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Locating Renewable Resources
Published in Dorothy Gerring, Renewable Energy Systems for Building Designers, 2023
The Global Wind Atlas (GWA)18 provides worldwide wind maps that are intended to be used during the exploratory and preliminary phases of wind assessment, prior to taking measurements on site. This provides a tool for governments and investors to understand wind resource potential. Governments are thus saved the need and costs for early-stage national wind mapping. It is a free, interactive map that provides global onshore coverage and offshore up to 200km (124 miles) from the shoreline. It has hub heights at 10m (32.8’), 50m (164’), 100m (328’), 150m (492’), and 200m (656’) above ground/sea level. There are video tutorials on the website. Users can create maps on the fly or download high-resolution maps and data for use in GIS tools. Figure 3.1219 shows the results of mean wind speed on land and offshore worldwide at 100m.
Probability Distribution of the Wind Speed and Preliminary Design of Wind Power Installations
Published in Mario Alejandro Rosato, Small Wind Turbines for Electricity and Irrigation, 2018
Two are the probability density functions commonly employed for the said scope: Weibull’s and Rayleigh’s functions. Both generate a distribution of the probability (in practice, the number of hours in a year when the wind blows at each given speed), using as seed datum the average wind speed of the site. The applicability of one or the other function depends on the case: in weak wind zones (Vavg < 5 m/s), or in zones where the wind is unsteady, Weibull’s probability distribution function provides more accurate results, while in windy zones (Vavg > 5 m/s) Rayleigh’s function is more accurate. If the annual average wind speed is not available from local weather stations, such value can be estimated from wind maps. For instance, in Italy the Atlante Eolico Italiano (Italian wind atlas) is accessible to the public from http://atlanteeolico.rse-web.it/viewer.htm, and other countries have similar sites with wind data, either interactive or to download for free. The DTU (Danish Technical University), together with other research partners, has developed the Global Wind Atlas (GWA)http://globalwindatlas.com/, a mesoscale model of the whole world. Employing such maps is costless and relatively quick. Considering the large error that wind data from generic weather stations can induce in the calculation of the energy potential of a site, the results provided by mesoscale models are acceptable for the installation of small wind turbines. Of course, if data from a local weather station are available, it is worth to check these too, and then compare results.
Wind Resource Assessment
Published in Vaughn Nelson, Kenneth Starcher, Wind Energy, 2018
Vaughn Nelson, Kenneth Starcher
Wind maps are available for countries and regions around the world because wind energy is now included in many national energy policies. Check with national energy institutions for information available and latest data. The Global Wind Atlas [10] is a web-based application (1-km resolution) for policy makers and investors to help them identify potential wind power locations. The tool has online queries, downloadable datasets, and digital maps showing global, regional, and country wind resource potential. Other sources for wind maps are RETScreen International [11] and the Renewable Energy Data Explorer [12] has 13 international countries.
Large-scale offshore wind production in the Mediterranean Sea
Published in Cogent Engineering, 2019
Regarding the large-scale wind forcing, it has been derived from Global Wind Atlas 1.0—TDU Wind Energy. The data used in the Global Wind Atlas were chosen from the best available global datasets. In a reanalysis, observations around the globe and a numerical weather prediction model simulating one or more aspects of Earth system are combined objectively to generate a synthesized estimate of the state of the system. In the 2010s four large atmospheric reanalysis projects took place. All provide an output at a horizontal resolution below 1° × 1°. Three of these reanalyses (i.e., CFDDA, CFSR and MERRA) were generalized and later used in the global wind atlas.