Overview of the TurbSim Stochastic Inflow Turbulence Simulator: Version 1.10

Kelley, Neil; Jonkman, Bonnie

doi:10.2172/891590

Cited by 28 publications

(6 citation statements)

References 2 publications

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“…The NWTC measurement suite allows inflow mean conditions and turbulence to be quantified as well as local and layer stability. This high-resolution data set will be used to investigate atmospheric conditions when high turbine loads occur; to investigate links between turbulence and stability; to further validate the stochastic flow model TurbSim; 11 for comparison with remote sensing instrumentation, 16 and as test data for nacelle-mounted LIDAR turbine control techniques. 34 First data from the new 135-m tower in October and November 2011 show that wind conditions vary considerably depending on wind direction and atmospheric stability.…”

Section: Discussionmentioning

confidence: 99%

“…The stochastic wind field simulator TurbSim was created using lessons learned from San Gorgonio, LIST, and LLLJP to produce a desktop simulation of a realistic atmospheric boundary layer. 11 This tool generates a wind field with similar statistical properties to those seen during these studies and is designed to be interfaced to turbine aerostructural models to estimate structural loading. TurbSim can also be used to generate boundary conditions for computational fluid dynamics calculations.…”

Section: Introductionmentioning

confidence: 99%

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Turbine Inflow Characterization at the National Wind Technology Center

Clifton

Schreck

Scott

et al. 2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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Utility-scale wind turbines operate in dynamic flows that can vary significantly over timescales from less than a second to several years. To better understand the inflow to utility-scale turbines, two inflow towers were installed and commissioned at the National Renewable Energy Laboratory's (NREL) National Wind Technology Center near Boulder, Colorado, in 2011. These towers are 135 m tall and instrumented with a combination of sonic anemometers, cup anemometers, wind vanes, and temperature measurements to characterize the inflow wind speed and direction, turbulence, stability and thermal strati fication to two utility-scale turbines. Herein, we present variations in mean and turbulent wind parameters with height, atmospheric stability, and as a function of wind direction that could be important for turbine operation as well as persistence of turbine wakes. Wind speed, turbulence intensity, and dissipation are all factors that affect turbine performance. Our results show that these all vary with height across the rotor disk, demonstrating the importance of measuring atmospheric conditions that influence wind turbine performance at multiple heights in the rotor disk, rather than relying on extrapolation from lower levels.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Turbine Inflow Characterization at the National Wind Technology Center

Clifton

Schreck

Scott

et al. 2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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“…A 10-min TurbSim-generated [25] wind file with a mean of 18 m/s and a power law exponent of 0.125 is used in the simulations to verify the proposed DAC-based IPC controllers' effectiveness. TurbSim uses the inverse Fourier transformation of a wind spectrum model to numerically simulate the time series of three component wind speed vectors.…”

Section: Simulation Environmentmentioning

confidence: 99%

Independent blade pitch controller design for a three-bladed turbine using disturbance accommodating control

Wang

Wright

Johnson

2016

2016 American Control Conference (ACC)

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“…A time varying wind field has been computed using TurbSim by NREL [21]. It outputs a wind speed matrix in the rotor plane for each time step, which is used as an input for the rotor model.…”

Section: System Under Consideration and Modellingmentioning

confidence: 99%

Wideband estimation of the drive torque of a wind turbine using LiDAR measure-ments, blade element momentum theory and Kalman filtering

Ell¹,

Stubbe²,

Turschner³

et al. 2015

REPQQJ

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In this paper a method to estimate the drive torques from Light Detection and Ranging (LiDAR) measurements is proposed. Knowledge of these values brings many advantages for turbine control and especially active damping of mechanical oscillations.Primarly a simplified method to calculate the aerodynamic torque from wind speed measurements of a nacelle based LiDARsystem will be presented which bases on blade element momentum theory (BEM). Comparisons of results of the original and a simplified computation method show small deviations in the relevant working range of a wind turbine. Additionally a Kalman Filter is used to estimate the drive torques of the wind turbine.The method is tested in simulation using a model of a doubly fed induction generator (DFIG) wind turbine including a gearbox. Simulation results show good performance of the estimation.

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Overview of the TurbSim Stochastic Inflow Turbulence Simulator: Version 1.10

Cited by 28 publications

References 2 publications

Turbine Inflow Characterization at the National Wind Technology Center

Turbine Inflow Characterization at the National Wind Technology Center

Independent blade pitch controller design for a three-bladed turbine using disturbance accommodating control

Wideband estimation of the drive torque of a wind turbine using LiDAR measure-ments, blade element momentum theory and Kalman filtering

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