LPV Control of Wind Turbines for Fatigue Loads Reduction using Intelligent Micro Sensors

Lescher, Fabien; Camblong, Haritza; Curea, Octavian; Briand, Renaud

doi:10.1109/acc.2007.4282790

Cited by 25 publications

(25 citation statements)

References 9 publications

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“…The performance for especially the fatigue damage is difficult to evaluate directly from the energy gain as discussed in [13], and the damage on tower and drive train is evaluated from rain-flow count [33]. Finally, the damage due to pitch activity is mostly on the blade bearings for which the damage can be approximated by the standard deviation of the pitch rate [33].…”

Section: Simulation Set-upmentioning

confidence: 99%

“…For this variable, only X and Y are directly available. In [30] it is suggested to calculate as in (13). Construction of the state-space controller in (8b) can then be described in Algorithm 2…”

Section: Controller Constructionmentioning

confidence: 99%

“…Then X cl can be constructed using (13), and the controller matrices in K can then be determined by Algorithm 2 with variables as in (12). In practice, the solution is unfortunately not that simple because numerical issues might make the controller construction impossible if no extra measures are taken.…”

Section: Numerical Conditioning Of An Lpv Controller Designmentioning

confidence: 99%

“…Mainly because the performance criteria are very different in partial load when compared with full load control, but also because it is rather crude to approximate the nonlinear aerodynamics by a first-order function over the entire operating region. In [13,14] this is handled by designing different LPV controllers for the below-and above-rated wind speeds and then switching between them.…”

mentioning

confidence: 99%

“…In [13][14][15] the LPV design procedure is applied for the special case of affine parameter dependency. However, affine parameter dependency is a very strict requirement for designing controllers for wind turbines in the entire operating region.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Linear parameter varying control of wind turbines covering both partial load and full load conditions

Østergaard

Stoustrup

Brath

2008

Intl J Robust & Nonlinear

115

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SUMMARYThis paper considers the design of linear parameter varying (LPV) controllers for wind turbines in order to obtain a multivariable control law that covers the entire nominal operating trajectory.The paper first presents a controller structure for selecting a proper operating trajectory as a function of estimated wind speed. The dynamic control law is based on LPV controller synthesis with general parameter dependency by gridding the parameter space.The controller construction can, for medium-to large-scale systems, be difficult from a numerical point of view, because the involved matrix operations tend to be ill-conditioned. The paper proposes a controller construction algorithm together with various remedies for improving the numerical conditioning the algorithm.The proposed algorithm is applied to the design of a LPV controller for wind turbines, and a comparison is made with a controller designed using classical techniques to conclude that an improvement in performance is obtained for the entire operating envelope.

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Section: Simulation Set-upmentioning

confidence: 99%

Section: Controller Constructionmentioning

confidence: 99%

Section: Numerical Conditioning Of An Lpv Controller Designmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Linear parameter varying control of wind turbines covering both partial load and full load conditions

Østergaard

Stoustrup

Brath

2008

Intl J Robust & Nonlinear

115

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show abstract

Multicomponent and Multimaterials Printing

Terrazas

Hossain

Lin

et al. 2021

3D Printing for Energy Applications

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Feedback–feedforward individual pitch control for wind turbine load reduction

Engelen¹,

Kanev

Selvam

et al. 2008

Intl J Robust & Nonlinear

204

164

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SUMMARYThis paper focuses on the problem of wind turbine fatigue load reduction by means of individual pitch control (IPC). The control approach has a two-degree-of-freedom structure, consisting of an optimal multivariable LQG controller and a feedforward disturbance rejection controller based on estimated wind speed signals. To make the control design problem time invariant, all signals are transformed to the non-rotating reference frame using the Coleman transformation. In the Coleman domain, the LQG control objective is minimization of the rotor tilt and yaw moments, whereas the feedforward controller tries to achieve even further improvement by rejecting the influence of the low-frequency components of the wind on the rotor moments. To this end, the tilt-and yaw-oriented components of the blade-effective wind speeds are approximated using stochastic random walk models, the states of which are then augmented with the turbine states and estimated using a Kalman filter. The effects of these (estimated) disturbances on the controlled outputs are then reduced using stable dynamic model inversion. The approach is tested and compared with the conventional IPC method in simulation studies with models of different complexities. The results demonstrate very good load reduction at not only low frequencies (1p blade fatigue load reduction) but also at the 3p frequency, giving rise to fatigue load reduction of the non-rotating turbine components.

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LPV Control of Wind Turbines for Fatigue Loads Reduction using Intelligent Micro Sensors

Cited by 25 publications

References 9 publications

Linear parameter varying control of wind turbines covering both partial load and full load conditions

Linear parameter varying control of wind turbines covering both partial load and full load conditions

Multicomponent and Multimaterials Printing

Feedback–feedforward individual pitch control for wind turbine load reduction

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