In LoTar, a structure or a so-called framework is to be developed, which consistently takes up the first approaches of standardized processing of lidar data from the e-WindLidar project and makes them usable for the entire research community and industry. Within the project, besides the framework with modules for general
data evaluation, the first topic-specific modules are also being developed. In order for industrial companies to benefit from the framework in addition to the scientific target group, two modules will be developed for improved handling of wind profile Doppler lidar data in complex terrain and for turbulence determination.
June 2021 to May 2024
University of Stuttgart, Stuttgart Wind Energy (SWE)
funded by german BMWK
with ~1 Mio€
This questionnaire is about relevant questions regarding the application of Lidar in complex terrain for wind resource assessment. By answering the questions you support the research project LoTar funded by the german Federal Ministry for Economic Affairs and Climate Action (BMWK). The questionnaire will take about 20 min to complete and the information gained will help us greatly in the successful implementation of the project. All participants will be informed directly about the results of the project. The provision and evaluation of the questionnaire is carried out neutrally by FGW. e.V (Fördergesellschaft Windenergie). The questionnaire can be filled out anonymously
- Hofsäß, Martin, Oliver Bischoff, Doron Callies, Dominic Clement, Tobias Klaas-Witt, Carolin Schmitt und Po Wen Cheng. 2023. Statistical comparison of the lidar measurement error of different wind lidar profilers in complex terrain. Zenodo, April. doi:10.5281/zenodo.8378051, https://doi.org/10.5281/zenodo.8378051.
Content at SWE
Design and construction of a modular framework for lidar data correction in complex terrain
Creation of a module for lidar data correction
Understanding and correcting systematic measurement deviations, or errors, of lidar versus mast measurements
Development of a method for the correction of wind profile Doppler lidar measurements based on machine learning techniques
Preparation of terrain data for site classification