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To assess dynamic loads, large offshore wind turbines need detailed and reliable statistical information on the inflow turbulence. We present a model that includes low frequencies down to ∼ 1 hr - 1 using the observed S (f) ∝ f - 5 / 3 in that range. The presented model contains a parameter representing the anisotropy of the two-dimensional, incompressible turbulence, and it assumes the low-frequency fluctuations to be homogeneous in the vertical direction. Combined with a three-dimensional model for the smaller scales, the model can predict correlations between different points. We have validated the model against two offshore wind data sets: a nacelle-mounted, forward-looking Doppler lidar with four beams at the Hywind Scotland offshore wind farm and sonic anemometer measurements at the FINO1 research platform in the North Sea. One-point auto spectra and two-point cross spectra were calculated after splitting the data into different atmospheric stability classes. The relative strength of the 2D low-frequency fluctuations to the 3D fluctuations was higher under stable conditions. The combined 2D+3D model was able to fit the measured spectra with good accuracy and could then predict the two-point cross spectra, co-coherences, and phase angles between wind fluctuations at different lateral and vertical separations. Good agreement was found between the measured and predicted values, albeit with exceptions. The model can generate stochastic wind fields for investigating wake meandering in wind farms or dynamic loads on floating wind turbines. [ABSTRACT FROM AUTHOR]

In moderate to heavy precipitation, raindrops may deteriorate the accuracy of Doppler lidar measurements of the line-of-sight wind velocity because their projected velocity in the beam direction differs greatly from that of air. Therefore, we propose a method for effectively suppressing the adverse effects of rain on velocity estimation by sampling the Doppler spectra faster than the time taken for a raindrop to transit through the beam. By using a special averaging procedure, we can suppress the strong rain signal by sampling the spectrum at 3 kHz. A proof-of-concept field measurement campaign was performed on a moderately rainy day with a maximum rain intensity of 4 mmh-1 using three ground-based continuous-wave Doppler lidars at the Risø campus of the Technical University of Denmark. We demonstrate that the rain bias can effectively be removed by normalizing the noise-flattened 3 kHz sampled Doppler spectra with their peak values before they are averaged down to 50 Hz prior to the determination of the speed. In comparison to the sonic anemometer measurements acquired at the same location, the wind velocity bias at 50 Hz (20 ms) temporal resolution is reduced from up to -1.58 ms-1 for the original raw lidar data to -0.18 ms-1 for the normalized lidar data after suppressing strong rain signals. This reduction in the bias occurs during the minute with the highest amount of rain when the focus distance of the lidar is 103.9 m and the corresponding probe length is 9.8 m. With the smallest probe length, 1.2 m, the rain-induced bias is only present at the period with the highest rain intensity and is also effectively eliminated with the procedure. Thus, the proposed method for reducing the impact of rain on continuous-wave Doppler lidar measurements of air velocity is promising and does not require much computational effort. [ABSTRACT FROM AUTHOR]

In moderate to heavy precipitation, rain droplets may deteriorate Doppler lidars' accuracy for measuring the line-of-sight wind velocity because their projected velocity on the beam direction differs greatly from that of air. Therefore, we propose a method of effectively filtering away the adverse effects of rain on velocity estimation by sampling the Doppler spectra faster than the rain drops' beam transit time. By using a special averaging procedure, we can suppress the rain signal by sampling the spectrum at 3 kHz. On a moderately rainy day with a maximum rain intensity of 4 mm/h, three ground-based continuous-wave Doppler lidars were used to conduct a field measurement campaign at the Risø campus of the Technical University of Denmark. We demonstrate that the rain bias can effectively be removed by normalizing the noise-flattened Doppler spectra with their peak values before they are averaged down to 50 Hz prior to the determination of the speed. In comparison to the sonic anemometer measurements acquired at the same location, the wind velocity bias at 50 Hz is reduced from up to −1.58 m/s of the conventional lidar data to −0.18 m/s of the normalized lidar data. This significant reduction of the bias occurs at the minute with the highest amount of rain when the measurement distance of the lidar is 103.9 m with a corresponding probe length being 9.8 m. With the smallest probe length, 1.2 m, the rain-induced bias was only present at the period with the highest rain intensity and was also effectively eliminated with the procedure. Thus the proposed method for reducing the impact of rain on continuous-wave Doppler lidar measurements of air velocity is promising, without requiring much computational effort. [ABSTRACT FROM AUTHOR]

The full-width at half-maximum or probe length of the Lorentzian weighting function of continuous-wave Doppler lidars increases quadratically with the focus distance, which results in a deterioration in the spatial resolution of measurements. What is worse, a Doppler lidar is susceptible to moving objects that are far away from the intended measurement point. Therefore, we suggest a novel configuration to mitigate these problems by deploying two co-planar quarter-wave plates with orthogonal fast axes in the conventional continuous-wave lidar system, without any change to the other optical or electronic components. If the vertically polarized laser beam that we emit goes out and its backscattered beam returns back through the same quarter-wave plate, the returned beam will become horizontally polarized. The horizontally polarized backscattered beam cannot beat with the vertically polarized local oscillator to generate a Doppler signal. However, the polarization of the returned beam will remain unchanged if the emitted beam travels out through one plate and returns through the other. In this way, the influence of a moving backscattering particle far away from the focus point can be reduced. Both theoretical and experimental results show that, in a proper configuration, the probe length of the continuous-wave lidar can be reduced by 10 % , compared with that of the conventional lidar. In addition, the fat tails of the Lorentzian weighting function can be suppressed by up to 80 % to reduce the return from a cloud, albeit with a large reduction (perhaps 90 % ) in the signal power. This investigation provides a potential method to increase the spatial resolution of Doppler wind lidars and suppress the low-hanging cloud return. [ABSTRACT FROM AUTHOR]

Lidar-assisted wind turbine control has been proven to be beneficial for turbine load reduction. It relies on the preview of incoming turbulence provided by a nacelle lidar, which allows the turbine controller to react to the flow disturbances before their impact on the turbine. When assessing its benefits, previous studies mainly use the standard turbulence parameters suggested by the IEC 61400-1 standard and assume Taylor's frozen hypothesis. Based on atmospheric turbulence observations, the parameters of the Mann spectral turbulence model differ significantly from the values recommended in the standard, and they vary, e.g., with atmospheric stability. Also, turbulence evolution from upstream to the rotor position conflicts with the frozen turbulence hypothesis, and its effect on the preview quality by a nacelle lidar still needs quantification. This work presents a simple method to extend the Mann model to account for the temporal evolution of turbulence using a space-time spectral velocity tensor. Under various atmospheric stability conditions, we derive the space-time tensor parameters and evaluate the space-time tensor using data from a five-beam lidar and a meteorological mast, we found good agreement between the space-time tensor and the measurement data. In addition, a numerical method for simulating a four-dimensional (4D) space-time velocity field based on the space-time tensor is presented. In the end, we analyze the importance of including the temporal evolution of turbulence for assessing lidar wind preview quality. Lidar-assisted wind turbine control has been proven to be beneficial for turbine load reduction. It relies on the preview of incoming turbulence provided by a nacelle lidar, which allows the turbine controller to react to the disturbances prior their impact on the turbine. This work presents a simple method to extend the Mann model to account for the temporal evolution of turbulence using a space-time spectral velocity tensor. Under various atmospheric stability conditions, we derive the space-time tensor parameters and evaluate the space-time tensor using data from a five-beam lidar and a meteorological mast, we found good agreement between the space-time tensor and the measurement data. We analyze the importance of including the temporal evolution of turbulence for assessing lidar wind preview quality. Figure 1: Typical nacelle lidar measurements over a wind field. The evolved turbulence (more transparent) illustrates the actual rotor disturbance while the upstream turbulence is observed by the lidar. A Gaussian range weighting shape/function is shown for LOS measurements (the LOS speeds along the beam are weight averaged by this function to get lidar LOS measurement). [Display omitted] [ABSTRACT FROM AUTHOR]

Trees are known to reduce the wind momentum efficiently. Yet, firm quantitative estimates of their contribution to the land surface drag have remained elusive, partly because trees have complex shapes that consist of elastic multi-scale elements. This structural complexity makes trees inherently difficult to scale for wind tunnel studies. Here, we test a new method for quantifying the drag force on a solitary mature tree in its natural environment. The method is based on the application of mass and momentum conservation over a control volume that encloses the tree. For this control volume, the drag force is estimated through the momentum deficit in the wake. For the characterisation of the heterogeneous and high-gradient wind field in the wake, spatially distributed measurements of the wind vector were acquired using three synchronously scanning wind lidar instruments in a vertical plane encompassing the wake. The resulting drag force estimate is compared to a reference measurement from a tree-mounted sensor at the base of the stem. We find that the drag force in both methods shows a dependence on the wind speed raised to an exponent of 1.8 and that the drag force, based on the momentum deficit method, is consistently underestimated by 1%–10%. Potential reasons for this bias are discussed in light of the accuracy of both methods. The relatively close agreement between the two methods indicates that scanning Doppler lidar measurements can be used to determine the drag force on complex objects in their natural environment, such as trees. [ABSTRACT FROM AUTHOR]

Scanning Doppler lidars have great potential for reducing uncertainty of wind resource estimation in complex terrain. Due to their scanning capabilities, they can measure at multiple locations over large areas. We demonstrate this ability with dual-Doppler lidar measurements of flow over two parallel ridges. The data have been collected using two pairs of scanning lidars operated in a dual-Doppler mode during the Perdigão 2017 measurement campaign. There the scanning lidars mapped the flow 80m above ground level along two ridges, which are considered favorable for wind turbine siting. The measurements are validated with sonic wind measurements at each ridge. By analyzing the collected data, we found that wind speeds are on average 10% higher over the southwest ridge compared to the northeast ridge. At the southwest ridge, the data show, for approach flow normal to the ridge, a change of 20% in wind speed along the ridge. Fine differences like these are difficult to reproduce with computational flow models, as we demonstrate by comparing the lidar measurements withWeather Research and Forecasting large-eddy simulation (WRF-LES) results. For the measurement period, we have simulated the flow over the site using WRF-LES to compare how well the model can capture wind resources along the ridges. We used two model configurations. In the first configuration, surface drag is based purely on aerodynamic roughness, whereas in the second configuration forest canopy drag is also considered. We found that simulated winds are underestimated in WRF-LES runs with forest drag due to an unrealistic forest distribution on the ridge tops. The correlation of simulated and observed winds is, however, improved when the forest parameterization is applied. WRF-LES results without forest drag overestimated the wind resources over the southwest and northeast ridges by 6.5% and 4.5%, respectively. Overall, this study demonstrates the ability of scanning lidars to map wind resources in complex terrain. [ABSTRACT FROM AUTHOR]

We define and demonstrate a procedure for carrying out wind turbine load validation based on measurements from nacelle‐mounted scanning lidars. Two coherent Doppler lidar systems, a pulsed lidar and a continuous‐wave lidar, are mounted on a 2.3‐MW wind turbine equipped with load measurement sensors. Wind measurements from a meteorological mast mounted at 2.5 rotor diameters distance are used as reference. The study shows how lidar measurements are processed and applied as inputs to aeroelastic load simulations, and the results are then compared with simulations where the wind inputs have been determined using the meteorological mast data in compliance with the IEC61400‐13 standard. For the majority of simulation cases considered, the use of nacelle‐mounted lidar measurements results in load estimation uncertainties lower or equal to those that are based on measurements from cup anemometers on the mast. These results demonstrate the usefulness of nacelle‐mounted lidars as tools for carrying out load validation without the need of meteorological masts. [ABSTRACT FROM AUTHOR]

Because flow recirculation can generate significant amounts of turbulence, it can impact the success of wind energy projects. This study uses unique Doppler lidar observations to quantify occurrences of flow recirculation on lee sides of ridges. An extensive dataset of observations of flow over complex terrain is available from the Perdigão 2017 field campaign over a period of 3 months. The campaign site was selected because of the unique terrain feature of two nearly parallel ridges with a valley-to-ridge-top height difference of about 200 m and a ridge-to-ridge distance of 1.4 km. Six scanning Doppler lidars probed the flow field in several vertical planes orthogonal to the ridges using range–height indicator scans. With this lidar setup, we achieved vertical scans of the recirculation zone at three positions along two parallel ridges. We construct a method to identify flow recirculation zones in the scans, as well as define characteristics of these zones. According to our data analysis, flow recirculation, with reverse flow wind speeds greater than 0.5 m s -1 , occurs over 50% of the time when the wind direction is perpendicular to the direction of the ridges. Atmospheric conditions, such as atmospheric stability and wind speed, affect the occurrence of flow recirculation. Flow recirculation occurs more frequently during periods with wind speeds above 8 m s -1. Recirculation within the valley affects the mean wind and turbulence fields at turbine heights on the downwind ridge in magnitudes significant for wind resource assessment. [ABSTRACT FROM AUTHOR]

Three synchronized pulsed Doppler wind lidars were deployed from May 2016 to June 2016 on the shores of a wide Norwegian fjord called Bjørnafjord to study the wind characteristics at the proposed location of a planned bridge. The purpose was to investigate the potential of using lidars to gather information on turbulence characteristics in the middle of a wide fjord. The study includes the analysis of the single-point and two-point statistics of wind turbulence, which are of major interest to estimate dynamic wind loads on structures. The horizontal wind components were measured by the intersecting scanning beams, along a line located 25m above the sea surface, at scanning distances up to 4.6km. For a mean wind velocity above 8m.s-1, the recorded turbulence intensity was below 0.06 on average. Even though the along-beam spatial averaging leads to an underestimated turbulence intensity, such a value indicates a roughness length much lower than provided in the European standard EN 1991-1-4:2005. The normalized spectrum of the along-wind component was compared to the one provided by the Norwegian Petroleum Industry Standard and the Norwegian Handbook for bridge design N400. A good overall agreement was observed for wave-numbers below 0.02m-1. The along-beam spatial averaging in the adopted set-up prevented a more detailed comparison at larger wave-numbers, which challenges the study of wind turbulence at scanning distances of several kilometres. The results presented illustrate the need to complement lidar data with point-measurement to reduce the uncertainties linked to the atmospheric stability and the spatial averaging of the lidar probe volume. The measured lateral coherence was associated with a decay coefficient larger than expected for the along-wind component, with a value around 21 for a mean wind velocity bounded between 10m.s-1 and 14m.s-1, which may be related to a stable atmospheric stratification. [ABSTRACT FROM AUTHOR]

The technical aspects of a multi-Doppler LiDAR instrument, the long-rangeWindScanner system, are presented accompanied by an overview of the results from several field campaigns. The long-range WindScanner system consists of three spatially-separated, scanning coherent Doppler LiDARs and a remote master computer that coordinates them. The LiDARs were carefully engineered to perform user-defined and time-controlled scanning trajectories. Their wireless coordination via the master computer allows achieving and maintaining the LiDARs' synchronization within ten milliseconds. The long-rangeWindScanner system measures the wind field by emitting and directing three laser beams to intersect, and then scanning the beam intersection over a region of interest. The long-range WindScanner system was developed to tackle the need for high-quality observations of wind fields on scales of modern wind turbine and wind farms. It has been in operation since 2013. [ABSTRACT FROM AUTHOR]

It is well known that when eddies are small, the eddy fluxes can be directly related to the mean vertical gradients, the so-called flux-gradient relation, but such a relation becomes weaker the larger the coherent structures. Here, we show that this relation does not hold at heights relevant for wind energy applications. The flux–gradient relation assumes that the angle (β) between the vector of vertical flux of horizontal momentum and the vector of the mean vertical gradient of horizontal velocity is zero, i.e., these vectors are aligned. Our observations do not support this assumption, either onshore or offshore. Here, we present analyses of a misalignment between these vectors from a Doppler wind lidar observations and large-eddy simulations. We also use a real-time mesoscale model output for inter-comparison with the lidar-observed vertical profiles of wind speed, wind direction, momentum fluxes, and the angle between the horizontal velocity vector and the momentum flux vector up to 500 m, both offshore and onshore. The observations show this within the height range 100–500 m, β = − 18 ∘ offshore and β = − 12 ∘ onshore, on average. However, the large-eddy simulations show β ≈ 0 ∘ both offshore and onshore. We show that observed and mesoscale-simulated vertical profiles of mean wind speed and momentum fluxes agree well; however, the mesoscale results significantly deviate from the wind-turning observations. [ABSTRACT FROM AUTHOR]

The long-range and short-range WindScanner systems, multi-Doppler lidar instruments, can map the turbulent flow around a wind turbine and at the same time measure mean flow conditions over an entire region such as a wind farm. As the WindScanner technology is novel, performing field campaigns with the WindScanner systems requires a methodology that will maximize the benefits of conducting WindScanner-based experiments. Such a methodology is presented and discussed through its application in a pilot experiment that took place in a complex and forested site in Portugal where for the first time the two WindScanner systems operated simultaneously. The methodology consists of 10 steps. The steps are presented and the implementation of each step is demonstrated. Overall, the demonstration of the methodology in the pilot experiment resulted in a detailed site selection criteria, well-thought-out experiment layout, novel flow mapping methods and high quality flow observations, all of which are presented in this paper. [ABSTRACT FROM AUTHOR]

This paper shows an efficient adaptation of a polarization diversity optical front-end, commonly used in high-speed fiber-optic communications, in a coherent Doppler lidar (CDL). The adopted architecture can be employed in a modified transceiver design for an all-fiber micropulsed coherent Doppler wind lidar where the performance limits of such systems are pushed beyond the conventionally available wind CDLs. As a result, either a longer measurement range, crucial in clear-air environments with low concentration of aerosols, or a shorter integration time (resulting in a faster scanning) can be achieved. Alternatively, in certain aerosol loading conditions where the presence of nonspherical aerosols is considerable, the system can be reconfigured on the fly to analyze the cross polarization of the backscatter optical signal. The result is the capability to analyze the nature of aerosol particles for the detected range of interest. Due to full utilization of the backscatter signal, i.e., detection of co-polarization and cross polarization components, the signal-to-noise-ratio (SNR) as well as detection range is improved in this configuration. Moreover, the system is capable of providing a more reliable estimation of the aerosol backscatter coefficient when compared with the contemporary CDLs. This system employs robust and compact all-fiber subsystems, which are cost effective and widely available as off-the-shelf components. [ABSTRACT FROM AUTHOR]