• Energy Research

In the North Sea, an array of wind profiling wind lidars were deployed mainly on offshore platforms. The purpose was to observe free stream winds at hub height. Eight lidars were validated prior to offshore deployment with observations from cup anemometers at 60, 80, 100 and 116 m on an onshore met mast situated in flat terrain. The so-called “NORSEWInD standard” for comparing lidar and mast wind data includes the criteria that the slope of the linear regression should lie within 0.98 and 1.01 and the linear correlation coefficient higher than 0.98 for the wind speed range 4–16 m∙s−1. Five lidars performed excellently, two slightly failed the first criterion and one failed both. The lidars were operated offshore from six months to more than two years and observed in total 107 months of 10-min mean wind profile observations. Four lidars were re-evaluated post deployment with excellent results. The flow distortion around platforms was examined using wind tunnel experiments and computational fluid dynamics and it was found that at 100 m height wind observations by the lidars were not significantly influenced by flow distortion. Observations of the vertical wind profile shear exponent at hub height are presented.

AbstractNacelle lidars are attractive for offshore measurements since they can provide measurements of the free wind speed in front of the turbine rotor without erecting a met mast, which significantly reduces the cost of the measurements. Nacelle‐mounted pulsed lidars with two lines of sight (LOS) have already been demonstrated to be suitable for use in power performance measurements. To be considered as a professional tool, however, power curve measurements performed using these instruments require traceable calibrated measurements and the quantification of the wind speed measurement uncertainty. Here we present and demonstrate a procedure fulfilling these needs.A nacelle lidar went through a comprehensive calibration procedure. This calibration took place in two stages. First with the lidar on the ground, the tilt and roll readings of the inclinometers in the nacelle lidar were calibrated. Then the lidar was installed on a 9m high platform in order to calibrate the wind speed measurement. The lidar's radial wind speed measurement along each LOS was compared with the wind speed measured by a calibrated cup anemometer, projected along the LOS direction. The various sources of uncertainty in the lidar wind speed measurement have been thoroughly determined: uncertainty of the reference anemometer, the horizontal and vertical positioning of the beam, the lack of homogeneity of the flow within the probe volume, lidar measurement mean deviation and standard uncertainty. The resulting uncertainty lies between 1 and 2% for the wind speed range between cut‐in and rated wind speed.Finally, the lidar was mounted on the nacelle of a wind turbine in order to perform a power curve measurement. The wind speed was simultaneously measured with a mast‐top mounted cup anemometer placed two rotor diameters upwind of the turbine. The wind speed uncertainty related to the lidar tilting was calculated based on the tilt angle uncertainty derived from the inclinometer calibration and the deviation of the measurement height from hub height. The resulting combined uncertainty in the power curve using the nacelle lidar was less than 10% larger on average than that obtained with the mast mounted cup anemometer. Copyright © 2015 John Wiley & Sons, Ltd.

AbstractThe advantages and limitations of the ZephIR®, a continuous‐wave, focused light detection and ranging (LiDAR) wind profiler, to observe offshore winds and turbulence characteristics were tested during a 6 month campaign at the transformer/platform of Horns Rev, the world's largest wind farm. The LiDAR system is a ground‐based sensing technique which avoids the use of high and costly meteorological masts. Three different inflow conditions were selected to perform LiDAR wind profiling. Comparisons of LiDAR mean wind speeds against cup anemometers from different masts showed high correlations for the open sea sectors and good agreement with their longitudinal turbulence characteristics. Cup anemometer mean wind speed profiles were extended with LiDAR profiles up to 161 m on each inflow sector. The extension resulted in a good profile match for the three surrounding masts. These extended profiles, averaged over all observed stabilities and surface roughness lengths, were compared to the logarithmic profile. The observed deviations were relatively small. Offshore wind farm wakes were also observed from LiDAR measurements where the wind speed deficits were detected at all LiDAR heights. Profile‐derived friction velocities and roughness lengths were compared to Charnock's sea roughness model. These average values were found to be close to the model, although the scatter of the individual estimations of sea roughness length was large. Copyright © 2008 John Wiley & Sons, Ltd.

In this talk, we present results of multi-lidar measurements from the Alaiz Experiment (ALEX17), carried out in a collaboration between DTU Wind Energy, CENER and UIB. Dual-Doppler synchronized measurements (125 m a.g.l.) are performed by four WindScanner systems on top of a ridge and a mountain range that are 6km apart. Results provide a first step towards resource assessment using scanning lidars, at the same time featuring the challenges faced to obtain a high data availability. The most common flow patterns are also highlighted, being gravity waves from notherly winds and atmospheric hydraulic jumps from southerly winds. These atmospheric phenomena are going to be better analyzed in an upcoming journal paper.

This report ALEX17, the acronym for ALaiz EXperiment 2017, is the last full-scale experiment within the NEWA (New European Wind Atlas) project, whose primary objective is to create a wind atlas of Europe that includes the state-of-the-art in modelling the wind resource, as well as the creation of a comprehensive database. ALEX17 aims to present a utility-scale measurements campaign to characterize the wind flow in complex terrain, through a combination of measurement technologies. Having finalized the measurements campaign and processed all the information, the wind flow in the area of study can be characterized for different weather conditions. In addition, the experimental data will be able to validate the reliability of numeric simulation models of wind flow in complex terrain, in order to reduce uncertainties when evaluating the wind resource.

Abstract A procedure for testing and evaluation of remote sensing instruments that makes use of two test sites in flat and complex terrain is presented. To illustrate the method, a system intercomparison experiment is presented involving one sodar and two lidars (pulsed and continuous-wave). The wind profilers are benchmarked with respect to reference cup anemometer and other mast-based instrumentation. The evaluation procedure comprises three steps: single-point regression, ensemble-averaged profile analysis and performance matrix summary. Apart from the influence of the terrain complexity on the flow field, it is also investigated the influence of the background atmospheric stability by classifying the results with the Richardson number in flat terrain and the Froude number in complex terrain. The result is a thorough field calibration of the instruments for a wide range of terrain-flow conditions fit for the purpose of conducting wind resource assessment campaigns.

AbstractIn this paper, we review a dynamical power curve concept that was introduced in earlier publications and shown to provide results for a wind turbine's power characteristic with several benefits compared with the IEC 61400‐12‐1 standard procedure. After summarizing the theoretical concept based on the theory of Langevin processes and their reconstruction, we enlarge on a number of specific practical issues. Special attention is paid to the convergence or robustness of the reconstructed results, and their dependence on different settings for the data analysis scheme is studied. A key issue for the procedure that is investigated in this paper is the variability of the wind speed data that may be controlled by applying a specific data filter. It is seen that the necessity for filtering depends both on the time scales present in the wind data in relation to the wind turbine power dynamics and to some degree also on the correlation between the wind and the power signal.The observations and findings altogether suggest that the dynamical performance characteristic, as it is considered here, is definitely a promising concept, particularly since it allows much flexibility in the handling of noisy performance data, but with some technical difficulties that demand a careful consideration in order to obtain reproducible and representative results. Copyright © 2014 John Wiley & Sons, Ltd.

ABSTRACTThe current IEC standard for wind turbine power performance measurement only requires measurement of the wind speed at hub height assuming this wind speed to be representative for the whole rotor swept area. However, the power output of a wind turbine depends on the kinetic energy flux, which itself depends on the wind speed profile, especially for large turbines. Therefore, it is important to characterize the wind profile in front of the turbine, and this should be preferably achieved by measuring the wind speed over the vertical range between lower and higher rotor tips.In this paper, we describe an experiment in which wind speed profiles were measured in front of a multimegawatt turbine using a ground–based pulsed lidar. Ignoring the vertical shear was shown to overestimate the kinetic energy flux of these profiles, in particular for those deviating significantly from a power law profile. As a consequence, the power curve obtained for these deviant profiles was different from that obtained for the ‘near power law’ profiles. An equivalent wind speed based on the kinetic energy derived from the measured wind speed profile was then used to plot the performance curves. The curves obtained for the two kinds of profiles were very similar, corresponding to a significant reduction of the scatter for an undivided data set. This new method for power curve measurement results in a power curve less sensitive to shear. It is therefore expected to eventually reduce the power curve measurement uncertainty and improve the annual energy production estimation. Copyright © 2011 John Wiley & Sons, Ltd.