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Wind turbine blade erosion poses a significant challenge to the durability and performance of wind turbines. Modeling of rain erosion damage, considering atmospheric conditions, improves our understanding of the progression of leading-edge erosion on wind turbine blades. In this study, we investigate the impact of varying raindrop characteristics on rain erosion damage development. We analyse 2.5 years of data from a disdrometer, which measures the size and velocity of falling rain droplets, at Risø campus. Various post-processing methods of the disdrometer data are used for estimating representative droplet diameters and fall velocities for each rain event. We compare measured droplet fall velocities with theoretical terminal velocities, revealing a necessity for revising theoretical approaches to raindrop fall velocity for erosion damage modeling. The measured rain rates and representative fall velocities are used to calculate the liquid water content in the air. We introduce a bin-wise summation method for estimating the liquid water content, circumventing the need for representative droplet assumptions. As this method provides the most accurate input for the damage model, we benchmark the other post-processing methods against it and employ it to evaluate bias estimates of associated damage predictions. The largest bias (22%) in accumulated damage is found with an arithmetic mean droplet diameter approach and the smallest bias (-2%) with the median volume estimation method for damage model input. Furthermore, we demonstrate that, for a given rainfall volume, smaller droplets contribute to larger accumulated damage compared to larger droplets.

Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world’s forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. Wefoundthatthetwomostdescriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns.

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

Solitary trees are natural land surface elements found in almost all climates, yet their influence on the surrounding airflow is poorly known. Here we use state-of-the-art, laser-based, remote sensing instruments to study the turbulent wind field in the near-wake region of a mature, open-grown oak tree. Our measurements provide for the first time a full picture of the mixing layer of high turbulence that surrounds the mean wind speed deficit. In this layer, we investigate the validity of a two-dimensional vectorial relation derived from the eddy-viscosity hypothesis, a hypothesis commonly used in modelling the turbulence transport of momentum and scalars in the atmosphere. We find that the momentum fluxes of the streamwise wind component can be adequately predicted by the transverse gradient of the mean flow. Using the mixing-length hypothesis we find that for this tree the corresponding turbulence length scale in the mixing layer can be approximated by one height-independent value. Further, the laser-based scanning technology used here was able to accurately reveal three-dimensional turbulent and spatially varying atmospheric flows over a large plane without seeding or intruding the atmospheric flow. This capability points to a new and more exact way of exploring the complex earth-atmosphere interactions.

Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world's forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. We found that the two most descriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns.

Satellitbaserede datalag kan gøre det lettere at bestemme den årlige energiproduktion for kommende vindmølleparker på land. Det kan føre til en lavere usikkerhed og besparelser i millionklassen.

We present a new algorithm for the estimation of the plant area density (PAD) profiles and plant area index (PAI) for forested areas based on data from airborne lidar. The new element in the algorithm is to scale and average returned lidar intensities for each lidar pulse, whereas other methods do not use the intensity information at all, use only average intensity values, or do not scale the intensity information, which can cause problems for heterogeneous vegetation. We compare the performance of the new algorithm to three previously published algorithms over two contrasting types of forest: a boreal coniferous forest with a relatively open structure and a dense beech forest. For the beech forest site, both summer (full-leaf) and winter (bare-tree) scans are analyzed, thereby testing the algorithm over a wide spectrum of PAIs. Whereas all tested algorithms give qualitatively similar results, absolute differences are large (up to 400 % for the average PAI at one site). A comparison with ground-based estimates shows that the new algorithm performs well for the tested sites. Specific weak points regarding the estimation of the PAD from airborne lidar data are addressed including the influence of ground reflections and the effect of small-scale heterogeneity, and we show how the effect of these points is reduced in the new algorithm, by combining benefits of earlier algorithms. We further show that low-resolution gridding of the PAD will lead to a negative bias in the resulting estimate according to Jensen's inequality for convex functions and that the severity of this bias is method dependent. As a result, the PAI magnitude as well as heterogeneity scales should be carefully considered when setting the resolution for the PAD gridding of airborne lidar scans.

Parameterizing the effect of vertically-distributed vegetation through an effective roughness (z0,eff) – whereby momentum loss through a three-dimensional foliage volume is represented as momentum loss over an area at one vertical level – can facilitate the use of forest data in flow models, to any level of detail, and simultaneously reduce computational cost. Results of numerical experiments and comparison with observations show that a modelling approach based on z0,eff can estimate wind speed and turbulence levels over forested areas, at heights of interest for wind energy applications (∼ 60 m and higher), but only above flat terrain. Caution must be exercised in the application of such a model to zones of forest edges. Advanced flow models capable of incorporating local (distributed) drag forces are recommended for complex terrain covered by forest.

This study reports simultaneous measurements of wind at single point positions up- and downstream of a tree and a numerical experiment with the aim of quantifying the interaction of a solitary tree and the wind field. Relative to the inflow velocity, the velocity deficit in the wake of the tree showed strong seasonal dependence, with wake velocities changing between 70% and 10% of the upstream value from no-leaf winter conditions to full-leaf summer conditions. Whereas for the winter tree the turbulence intensity in the wake is everywhere reduced relative to the upwind flow, for the summer tree the turbulent intensity is markedly reduced in the inner wake, but increased in the outer wake. For the numerical experiment, the combination of (i) a high-detail tree model, based on terrestrial lidar scanning, and (ii) observations of the total bending moment on the tree, taken from strain gauges mounted on the stem, provided the tree parameterization. By this approach, the drag coefficient is not calibrated to fit the observed wind speed in the wake, but the total observed bending moment. Mean wind speed observations in the wake of both the winter and summer tree were well reproduced by the model with mean absolute errors lower than or equal to 5% throughout the wake transect. Also the turbulence intensity in the wake were well reproduced for the summer tree, whereas it was overestimated for the winter tree. Effects of changing tree model and grid resolution are demonstrated and discussed. Based on the presented findings, we recommend to estimate the total bending moment (or drag force) on modelled trees to ensure transferability of results between different numerical setups.

The aim of the present work is to obtain a better understanding of how to model the thermally stratified wind field over a forest during full diurnal cycles. The setup of the study assumes a horizontally homogeneous forest, with the objective of finding a simple and efficient way to model the canopy flow using time-dependent input data, obtained from measurements and mesoscale simulations. With this, new insights can be gained for future microscale modelling of complex forested terrains using mesoscale input data. In terrain without forest a diurnal cycle is commonly simulated by imposing time-dependent ground temperature. However, the presence of forests partially isolates the temperature at ground level from the flow above the canopy, making this common approach ineffective. This work proposes imposing the time-dependent net radiation at the forest canopy top to drive the thermal stratification changes along the diurnal cycle. To this end, several full days of simulation are driven by prescribing the net radiative heat flux balance measured on top of the canopy, together with a geostrophic pressure gradient. The advantage of the method is its simplicity and that the input data can be easily obtained from mesoscale modelling. When compared to the observations at the Swedish site Ryningsnas, the new method dramatically improves estimations of wind speed, wind direction and turbulent kinetic energy compared to simulations that only assume neutral stratification. Out of the variables studied, temperature and turbulent heat flux profiles were the ones that qualitatively followed the measurements the best, while wind speed and turbulent kinetic energy showed a larger disagreement.

We propose a method to assess the accuracy of atmospheric turbulence measurements performed by sonic anemometers and test it by analysis of measurements from two commonly used sonic anemometers, a Metek USA-1 and a Campbell CSAT3, at two locations in Denmark. The method relies on the estimation of the ratio of the vertical to the along-wind velocity power spectrum within the inertial subrange and does not require the use of another measurement as reference. When we correct the USA-1 to account for three-dimensional flow-distortion effects, as recommended by Metek GmbH, the ratio is very close to 4/3 as expected from Kolmogorov's hypothesis, whereas non-corrected data show a ratio close to 1. For the CSAT3, non-corrected data show a ratio close to 1.1 for the two sites and for wind directions where the instrument is not directly affected by the mast. After applying a previously suggested flow-distortion correction, the ratio increases up to approximate to 1.2, implying that the effect of flow distortion in this instrument is still not properly accounted for.