TY  - JOUR
A1  - Bresgott, Jannes
T1  - How can artificial intelligence be used to find areas for wind turbines and solve other challenges associated with wind energy?
JF  - Educational Journal of Renewable Energy Short Reviews
N2  - This article discusses the use of artificial intelligence
in the wind energy industry, particularly in addressing
challenges and optimizing the expansion of renewable
energies in Germany. It highlights the application
of artificial intelligence in wind forecasts and yield
predictions, bird detection, wind turbine and farm
design, condition monitoring, and predictive maintenance.
Additionally, it introduces the “WindGISKI”
research project, which aims to use artificial intelligence
to identify new areas for wind turbines. The
project utilizes a neural network to analyze and predict
flight routes, potentially reducing bird mortality.
The document also emphasizes the potential broader
applications of “WindGISKI” in other fields of activity,
such as land use planning and city development.
Overall, it underscores the significant role of artificial
intelligence in addressing challenges in wind energy
and outlines the potential for artificial intelligence
to drive the expansion of renewable energies while
addressing key obstacles.
T3  - EGU Master Journal of Renewable Energy Short Reviews - 2024_02 
KW  - wind turbine
KW  - WindGISKI
KW  - artificial intelligence
Y1  - 2024
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:836-opus-176393
SP  - 9
EP  - 13
ER  -