Ferhat Bingöl

SAR-based Wind Resource Statistics in the Baltic Sea

Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

Conically scanning lidar error in complex terrain

Conically scanning lidars assume the flow to be homogeneous in order to deduce the horizontal wind speed. However, in mountainous or complex terrain this assumption is not valid implying a risk that the lidar will derive an erroneous wind speed. The magnitude of this error is measured by collocating a meteorological mast and a lidar at two Greek sites, one hilly and one mountainous. The maximum error for the sites investigated is of the order of 10 %. In order to predict the error for various wind directions the flows at both sites are simulated with the linearized flow model, WAsP Engineering 2.0. The measurement data are compared with the model predictions with good results for the hilly site, but with less success at the mountainous site. This is a deficiency of the flow model, but the methods presented in this paper can be used with any flow model.

Lidar Scanning of Momentum Flux in and above the Atmospheric Surface Layer

Abstract Methods to measure the vertical flux of horizontal momentum using both continuous wave and pulsed Doppler lidar profilers are evaluated. The lidar measurements are compared to momentum flux observations performed with sonic anemometers over flat terrain at Hovsore, Denmark, and profile-derived vertical momentum flux observations at the Horns Rev wind farm in the North Sea. Generally, the momentum fluxes are reduced because of the finite measuring volume of the instruments, and the filtering is crudely accounted for theoretically. The essential parameter for the estimation of the reduction is the ratio of the turbulence scale to the size of the measuring volume. For the continuous wave lidar the reduction can largely be compensated by averaging Doppler spectra instead of radial velocities.

LiDAR error estimation with WAsP engineering

The LiDAR measurements, vertical wind profile in any height between 10 to 150m, are based on assumption that the measured wind is a product of a homogenous wind. In reality there are many factors affecting the wind on each measurement point which the terrain plays the main role. To model LiDAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met, mast data have been collected and the same conditions are simulated with RisO/DTU software, WAsP Engineering 2.0. Finally measurement data is compared with the model results. The model results are acceptable and very close for one site while the more complex one is returning higher errors at higher positions and in some wind directions.

Laser measurements of flow over a forest

It is estimated that 20–30% of the total European wind energy growth takes place in areas where the wind flow is affected by forests. The description of the wind conditions near and above forests poses a challenge, since assumptions of classical boundary-layer theory are violated. Turbines are designed for a maximal turbulence intensity and wind profile gradient. In forested areas, these limits are often violated possibly leading to reduced turbine life-time. In this paper we investigate the mean wind profile and turbulence statistics above an 85 years old dense beech forest by use of a laser Doppler anemometer and compare the profiles with a CFD model specifically made for the modeling of flow over vegetation canopies.

Wake Meandering - An Analysis of Instantaneous 2D Laser Measurements

The vast majority of wind turbines are today erected in wind farms. As a consequence, wake generated loads are becoming more and more important. We present a new experimental technique to measure the instantaneous wake deficit directly, thus allowing us to quantify the wake meandering as well as the instantaneous wake expansion expressed in a meandering frame of reference. The experimental results are subsequently used in a preliminary verification of the basic conjecture of a wake meandering model that essentially considers the wake as a passive tracer.

Fast wake measurements with LiDAR at Risø test field

The vast majority of wind turbines are today erected in wind farms. As a consequence, wake generated loads are becoming more and more important. We present a new and successful experimental technique, based on remote sensing, to measure instantaneously the flow in the wake of wind turbines. Downstream wind speed can be quantified spatially in one and two dimensions. Data analysis allows us to identify the wake transversal position, thus enabling us to quantify the wake meandering as well as the instantaneous wake expansion expressed in a meandering frame of reference. The experimental results are subsequently used in a preliminary verification of the basic conjecture of a wake meandering model that essentially considers the wake as a passive tracer.

An Attempt to Characterize the Structure of Wake Turbulence Using a Combined Experimental and Numerical Approach

This paper describes a combined numerical and experimental effort to characterize the structure of wake turbulence. The numerical approach is based on detailed LES. The experimental approach is based on an innovative analysis applied on full-scale wake recordings obtained using a newly developed 2D lidar technology. Consistency between the numerical and experimental approaches in terms of wake turbulence characteristics is observed. Compared to conventional atmospheric boundary layer (ABL) turbulence, the wake turbulence is inhomogeneous with reduced length scales, increased intensity, and increased coherence decay.