Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

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.publishedVersio

Summer Algal Blooms in a Coastal Ecosystem: the Role of Atmospheric Deposition Versus Entrainment Fluxes

The nitrogen inputs from atmospheric deposition and bottom water entrainment to the surface layer were modelled in the summer period (May–September) over a 11-year period (1989–1999) and compared to investigate the significance of these fluxes for generating blooms in the Kattegat. In the summer periods the average atmospheric deposition was 2.81 mg N m-2 d-1 compared to average entrainment fluxes of 5.42 mg N m-2 d-1, 1.21 mg N m-2 d- and 1.15 mg N m-2 d-1 for the northern, central and southern part of the Kattegat, respectively. Atmospheric nitrogen deposition alone could not sustain biomass increases associated with observed blooms and entrainment fluxes dominated the high nitrogen inputs to the surface layer. The potential for a bloom through growth was typically obtained after several days of high nitrogen inputs from entrainment in the frontal area of the northern Kattegat and to some extent from atmospheric deposition. The modelled nitrogen input in this area could account directly for 30% of the observed blooms in the Northern sub-basin, and through advective transport 24% and 19% of the observed blooms in the central and southern Kattegat. The direct nitrogen inputs through atmospheric deposition and entrainment to the central and southern sub-basins were small and could not be linked to any bloom observation. 2004 Elsevier Ltd. All rights reserved.JRC.H.5-Rural, water and ecosystem resource

Support of wind resource modeling using Earth observation – a European perspective on the status and future options

This contribution outlines the potential of remote sensing data to support wind resource modelling especially through improved input parameterization regarding the state and characterization of the land surface. Wind speed and wind flow is strongly influenced by land surface properties. Three different remote sensing based parameters can help to characterize wind resources: a) land cover and land use; b) digital elevation models (DEM); c) phenological information. Earth observation data are used already in wind resource models to some extent. However, the new advances and especially the possibilities which open up through the Copernicus Sentinel satellites are not considered yet. Opportunities include seasonal mapping of land cover which will allow a precise quantification of vegetation cover which has a direct influence on heat fluxes. The use of newest DEMs like Tandem-X with a 12 m resolution allows detecting also small landscape feature like rows of hedges and trees. Further, elevation models derived by either photogrammetric approaches or airborne laser scanning can further refine the information. By using EO-based information on the surface, e.g. roughness, and in-situ wind measurements, realistic wind fields for sufficiently large areas can be derived by considering also shadowing effects and wind shear