TurbSim User's Guide

Jonkman, Bonnie; Buhl, M. L.

doi:10.2172/891594

Cited by 240 publications

(169 citation statements)

References 14 publications

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“…The high-fidelity turbine model is of much greater complexity than the model (25) employed in the estimator and with the exception of the yaw axis, all degrees-of-freedom were enabled, including flap-wise and edge-wise blade modes, in addition to the tower and shaft dynamics. Simulations in this study were conducted under a turbulent wind field with a mean wind speed 18 ms −1 and turbulence intensity of 16%, generated from TurbSim [21], chosen since this value is near the centre of the range of wind speeds covering above-rated wind conditions.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

Analysis and design of a tower motion estimator for wind turbines

Lio

Jones

Rossiter

2016

2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

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Abstract-The use of blade individual pitch control (IPC) provides a means of alleviating the harmful turbine loads that arise from the uneven and unsteady forcing from the oncoming wind. Such IPC algorithms, which mainly target the blade loads at specific frequencies, are designed to avoid excitations of other turbine dynamics such as the tower. Nonetheless, these blade and tower interactions can be exploited to estimate the tower movement from the blade load sensors. As a consequence, the aim of this paper is to analyse the observability properties of the blade and tower model and based on these insights, an estimator design is proposed to reconstruct the tower motion from the measurements of the flap-wise blade loads, that are typically available to the IPC. The proposed estimation strategy offers many immediate benefits, for example, the estimator obviates the need for hardware sensor redundancy, and the estimated signals can be used for control or fault monitoring purposes. We further show results obtained from high-fidelity turbine simulations to demonstrate the performance of the proposed estimator.

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Section: Numerical Results and Discussionmentioning

confidence: 99%

Analysis and design of a tower motion estimator for wind turbines

Lio

Jones

Rossiter

2016

2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

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“…The 350 seconds of warm up and transient response contains 50 seconds controller warm up and 150 seconds of constant wind, and were removed from the results before post processing. 64-bit TurbSim [22] was used to simulate the 3-hour turbulent wind field. Turbulence was generated applying the Kaimal spectrum and the IEC normal turbulence model [23] with a reference turbulence intensity of 0.12.…”

Section: Simulation Length Wind and Wave Loadsmentioning

confidence: 99%

Time domain analysis procedures for fatigue assessment of a semi-submersible wind turbine

Kvittem

Moan

2015

Marine Structures

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Long term time domain analysis of the nominal stress for fatigue assessment of the tower and platform members of a three-column semisubmersible was performed by fully coupled time domain analyses in SimoRiflex-AeroDyn. By combining the nominal stress ranges with stress concentration factors, hot spot stresses for fatigue damage calculation can be obtained. The aim of the study was to investigate the necessary simulation duration, number of random realisations and bin sizes for the discretisation of the joint wind and wave distribution. A total of 2316 3-hour time domain simulations, were performed.In mild sea states with wind speeds between 7 and 9 m/s, the tower and pontoon experienced high fatigue damage due to resonance in the first bending frequency of the tower from the tower wake blade passing frequency (3P).Important fatigue effects seemed to be captured by 1 hour simulations, and the sensitivity to number of random realisations was low when running simulations of more than one hour. Fatigue damage for the tower base converged faster with simulation duration and number of random realisations than it did for the platform members.Bin sizes of 2 m/s for wind, 1 s for wave periods and 1 m for wave heights seemed to give acceptable estimates of total fatigue damage. It is, however, important that wind speeds that give coinciding 3P and tower resonance are included and that wave periods that give the largest pitch motion are included in the analysis.

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“…The simulation validation platform includes the dynamical model of a 10-kW direct-drive WTG developed in a combined environment of FAST (Fatigue, Aerodynamics, Structures, and Turbulence) [34], TurbSim [35], and Simulink, as illustrated in Fig. 4.1, where TurbSim generates the wind data; FAST simulates the dynamics of the wind turbine; and Simulink simulates the dynamics of the generator and other electrical components of the WTG system.…”

Section: Simulation Validation Platformmentioning

confidence: 99%

“…TurbSim, which is a stochastic, full-field, turbulent wind simulator developed by the National Renewable Energy Laboratory (NREL) [35], was used in the simulation study to produce wind velocity vectors in a time series across the entire rotating plane of the wind turbine's rotor. An average wind speed of 12 m/s was chosen in the simulation study.…”

Section: Wind Speed Datamentioning

confidence: 99%

Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

Wang¹

2012

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TurbSim User's Guide

Cited by 240 publications

References 14 publications

Analysis and design of a tower motion estimator for wind turbines

Analysis and design of a tower motion estimator for wind turbines

Time domain analysis procedures for fatigue assessment of a semi-submersible wind turbine

Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

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