; Petrović, Vlaho; Boersma, Sjoerd; Wingerden, Jan‐Willem van; Pao, Lucy Y.; Kühn, Martin

doi:10.23919/acc.2019.8814757

Cited by 16 publications

(22 citation statements)

References 17 publications

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“…However, we would like to emphasize the presence of uncertainties in all three components, as the result of the wind evolution, the simplicity of the induction zone correction, "cyclops dilemma", and using only a single-point measurement for the estimation of the blade effective wind speed at assumed zero value of v h,i and w h,i components (see Section 2.1), etc. Therefore, it is important to consider the uncertainties in the controller development; e.g., uncertainty at the yaw and tilt components was already approximately 150 % at 0.195 Hz (1P frequency), which could have affected the performance of the controller, i.e., it can lead to increased values of the sensitivity function, causing load increase on the non-rotating components of the wind turbine, as was asserted by Ungurán et al (2019).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the question as to whether robust stability and performance can be ensured with such a high uncertainty still remains, i.e., Ungurán et al (2019) assumed only 300 % of high-frequency uncertainties on the yaw and tilt components. To avoid such a peak, the telescopes need to be well aligned with each other and the blade segment orientation angles and linear velocities should be measured well.…”

Section: Discussionmentioning

confidence: 99%

“…The uncertainty weight found in Section 3.3.2 might cover these cases, and may serve helpful in the control development rather than that found in the no-induction case in Section 3.3.1. Nevertheless, this may further reduce the gains of the feedforward controller (see Ungurán et al (2019)) with respect to the controller developed by using the uncertainty weight found for the no-induction case, thus limiting the benefits of the lidar system.…”

Section: Discussionmentioning

confidence: 99%

“…(1) Only one objective was introduced in Equation 10; nevertheless, other objectives can be added, such as penalizing the control signal magnitude at high frequencies (Ungurán et al (2019) as a scaling factor of the objective function, as in Figure 5 was extended with the inverse of the disturbance model (G −1 d,f ) (shown in a dashed rectangle), so that…”

Section: Gwtfmentioning

confidence: 99%

“…Such a feature of the system enables addressing the mitigation of higher harmonic dynamic blade loads through feedbackfeedforward individual pitch and trailing edge flap controllers (Ungurán et al (2018(Ungurán et al ( , 2019), while simultaneously posing challenges with the presence of the induction zone. The closer the lidar measurement is taken to the rotor plane, the higher the deficit between the measured inflow and free flow wind speeds.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainties identification of the blade-mounted lidar-based inflow wind speed measurements for robust feedback-feedforward control synthesis

Ungurán¹,

Petrović²,

Pao³

et al. 2019

Preprint

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Abstract. The current trend toward larger wind turbine rotors leads to high periodic loads across the components due to the non-uniformity of inflow across the rotor. On this regard, we introduce a blade-mounted lidar on each blade to provide a preview of inflow wind speed that can be used as a feedforward control input for the mitigation of such periodic blade loads. We present a method to easily determine blade-mounted lidar parameters, such as focus distance, telescope position, and orientation on the blade. However, such method is accompanied by uncertainties in the inflow wind speed measurement, which may also be due to the induction zone, wind evolution, cyclops dilemma, unidentified misalignment in the telescope orientation, and the blade segment orientation sensor. Identification of these uncertainties allows their inclusion in the feedback-feedforward controller development for load mitigation. We perform large-eddy simulations, in which we simulate the blade-mounted lidar including the dynamic behaviour and the induction zone of one reference wind turbine for one above rated inflow wind speed. Our calculation approach provides a good trade-off between a fast-and-simple determination of the telescope parameters and an accurate inflow wind speed measurement. We identify and model the uncertainties, which then can directly be included in the feedback-feedforward controller design and analysis. The rotor induction effect increases the preview time, which needs to be considered in the controller development and implementation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Gwtfmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainties identification of the blade-mounted lidar-based inflow wind speed measurements for robust feedback-feedforward control synthesis

Ungurán¹,

Petrović²,

Pao³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

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Analysis and optimal individual pitch control decoupling by inclusion of an azimuth offset in the multiblade coordinate transformation

et al. 2018

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With the trend of increasing wind turbine rotor diameters, the mitigation of blade fatigue loadings is of special interest to extend the turbine lifetime. Fatigue load reductions can be partly accomplished using individual pitch control (IPC) facilitated by the so‐called multiblade coordinate (MBC) transformation. This operation transforms and decouples the blade load signals in a yaw‐axis and tilt‐axis. However, in practical scenarios, the resulting transformed system still shows coupling between the axes, posing a need for more advanced multiple input multiple output (MIMO) control architectures. This paper presents a novel analysis and design framework for decoupling of the nonrotating axes by the inclusion of an azimuth offset in the reverse MBC transformation, enabling the application of simple single‐input single‐output (SISO) controllers. A thorough analysis is given by including the azimuth offset in a frequency‐domain representation. The result is evaluated on simplified blade models, as well as linearizations obtained from the NREL 5–MW reference wind turbine. A sensitivity and decoupling assessment justify the application of decentralized SISO control loops for IPC. Furthermore, closed‐loop high‐fidelity simulations show beneficial effects on pitch actuation and blade fatigue load reductions.

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Lidar‐based feedforward control design methodology for tower load alleviation in wind turbines

et al. 2022

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Summary Minimising tower loads is a key issue for the optimal operation and cost‐effective design of wind turbines. Light detection and ranging (LIDAR) technologies enable the measurement of free wind ahead of the rotor and the addition of new feedforward controllers to the traditional control loops, improving the performance in terms of generator speed regulation and load reduction. This paper presents a design procedure based on plant inversion at a set of key frequencies. Tower base longitudinal bending moment is considered the main output of the system. Although the minimisation of tower base loads is the main objective of the design, good results are obtained in terms of generator speed regulation and pitch actuation as well. The methodology has been tested in the well‐known NREL 5MW wind turbine. Results have been obtained for different LIDAR configurations in order to quantify the loss of performance due to measurement errors. In all cases, the feedforward control behaves better than the baseline case.

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Feedback-feedforward individual pitch control design for wind turbines with uncertain measurements

Cited by 16 publications

References 17 publications

Uncertainties identification of the blade-mounted lidar-based inflow wind speed measurements for robust feedback-feedforward control synthesis

Uncertainties identification of the blade-mounted lidar-based inflow wind speed measurements for robust feedback-feedforward control synthesis

Analysis and optimal individual pitch control decoupling by inclusion of an azimuth offset in the multiblade coordinate transformation

Lidar‐based feedforward control design methodology for tower load alleviation in wind turbines

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