Research Project STRAIGHT

STRAIGHT – Increasing Quality and Efficiency in Yield Estimation for Wind Farms

Partners anemos Gesellschaft für Umweltmeteorologie mbH, University of Kassel, ABO Wind AG, DKB (Deutsche Kreditbank AG), EnBW (Energie Baden-Württemberg AG), ENERTRAG SE, FGW (Fördergesellschaft für Windenergie und andere Dezentrale Energien e.V.)
Funding Federal Ministry for Economic Affairs and Climate Action
Duration 01.06.2023 – 31.05.2026
Researchers Alexander Basse, Paul Kühn,  Doron Callies, Arne Füsers, Maximilian Kleebauer, Maximilian Pfennig

Project Description

In order to achieve the ambitious goals for wind energy expansion in Germany, it is necessary to not only accelerate approval procedures, but also to make the technical and economic aspects of wind farm planning more efficient. At present, this typically takes around one and a half years.

A key factor in accelerating wind farm planning would be a reduced measurement period. Therefore, a main goal of the project is the qualification (bankability) of short-term measurements for yield estimation, or even wind-potential analyses without measurement. Besides acceleration, a significantly higher cost efficiency can be attained: By shortening the measurement period to six or three months instead of the usual year, a cost reduction of about 40% or 65% can be achieved.

Since a smaller amount of data would be available in such a case, special requirements arise for yield estimation, for example ensuring a high-quality data basis for both measured and long-term data (usually weather model data), which are then used for long-term classification - the so-called long-term correction - of the measured data. On the other hand, the procedures and processes, e.g., for calculating the energetic losses, must be improved and further developed. This is the only way to achieve high accuracy (low uncertainty) despite a reduced data basis.


The following innovations and goals are being pursued in detail within the project:

  • Development of a procedure for the improvement of the measurement-data basis (filling of data gaps)
  • Improvement of weather models and reanalysis data (based on the anemos wind atlas)
  • Development of an AI-procedure for the long-term correction of short-term wind measurements to account for seasonal effects
  • Improvement of the loss calculation regarding daily and seasonally dependent losses (e.g., species protection, noise-reduced operation, shadow flicker)
  • Improvement of the loss calculation regarding shading losses within the wind farm
  • Development of a site-specific correction of the power curve to account for effects such as turbulence or oblique flow on turbine yields
  • Improvement and use of geodata for the determination of local temporal harshness and or change

In addition, methods for the objectified determination of all relevant partial uncertainties are to be developed.

The methods developed in the project will be combined in such a way that a highly automated estimation of the yields, including uncertainties, is achieved (result reports). In addition, Fraunhofer IEE combines the methods in such a way that a yield estimation on a regional level is possible. This in turn then allows for the calculation of potential studies which would support the large-scale planning of both the industry and the political sector.