Using Multiple Fidelity Numerical Models for Floating Offshore Wind Turbine Advanced Control Design

Olondriz, Joannes; Yu, Wei; Jugo, J.; Lemmer, Frank; Elorza, Iker; Alonso‐Quesada, S.; Pujana-Arrese, Aron

doi:10.3390/en11092484

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Olondriz et al used a floater platform motion feedback control (PMFC) strategy to improve the pitch motion of the platform of the floater, generator speed, and blade and tower loads using a model based on the National Renewable Energy Laboratory (NREL) 5-MW ITI energy barge [3]. In addition, PMFC was applied to a linear model of a DTU 10-MW FOWT model to improve the power quality and reduce the pitch motion of the platform [4]. In addition, for automatic improvement in the conventional feedback control loop, a new optimization method was proposed based on the Monte Carlo method, which retained the overall performance level of the wind turbine while reducing the mechanical fatigue load of the components [5].…”

Section: Introductionmentioning

confidence: 99%

Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine

Kim

et al. 2021

Energies

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In this study, a resonance avoidance control algorithm was designed to address the tower resonance problem of a semi-submersible floating offshore wind turbine (FOWT) and the dynamic performance of the wind turbine, floater platform, and mooring lines at two exclusion zone ranges were evaluated. The simulations were performed using Bladed, a commercial software for wind turbine analysis. The length of simulation for the analysis of the dynamic response of the six degrees of freedom (DoF) motion of the floater platform under a specific load case was 3600 s. The simulation results are presented in terms of the time domain, frequency domain, and using statistical analysis. As a result of applying the resonance avoidance control algorithm, when the exclusion zone range was ±0.5 rpm from the resonance rpm, the overall performance of the wind turbine was negatively affected, and when the range was sufficiently wide at ±1 rpm, the mean power was reduced by 0.04%, and the damage equivalent load of the tower base side–side bending moment was reduced by 14.02%. The tower resonance problem of the FOWT caused by practical limitations in design and cost issues can be resolved by changing the torque control algorithm.

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Section: Introductionmentioning

confidence: 99%

Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine

Kim

et al. 2021

Energies

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“…If the first loop manages to increase the damping such that the fore‐aft damping is sufficiently high, the fore‐aft dynamics will not be critical anymore, and the dynamics will not be critical disappear. Two independent control loops have been considered in different publications . The control design procedure of closing one loop at a time is called decentralized control, p443 or “multi SISO‐control” .…”

Section: Introductionmentioning

confidence: 99%

Robust gain scheduling baseline controller for floating offshore wind turbines

Lemmer

Schlipf

et al. 2019

Wind Energy

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The possibility of a pitch instability for floating wind turbines, due to the blade‐pitch controller, has been discussed extensively in recent years. Contrary to many advanced multi‐input‐multi‐output controllers that have been proposed, this paper aims at a standard proportional‐integral type, only feeding back the rotor speed error. The advantage of this controller is its standard layout, equal to onshore turbines, and the clearly defined model‐based control design procedure, which can be fully automated. It is more robust than most advanced controllers because it does not require additional signals of the floating platform, which make controllers often sensitive to unmodeled dynamics. For the design of this controller, a tailored linearized coupled dynamic model of reduced order is used with a detailed representation of the hydrodynamic viscous drag. The stability margin is the main design criterion at each wind speed. This results in a gain scheduling function, which looks fundamentally different than the one of onshore turbines. The model‐based controller design process has been automated, dependent only on a given stability margin. In spite of the simple structure, the results show that the controller performance satisfies common design requirements of wind turbines, which is confirmed by a model of higher fidelity than the controller design model. The controller performance is compared against an advanced controller and the fixed‐bottom version of the same turbine, indicating clearly the different challenges of floating wind control and possible remedies.

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Stability and Reliability Analysis for Multiple WT Using Deep Reinforcement Learning

Padmaja¹,

Kumar²,

Dhanesh³

et al. 2023

Electric Power Components and Systems

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Using Multiple Fidelity Numerical Models for Floating Offshore Wind Turbine Advanced Control Design

Cited by 4 publications

References 12 publications

Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine

Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine

Robust gain scheduling baseline controller for floating offshore wind turbines

Stability and Reliability Analysis for Multiple WT Using Deep Reinforcement Learning

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