Control of floating wind turbines

Veen, G.J. van der; Couchman, Ian; Bowyer, Robert

doi:10.1109/acc.2012.6315120

Cited by 50 publications

(24 citation statements)

References 7 publications

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“…The controller pitches the blades, due to a change of the relative wind speed seen by the rotor, originated from a fore-aft oscillation of the platform. This pitching reduces the thrust and can eventually yield a fore-aft system instability as shown by [2][3][4], among others. The effect was experimentally shown for the semi-submersible FOWT concept of this work in [5].…”

Section: Coupled Aero-hydro-servo-elastic Dynamicsmentioning

confidence: 97%

Iterative Frequency-Domain Response of Floating Offshore Wind Turbines with Parametric Drag

Lemmer¹,

Yu²,

Cheng³

2018

JMSE

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Methods for coupled aero-hydro-servo-elastic time-domain simulations of Floating Offshore Wind Turbines (FOWTs) have been successfully developed. One of the present challenges is a realistic approximation of the viscous drag of the wetted members of the floating platform. This paper presents a method for an iterative response calculation with a reduced-order frequency-domain model. It has heave plate drag coefficients, which are parameterized functions of literature data. The reduced-order model does not represent more than the most relevant effects on the FOWT system dynamics. It includes first-order and second-order wave forces, coupled with the wind turbine structural dynamics, aerodynamics and control system dynamics. So far, the viscous drag coefficients are usually defined as constants, independent of the load cases. With the computationally efficient frequency-domain model, it is possible to iterate the drag, such that it fits to the obtained amplitudes of oscillation of the different members. The results show that the drag coefficients vary significantly across operational load conditions. The viscous drag coefficients converge quickly and the method is applicable for concept-level design studies of FOWTs with load case-dependent drag.

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Section: Coupled Aero-hydro-servo-elastic Dynamicsmentioning

confidence: 97%

Iterative Frequency-Domain Response of Floating Offshore Wind Turbines with Parametric Drag

Lemmer¹,

Yu²,

Cheng³

2018

JMSE

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“…This is due to a decrease in rotor thrust at constant rotor speed as the wind speed increases. This can then lead directly to tower fore-aft oscillation, hence, decreased tower axial fatigue life if not controlled, as illustrated in Figure 1 [4]. Fixed turbines can avoid the negative damping effect without a loss in performance as the natural frequency of the blade pitch control system is lower than the first resonance modes of the tower.…”

Section: Introductionmentioning

confidence: 99%

“…Tower oscillation propagation in a pitch-to-feather horizontal axis wind turbine (HAWT) due to the negative damping cycle. Adapted from Reference[4] Reprinted with permission [van der Veen]; 2012, American Control Conference.…”

mentioning

confidence: 99%

Reducing Tower Fatigue through Blade Back Twist and Active Pitch-to-Stall Control Strategy for a Semi-Submersible Floating Offshore Wind Turbine

2019

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The necessity of producing more electricity from renewable sources has been driven predominantly by the need to prevent irreversible climate chance. Currently, industry is looking towards floating offshore wind turbine solutions to form part of their future renewable portfolio. However, wind turbine loads are often increased when mounted on a floating rather than fixed platform. Negative damping must also be avoided to prevent tower oscillations. By presenting a turbine actively pitching-to-stall, the impact on the tower fore–aft bending moment of a blade with back twist towards feather as it approaches the tip was explored, utilizing the time domain FAST v8 simulation tool. The turbine was coupled to a floating semisubmersible platform, as this type of floater suffers from increased fore–aft oscillations of the tower, and therefore could benefit from this alternative control approach. Correlation between the responses of the blade’s flapwise bending moment and the tower base’s fore–aft moment was observed with this back-twisted pitch-to-stall blade. Negative damping was also avoided by utilizing a pitch-to-stall control strategy. At 13 and 18 m/s mean turbulent winds, a 20% and 5.8% increase in the tower axial fatigue life was achieved, respectively. Overall, it was shown that the proposed approach seems to be effective in diminishing detrimental oscillations of the power output and in enhancing the tower axial fatigue life.

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“…New concepts have to be devised particularly for collective blade pitch control to regulate the rotor speed because of the known negative damping of the platform pitch motion at low frequencies introduced by the wind variations at these frequencies . Based on van der Veen et al (2012), there are mainly four possibilities to face this problem by feedback control: A straightforward approach is to lower the closed-loop bandwidth of the pitch controller under the platform pitch frequency as done by Jonkman (2007) and Larsen and Hanson (2007). The second possibility is to use acceleration measurements to damp the pitch motion (Lackner and Rotea, 2011).…”

Section: Introductionmentioning

confidence: 99%

Collective Pitch Feedforward Control of Floating Wind Turbines Using Lidar

Schlipf¹,

Simley²,

Lemmer³

et al. 2015

JOWE

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In this work a collective pitch feedforward controller for floating wind turbines is presented. The feedforward controller provides a pitch rate update to a conventional feedback controller based on a wind speed preview. The controller is designed similar to the one for onshore turbines, which has proven its capability to improve wind turbine control performance in field tests. In a first design step, perfect wind preview and a calm sea is assumed. Under these assumptions the feedforward controller is able to compensate almost perfectly the effect of changing wind speed to the rotor speed of a full nonlinear model over the entire full load region. In a second step, a nacelle-based lidar is simulated scanning the same wind field which is used also for the aero-hydro-servo-elastic simulation. With model-based wind field reconstruction methods, the rotor effective wind speed is estimated from the raw lidar data and is used in the feedforward controller after filtering out the uncorrelated frequencies. Simulation results show that even with a more realistic wind preview, the feedforward controller is able to significantly reduce rotor speed and power variations. Furthermore, structural loads on the tower, rotor shaft, and blades are decreased. A comparison to a theoretical investigation shows that the reduction in rotor speed regulation is close to the optimum.

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Control of floating wind turbines

Cited by 50 publications

References 7 publications

Iterative Frequency-Domain Response of Floating Offshore Wind Turbines with Parametric Drag

Iterative Frequency-Domain Response of Floating Offshore Wind Turbines with Parametric Drag

Reducing Tower Fatigue through Blade Back Twist and Active Pitch-to-Stall Control Strategy for a Semi-Submersible Floating Offshore Wind Turbine

Collective Pitch Feedforward Control of Floating Wind Turbines Using Lidar

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