|Category||Cleantech, renewable energy, wind energy|
|Keywords||Small sample observation, wind turbines, wind forecast|
The wind in topographic regions can change dramatically over short distances (hundreds of meters), yet present-day high resolution numerical and statistical models cannot accurately predict variability in the wind field. Therefore, feasibility studies for wind energy projects require years of costly wind measurements due to seasonal and interannual variability, as well as the chaotic nature of the wind.
Our method reduces the observation period to one to two months, saving time and significantly cutting down cost.
The researchers developed a method relying on wind data from existing global reanalysis projects, with just a few months of in situ observations.
The method was tested against real observations in several locations. The results confirmed high precision of the proposed model.
The cost-efficient technology will enhance productivity, accuracy and observation time for wind forecasting. The technology has a wide variety of usage and can be applied to feasibility studies and wind turbines disposition. Companies will benefit from quick and precise analysis that will save them time and money.