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The main result from the project is a prototype satellite SAR wind retrieval and statistical analysis tool. The tool is an add-on the widely used WAsP micrositing model for wind turbine siting. The specific milestone achievements are: 1. SAR wind retrieval algorithms have been reviewed. 2. SAR images from the test sites in Norway, Denmark and Italy have been analysed to derive wind speed using, whenever possible, SAR retrieved wind direction. 3. New model simulations of the wind fields in the test sites have been carried out. 4. Model results and in situ data have been compared with SAR retrieved wind fields. 5. Definition and development of the WEMSAR tool. 6. Validation of WEMSAR tool. 7. Marketing of WEMSAR tool NERSC Technical Report np. 237. Funded by the European Union under Contract no. ERK6-CT1999-00017

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.

Leading edge erosion on wind turbine blades is a common issue, particularly for wind turbines placed in regions characterized by high wind speeds and precipitation. This study presents the development of a rain erosion atlas for Scandinavia and Finland, based on ERA5 reanalysis and NORA3 mesoscale model data on rainfall intensity and wind speed over five years. The IEA 15 MW reference wind turbine is used as an example to evaluate impingement water impact and erosion onset time for a commercial coating material. The damage progression is modeled by combining the wind speed and rainfall data with an empirical damage model that relates impinged water (H) as a function of impact velocity to the time of erosion onset. Comparative analyses at two weather station locations show that NORA3 data more accurately aligns with measurements in terms of power spectral density, mean wind speed, rainfall, and erosion prediction than ERA5. NORA3-based atlas layers offer finer spatial detail and predict shorter erosion onset times over land compared to ERA5, particularly in complex terrain. Conversely, the ERA5-based atlas suggests a shorter onset of erosion offshore. Based on NORA3 data, erosion onset time is estimated at 5 years on average for Baltic Sea wind farm sites and 3.2 years for sites in the North Sea.

A wind resource estimation study based on a series of 62 satellite wind field maps is presented. The maps were retrieved from imaging synthetic aperture radar (SAR) data. The wind field maps were used as input to the software RWT, which calculates the offshore wind resource based on spatial averaging (footprint modelling) of the wind statistic in each satellite image. The calculated statistics can then be input to the program WAsP and used in lieu of in-situ observations by meteorological instruments. A regional wind climate map based on satellite SAR images delineates significant spatial wind speed variations. The site of investigation was Horns Rev in the North Sea, where a meteorological time series is used for comparison. The advantages and limitations of these new techniques, which seem particularly useful for mapping of the regional wind climate, are discussed. Copyright © 2005 John Wiley & Sons, Ltd.

The offshore wind climate in Iceland is examined based on satellite synthetic aperture radar (SAR), coastal meteorological station measurements, and results from two atmospheric model data sets, HARMONIE and NORA10. The offshore winds in Iceland are highly influenced by the rugged coastline. Lee effects, gap flow, coastal barrier jets, and atmospheric gravity waves are not only observed in SAR, but are also modeled well from HARMONIE. Offshore meteorological observations are not available, but wind speed and wind direction measurements from coastal meteorological masts are found to compare well to nearby offshore locations observed by SAR. More than 2500 SAR scenes from the Envisat ASAR wide swath mode are used for wind energy resource estimation. The wind energy potential observed from satellite SAR shows high values above ${1000}\;{Wm}^{ - {2}}$ in coastal regions in the south, east, and west, with lower values in the north. The most promising region for wind energy production is the southwestern coastal region.