Turbsim User's Guide: Version 1.50

Jonkman, Bonnie

doi:10.2172/965520

Cited by 507 publications

(465 citation statements)

References 17 publications

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“…9 The coherence parameters a l and b l are based on field measurements and are a u = 9.513, a As mentioned in the previous section, the coherence between the u and v, u and w, as well as v and w components of wind speed is non-zero for the wind field used in this paper. The average Reynolds stress 9 u w for this wind field, where u = u −ū and w = w −w, is -0.281 at hub height, which results in non-zero uw coherence functions.…”

Section: A the Great Plains-low Level Jet Wind Fieldmentioning

confidence: 99%

LIDAR Wind Speed Measurements of Evolving Wind Fields

Simley¹,

Pao²

2012

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Light Detection and Ranging (LIDAR) systems are able to measure the speed of incoming wind before it interacts with a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. Past studies have assumed Taylor's frozen turbulence hypothesis, which implies that turbulence remains unchanged as it advects downwind at the mean wind speed. With Taylor's hypothesis applied, the only source of wind speed measurement error is distortion caused by the LIDAR. This study introduces wind evolution, characterized by the longitudinal coherence of the wind, to LIDAR measurement simulations to create a more realistic measurement model. A simple model of wind evolution is applied to a frozen wind field used in previous studies to investigate the effects of varying the intensity of wind evolution. Simulation results show the combined effects of LIDAR errors and wind evolution for realistic turbine-mounted LIDAR measurement scenarios.Nomenclature a decay parameter for exponential coherence a l decrement parameter for transverse coherence (l ∈ {u, v, w}) b l offset parameter for transverse coherence (l ∈ {u, v, w}) D longitudinal distance between two points or measurement preview distance F focal distance f frequency (Hz) θ LIDAR measurement angle off of longitudinal direction k wind velocity wavenumber (m −1 ) λ wavelength (m) R range along LIDAR beam r scan radius for spinning LIDAR scenario r i,j distance between two points in the yz plane U mean wind speed (m/s) u i,j average mean wind speed between two points in the yz plane ψ azimuth angle in the rotor plane γ 2 xy (f ) Coherence between signals x and y

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Section: A the Great Plains-low Level Jet Wind Fieldmentioning

confidence: 99%

LIDAR Wind Speed Measurements of Evolving Wind Fields

Simley¹,

Pao²

2012

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“…Simulations are done with realistic turbulent wind speed using the Kaimal turbulence model [25]. TurbSim [26] is used to generate a time marching hub-height wind profile. In order to stay in the full load region, a realization of turbulent wind speed is used from category C of the turbulence categories of the IEC 61400-1 [25], with 18m/s as the mean wind speed.…”

Section: Simulationsmentioning

confidence: 99%

Robust model predictive control of a wind turbine

Mirzaei

Poulsen

Niemann

2012

2012 American Control Conference (ACC)

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Abstract-In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition, a new sensor is introduced in the EKF to give faster estimations. Wind speed estimation error is used to assess uncertainties in the linearized model. Significant uncertainties are considered to be in the gain of the system (B matrix of the state space model). Therefore this special structure of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally simulation results are presented. First a comparison between PI and robust MPC is given. Afterwards simulations are done for a realization of turbulent wind with uniform profile based on the IEC standard.

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“…The aeroelastic simulations are performed with the simulation software FAST [24]. The wind fields are generated with TurbSim [25] on a 31 × 31 square grid with 145 m width, which is centered at the hub height of the wind turbine model. Detailed turbulence data at FINO 1 were not available in the present study, therefore the Kaimal turbulence spectrum is used.…”

Section: Simulationsmentioning

confidence: 99%

Investigation of Site-Specific Wind Field Parameters and Their Effect on Loads of Offshore Wind Turbines

Ernst

Seume

2012

Energies

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Abstract:The main contributing factors to unsteady loading of Offshore Wind Turbines (OWT) are wind shear, turbulence, and waves. In the present paper, the turbulence intensity and the wind shear exponent are investigated. Using data from the FINO 1 research platform, these parameters are analyzed and compared with the proposed wind field parameters in the IEC standard 61400-3. Based on this analysis, aeroelastic simulations are performed to determine the effect of wind field parameters on the fatigue and the extreme loads on the rotor blades. For the investigations, the aeroelastic model of a 5 MW OWT is used with a focus on design load cases in an operating state (power production). The fatigue loads are examined by means of the damage-equivalent load-range approach. In order to determine the extreme loads with a recurrence period of 50 years, a peak over threshold extrapolation method and a novel method based on average conditional exceedance rates are used. The results show that the requirements of the IEC standard are very conservative for the design of the rotor blades. Therefore, there could be a large optimization potential for the reduction of weight and cost of the rotor blades.

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Turbsim User's Guide: Version 1.50

Cited by 507 publications

References 17 publications

LIDAR Wind Speed Measurements of Evolving Wind Fields

LIDAR Wind Speed Measurements of Evolving Wind Fields

Robust model predictive control of a wind turbine

Investigation of Site-Specific Wind Field Parameters and Their Effect on Loads of Offshore Wind Turbines

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