LiMeS - Optimierung von LiDAR basierten Messstrategien zur Standortbewertung von Windparks - Satellite based evaluation of weather conditioned LiDAR measurement downtimes [funded by BMWI ] - Status: closed
Wind energy plays a major role in the transition from traditional to renewable energy sources. To further develop the wind energy potential sites located in complex terrain gain more focus. To be able to accuratelly assess the resources as well as the economic efficiency of potential sites, elaborate measurement strategies are needed. In order to keep site development costs low as an alternative to traditional tower based measurements, LiDAR remote sensing techniques may be employed. To evaluate weather conditioned measurement downtimes due to fog/ low stratus, high resolution frequency maps are needed.
This work package of the project will generate fog/ low stratus frequency maps with a resolution of << 1000m. Based on existing low resolution products derived from Meteosat Second Generation satellite data, a high resolution digital elevation model (DEM), land cover data and point measurements a downscaling using a combination of advanced machine learning techniques, spatial and microphysics modelling, will be conducted.
Publications and poster presentations:
- Rösner, B.; Egli, S.; Thies, B.; Beyer, T.; Callies, D.; Pauscher, L. & Bendix, J. (2020): Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning. Energies 13(15), 3859.
- Urbich, I.; Bendix, J. & Müller, R. (2019): The Seamless Solar Radiation (SESORA) Forecast for Solar Surface Irradiance—Method and Validation. Remote Sensing 11(21), 2576.