23 june 2023
This summer, version 3.3 of the Global Wind Atlas is live. This new release is realized in cooperation with DTU Wind Energy and The World Bank, it contains three mayor improvements.
The list of datasets expands with three new global layers that help select the right wind turbine model for a specific location. A wind turbine on lowland terrain with a mean wind speed of 6 m/s does not have to endure the same as a turbine on top of a hill, exposed to more extreme wind speeds. Therefore manufacturers design turbines according to IEC classes, set by the International Electrotechnical Commission. This international standard prescribes the wind speeds and gusts a turbine designed for a certain class needs to withstand. The IEC class is calculated on a global scale amongst other things by looking at the the wind speed distribution and turbulence.
Looking at the example of Belgium, most locations are classified as the low speed class (IEC class 3). At the coast and in the Fagne-Famenne and Ardennes on the other hand, more sturdy wind turbines need to be selected, that can withstand higher mean wind speeds and gusts.
Additionally the Energy Yield Calculation tool, that helps users estimate the potential energy yield of a certain type of windturbine on a certain location, is updated. Users can execute the tool for bigger areas thanks to a performance upgrade. Furthermore the result can be downloaded ánd visualised on the map. This helps users without GIS experience to visualise the data.
Finally we introduce a completely new tool: the masking feature. This tool enables users to hide areas that are not interesting, by means of the values of another layer. For instance the figure below shows the wind speeds at the shore of Northern France for the locations with a water depth of the Atlantic Ocean less than 50m. This way the user can only show locations that are interesting for his/her use case.
The Global Wind Atlas is a free, web-based application developed to help policymakers and investors identify potential high-wind areas for wind power generation virtually anywhere in the world, and perform preliminary calculations. The tool facilitates online queries and provides freely downloadable datasets based on the latest input data and modelling methodologies. In addition to a completely revised underlying dataset, the GWA website has been reimagined from the bottom up by Nazka Mapps, under contract to DTU Wind Energy, and funded by Energy Sector Management Assistance Program (ESMAP), a multi-donor trust fund administered by The World Bank and supported by 13 official bilateral donors.