Wind Speed Turbulence Research Articles

Seasonal effectiveness of a Korean traditional deciduous windbreak in reducing wind speed

Little is known about how the increased porosity of a deciduous windbreak, which results from loss of leaves, influences wind speed reduction. We hypothesized that, with loss of foliage, the wind speed reduction effectiveness of a deciduous windbreak decreases on near leeward side but not on further leeward side and that wind speed recovers faster in the full foliage season than in other seasons. During summer, autumn, and winter (full, medium, and non-foliage season, respectively), we observed wind speed and direction around a deciduous windbreak in a traditional Korean village on windward and near and further leeward sides (at -8H, 2H, and 6H; H = 20 m, a windbreak height). We used a linear mixed effects model to determine that the relative wind speed reduction at 2H significantly decreased from 83% to 48% (<TEX>$F_{2,111.97}=73.6$</TEX>, P < 0.0001) with the loss of foliage. However, the relative wind speed reduction at 6H significantly increased from 26% to 43% (<TEX>$F_{2,98.54}=18.5$</TEX>, P < 0.0001). Consequently, wind speed recovery rate between 2H and 6H in summer was two times higher than in autumn and ten times higher than in winter (<TEX>$F_{2,102.93}=223.1$</TEX>, P < 0.0001). These results indicate that deciduous windbreaks with full foliage seem to induce large turbulence and increase wind speed recovery rate on leeward side. Our study suggests that further research is needed to find the optimal foliage density of a deciduous windbreak for maximizing windbreak effectiveness regardless of seasonal foliage changes.

Damping Wind and Wave Loads on a Floating Wind Turbine

Offshore wind energy capitalizes on the higher and less turbulent wind speeds at sea. To enable deployment of wind turbines in deep-water locations, structures are being explored, where wind turbines are placed on a floating platform. This combined structure presents a new control problem, due to the partly unconstrained movement of the platform and ocean wave excitation. If this additional complexity is not dealt with properly, this may lead to a significant increase in the structural loads and, potentially, instability of the controlled system. In this paper, the wave excitation is investigated, and we show the influence that both wind speed, wave frequencies and misalignment between wind and waves have on the system dynamics. A new control model is derived that extends standard turbine models to include the hydrodynamics, additional platform degrees of freedom, the platform mooring system and tower side-side motion, including gyroscopic effects. The models support a model-based design that includes estimators for wind speed and wave frequency. The design is applied to a number of examples representing different wind and wave conditions and successfully demonstrates a reduction in the structural oscillations, while improving power performance.

A new turbulence model for offshore wind turbine standards

ABSTRACTCorrect turbulence intensity modeling is crucial for fatigue load estimation for wind turbine structural design. It is well known that the International Electrotechnical Commission 61400‐3 Normal Turbulence Model recommended for offshore wind turbine design is not representative of offshore wind conditions. A new model is urgently needed as offshore wind energy is rapidly developing worldwide. After evaluating the suitability of the Normal Turbulence Model at three sites in Asia, Europe and the USA, it is found that wind–wave interaction and stability correction should be taken into account in modeling the offshore turbulence intensity and wind speed relationship. Therefore, a new turbulence intensity model, which models wind–wave interaction with the Charnock equation and adjusts for the influence of atmospheric stability through empirical turbulence scaling functions for the unstable atmospheric boundary layer, was developed. The new model is physically based and is tested against observations from the three sites. It shows better performance than the Normal Turbulence Model and hence is recommended to replace the Normal Turbulence Model. For model application, only two parameters are required, which are defined herein to represent offshore sites with high, medium and low turbulence intensities. Copyright © 2013 John Wiley &amp; Sons, Ltd.

High‐frequency sampling and kernel estimation for continuous‐time moving average processes

Interest in continuous‐time processes has increased rapidly in recent years, largely because of high‐frequency data available in many applications. We develop a method for estimating the kernel function g of a second‐order stationary Lévy‐driven continuous‐time moving average (CMA) process Y based on observations of the discrete‐time process YΔ obtained by sampling Y at Δ, 2Δ, …, nΔ for small Δ. We approximate g by gΔ based on the Wold representation and prove its pointwise convergence to g as Δ → 0 for continuous‐time autoregressive moving average (CARMA) processes. Two non‐parametric estimators of gΔ, on the basis of the innovations algorithm and the Durbin–Levinson algorithm, are proposed to estimate g. For a Gaussian CARMA process, we give conditions on the sample size n and the grid spacing Δ(n) under which the innovations estimator is consistent and asymptotically normal as n → ∞. The estimators can be calculated from sampled observations of any CMA process, and simulations suggest that they perform well even outside the class of CARMA processes. We illustrate their performance for simulated data and apply them to the Brookhaven turbulent wind speed data. Finally, we extend results of Brockwell et al. (2012) for sampled CARMA processes to a much wider class of CMA processes.

Sensitivity of inflow boundary conditions on downstream wind and turbulence profiles through building obstacles using a CFD approach

This study investigates the sensitivity on inflow turbulence profiles for predicting the downstream wind velocity and turbulent kinetic energy profiles within the street arrays of urban environments. Computational fluid dynamics (CFD) techniques, and the realizable k–ε turbulence model are used to model the wind environment and the CFD model is validated by wind tunnel measurement. The results show that turbulence is internally generated by the upwind building obstacles. The shape and magnitude of downwind velocity and turbulence profiles are not greatly affected by different input turbulence profiles deviating from the baseline turbulence profile (within an envelope of ±50%) as the flow advances from the upstream to downstream regions within the building arrays. Various profiles of turbulent kinetic energy magnitude (within an envelope of ±50%) and with the same velocity profile are input as inlet boundary conditions to three different geometric settings, and also to an actual urban setting. Turbulent kinetic energy and wind speed ratios are obtained at different locations within the computational domain, and used as indicators for comparison and investigation. The study finds that even with a significant deviation (50%) in magnitude from the inflow turbulent kinetic energy profile, there is less than 15% difference in the wind speed and turbulent kinetic energy in the downwind region of the urban area.

Rotational Turbulent Wind Field Simulation of Wind Turbine

In order to accurately obtain the influence of rotational effect on fluctuating component of turbulent wind acted on wind turbine, rotational Fourier spectrum with considering rotational effect of rotor was deduced. Physical nature of the rotational Fourier spectrum embodied by coherence function and phase lag was indicated. Auto power spectral density and cross power spectral density of rotational Fourier spectrum with introducing phase lag were proposed. The spectrum matrix constructed by the module of rotational Fourier spectrum was decomposed with Cholesky's method, according to the spectrum representation method with introducing phase lag, the random turbulent wind speed field was generated by superposing a set of cosine functions. Finally, an example involving simulation of the longitudinal turbulent wind velocity time series of a 1.5 MW three-bladed pitch regulated wind turbine was investigated. The target spectrum and simulated spectrum were compared. The result shows that the proposed algorithm is more accurate to simulate the fluctuating wind velocity of rotational blade.

Observation of water and solute movement in a saline, bare soil, groundwater seepage area, Western Australia. Part 1: Movement of water in near-surface soils in summer

In order to elucidate the relationship between evaporation, salinisation, and annual water and salt balances in semi-arid and arid regions, hydrological and meteorological observations were undertaken over 3 years in a small, salinised, bare-soil, groundwater seepage area in Western Australia. This paper focuses on water behaviour near a bare saline soil surface during the dry summer. Analysis of observed data on soil vapour density using a vapour diffusion transfer model can account for the daily upward vapour flux from the soil surface that occurs in midsummer. The dry soil undergoes cycles of drying during the day, accompanied by salt crust formation and wetting during the night. In late summer, the same zones show a wetting trend owing to a marked atmospheric vapour invasion and condensation at night regardless of evaporation during daytime. The daily average vapour flux at the ground surface in mid- and late-summer, respectively, estimated through the vapour transfer model in the dry soil layer was ~0.35 and 0.03 mm/day. Comparison of vapour fluxes at the ground surface measured with a portable surface evaporimeter with modelled estimates of vapour transport in soil showed agreement of the proposed model to field results at low wind speed, but not at the higher wind speeds. This identifies the active role of turbulent surface wind speed on vapour transfer in the dry soil layer below the ground surface.

Optimal Intelligent Control for Wind Turbulence Rejection in WECS Using ANNs and Genetic Fuzzy Approach

One of the disadvantages in Connection of wind energy conversion systems (WECSs) to transmission networks is plentiful turbulence of wind speed. Therefore effects of this problem must be controlled. �owadays, pitch-controlled WECSs are increasingly used for variable speed and pitch wind turbines. Megawatt class wind turbines generally turn at variable speed in wind farm. Thus turbine operation must be controlled in order to maximize the conversion efficiency below rated power and reduce loading on the drive-train. Due to random and non-linear nature of the wind turbulence and the ability of Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) Artificialeuraletworks (A��s) in the modeling and control of this turbulence, in this study, widespread changes of wind have been perused using MLP and RBF artificial ��s. In addition in this study, a new genetic fuzzy system has been successfully applied to identify disturbance wind in turbine input. Thus output power has been regulated in optimal and nominal range by pitch angle regulation. Consequently, our proposed approaches have regulated output aerodynamic power and torque in the nominal range.

SCIDAR: an optical turbulence profiler for Dome A

AbstractThis paper introduces a plan to detect turbulence profiles at Dome A with a Single Star Scidar (SSS), to enhance our understanding of the characteristics of the site. The development of a portable monitor for profiling vertical atmospheric optical turbulence and wind speed is presented. By analyzing the spatial auto and cross-correlation functions of very short exposure images of single star scintillation patterns, the SSS can provide the vertical profiles of turbulence intensity C2n(h) and wind speed V(h). A SSS prototype is already operational at Ali in Tibet which will be improved in order to become fully robotic and adapted to extreme weather conditions that prevail at Dome A in Antarctica.

Modeling of atmospheric wind speed sequence using a lognormal continuous stochastic equation

In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350s and sampled at 20Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with β=1.68 close to the Kolmogorov value −5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function ζV(q) is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.

PDF models and synthetic model for the wind speed fluctuations based on the resolution of Langevin equation

Wind energy production is very sensitive to turbulent wind speed. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output, in particular when wind power variations on very short time scales, range at few seconds to 1h, are considered. In small grid as they exist on islands (Guadeloupean Archipelago: French West Indies) such fluctuations can cause instabilities in case of intermediate power shortages. The developed analysis in [14] reveals three main classes of time series for the wind speed fluctuations. In this work, Probability Density Functions (PDFs) are proposed to fit the wind speed fluctuations distributions in each class. After, to simulate wind speed fluctuations sequences, we use a stochastic differential equation, the Langevin equation considering Gaussian turbulence PDF (class I), Gram–Charlier PDF (class II) and a mixture of gaussian PDF (class III). The statistical and dynamical properties of simulated wind sequences are close to those of measured wind sequences, for each class.

Direct measurement of the spectral transfer function of a laser based anemometer

The effect of a continuous-wave (cw) laser based anemometer's probe volume on the measurement of wind turbulence is studied in this paper. Wind speed time series acquired by both a remote sensing cw laser anemometer, whose line-of-sight was aligned with the wind direction, and by a reference sensor (sonic anemometer) located in the same direction, were used. The spectral transfer function, which describes the attenuation of the power spectral density of the wind speed turbulence, was calculated and found to be in good agreement with the theoretical exponential function, which is based on the properties of the probe volume of a focused Gaussian laser beam. Parameters such as fluctuations of the wind direction, as well as the overestimation of the laser Doppler spectrum threshold, were found to affect the calculation of the spectral transfer function by introducing high frequency noise.

Comparison of an island wind turbine collective and individual pitch LQG controllers designed to alleviate fatigue loads

This study aims to analyse different linear quadratic Gaussian (LQG) controllers' performances in terms of reducing the fatigue load of wind turbines' (WT) most costly components caused by the spatial turbulence of wind speed. Five LQGs with increasing control model complexity and a greater number of objectives are designed, the first four with collective pitch control (CPC), and the fifth with individual pitch control (IPC). In the design of the controllers, firstly a linear control model is obtained in the operating point corresponding to a wind speed of 18 m/s. Then, the Kalman filter (KF) and the rest of the controller are tuned with simulations in order to obtain the lowest possible fatigue loads while respecting certain generator power and speed variation limits. Finally, the five controllers are tested with processor-in-the-loop (PIL). Fatigue loads are evaluated by rainflow counting algorithm and then applying the Palmgren'Miner rule. Tests results show that drive-train loads are significantly reduced from LQG1_CPC, that the complexity of the controllers does not have a significant influence on the reduction of tower loads, and that LQG3_IPC allows fatigue loads on blades to be alleviated considerably.

First laboratory results with the LINC-NIRVANA high layer wavefront sensor

In the field of adaptive optics, multi-conjugate adaptive optics (MCAO) can greatly increase the size of the corrected field of view (FoV) and also extend sky coverage. By applying layer oriented MCAO (LO-MCAO) [4], together with multiple guide stars (up to 20) and pyramid wavefront sensors [7], LINC-NIRVANA (L-N for short) [1] will provide two AO-corrected beams to a Fizeau interferometer to achieve 10 milliarcsecond angular resolution on the Large Binocular Telescope. This paper presents first laboratory results of the AO performance achieved with the high layer wavefront sensor (HWS). This sensor, together with its associated deformable mirror (a Xinetics-349), is being operated in one of the L-N laboratories. AO reference stars, spread across a 2 arc-minute FoV and with aberrations resulting from turbulence introduced at specific layers in the atmosphere, are simulated in this lab environment. This is achieved with the Multi-Atmosphere Phase screen and Stars (MAPS) [2] unit. From the wavefront data, the approximate residual wavefront error after correction has been calculated for different turbulent layer altitudes and wind speeds. Using a somewhat undersampled CCD, the FWHM of stars in the nearly 2 arc-minute FoV has also been measured. These test results demonstrate that the high layer wavefront sensor of LINC-NIRVANA will be able to achieve uniform AO correction across a large FoV.

Optimal controller design of a doubly-fed induction generator wind turbine system for small signal stability enhancement

Multi-objective optimal controller design of a doubly-fed induction generator (DFIG) wind turbine system using differential evolution (DE) is presented. A detailed mathematical model of DFIG wind turbine with a closed-loop vector control system is developed. Based on this, objective functions addressing the steady-state stability and dynamic performance at different operating conditions are implemented to optimise the controller parameters of both the rotor and grid-side converters. A superior ɛ-constraint method and method of adaptive penalties are applied to handle the multi-objective problem and the constraint with DE, respectively. Eigenvalue analysis and time-domain simulations are performed on a single machine infinite bus system as well as a nine-bus multi-machine system with two DFIG wind turbines to illustrate the control performance of the DFIG wind turbine with the optimised controller parameters. The electric energy productions of the studied DFIG wind turbine system with and without optimised controller parameters under turbulent wind speed are also demonstrated.

Well mixed condition verification in windy and low wind speed conditions

Dispersion in low wind speed conditions is governed by meandering that disperses plumes over wide angular sectors, thus g.l.c. are lower than predicted by Gaussian models. It was proposed to model these dispersion situations in homogeneous conditions with two coupled Langevin equations, based on low wind speed turbulence analysis. Their parameters were derived from the autocorrelation functions of horizontal wind that exhibit an oscillations and large negative lobes. We propose a new equation system for: general case of inhomogeneous turbulence; total velocity; for the windy situations (based on the Thomson simplest solution) and verify that these new solutions satisfy the well-mixed condition.

Deformable trailing edge flaps for modern megawatt wind turbine controllers using strain gauge sensors

AbstractThe present work contains a deformable trailing edge flap controller integrated in a numerically simulated modern, variablespeed, pitch‐regulated megawatt (MW)‐size wind turbine. The aeroservoelastic multi‐body code HAWC2 acts as a component in the control loop design. At the core of the proposed controller, all unsteady loads are divided by frequency content. Blade pitching and generator moment react to low‐frequency excitations, whereas flaps deal with high‐frequency excitations. The present work should be regarded as an investigation into the fatigue load reduction potential when applying trailing edge flaps on a wind turbine blade rather than a conclusive control design with traditional issues like stability and robustness fully investigated. Recent works have shown that the fatigue load reduction by use of trailing edge flaps may be greater than for traditional pitch control methods. By enabling the trailing edge to move independently and quickly along the spanwise position of the blade, local small flutuations in the aerodynamic forces can be alleviated by deformation of the airfoil flap. Strain gauges are used as input for the flap controller, and the effect of placing strain gauges at various radial positions on the blade is investigated. An optimization routine minimizes blade root fatigue loads. Calculations are based on the 5 MW reference wind turbine part of the UpWind project primarily with a mean turbulent wind speed close to rated power. A fatigue load reduction of 25% in the blade root moment was obtained for a continuous 6.3 m long flap. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Analysis of Maximum Wind force for Offshore Structure Design

This paper presents the results of a study in which a method is developed for estimating maximum turbulent wind drag force acting on a floating offshore structure with low natural frequency. In evaluating the drag force, forces associated with turbulent wind speeds are considered using both the linear and nonlinear reliability analysis approaches. A mathematical wind spectral density formulation is employed. The probability density function applied for the maximum turbulent wind-induced drag force analysis is considered as a random process. The maximum wind force is analytically developed by using an approximate single term expression for the functional relationship between the wind speed and the associated turbulent drag force. At last, the probable maximum and the design maximum values are estimated by applying maximum value statistics and reliability analysis.

Forecasting wind gusts in complex terrain

Wind gusts are calculated in a collection of simulated atmospheric flows in complex terrain. This study focuses on a region in West-Iceland during February to April 2007 which includes several windstorms. The atmospheric data is a subset in a large collection of realtime numerical simulations used for forecasting in Iceland. It is generated at horizontal resolutions of 9 and 3 km, and in two sensitivity tests at 1 km. The gust prediction method is based on turbulence kinetic energy, static stability and wind speed in the atmospheric boundary layer. The gust prediction method is implemented as post-processing. The calculated gust strength is compared with wind gust observations from several automatic weather stations. The estimated gusts are strongly dependent on the quality of the simulated flow and are on average well captured when the mean winds are correctly simulated. Maximum gusts in downslope windstorms are however frequently underestimated. The error is presumably related to an inadequate simulation of the downslope surface winds which are also too weak. The windstorms in the current study appear to be related to gravity wave activity aloft and are better reproduced at higher resolutions than at coarse resolution. There are cases of overestimated gusts on the upstream side of mountains, which may be related to an inadequate simulation of the upstream deceleration of the flow and overestimated surface winds. Gustiness in mountain wakes is frequently too great, which appears to be related to overestimated turbulence in the wakes.

Identification of wind turbines in closed‐loop operation in the presence of three‐dimensional turbulence wind speed: torque demand to measured generator speed loop

AbstractIn order to get reliable linear models for tuning controllers in real operation conditions, a procedure for identification in closed‐loop operation of wind turbine (WT) models at any time and placement is presented in this paper. This procedure has been tested using data from a nonlinear aeroelastic code, generated in a context reproducing real operation conditions of WTs, with the presence of three‐dimensional turbulence. The algorithms for model identification of WTs operating in closed loop together with the corresponding validation techniques are presented. To illustrate the procedure, data from one Bladed® WT model is used. Identification and validation of the model are presented and the resulting model is analysed and its characteristics are plotted. In the final sections of the paper, the model obtained from identification in closed loop and the model obtained by linearization are comparatively tested in terms of the performances obtained with the corresponding model‐based designed controllers applied to the Bladed® WT model. A description of future work concludes the paper. Copyright © 2009 John Wiley &amp; Sons, Ltd.