Joint project: WINDOW - Development of a Lidar- and AI-supported method for large-scale measurement of the wind field inside and outside offshore wind farms
Subproject: Development and test of methods for the generation of a lidar- and AI-supported wind field on the basis of measured data
Wind energy is currently the largest electricity producer in Germany. In order to further increase wind farm performance and to meet the increased requirements from the perspective of grid and market integration, improved procedures for monitoring and operating wind farms are necessary. This is particularly true for offshore wind farms. Hence, a continuous wind farm monitoring is necessary. However, this requires precise real-time information about the wind conditions in and around the respective wind farm in order to analyse the farm behaviour at any time and to enable technical and economic optimisations. Using a combination of innovative lidar measurement technology and artificial intelligence methods, a procedure is to be developed within the project that provides a high-resolution wind field in and around offshore wind farms with high cost efficiency and accuracy. Such a wind field enables, for example, continuous measurement of the power curve as well as evaluations of the wind farm's performance. The focus of the section Integrated Energy Systems at the University of Kassel in the project is on the development and use of machine learning methods to generate and adapt the wind field.
Federal Ministry for Economic Affairs and Climate Action
11/2018 - 10/2021
Fraunhofer IEE, EnBW
|Alexander Basse, Dr. Martin Wiemer, Dr. Doron Callies