@article{Bresgott2024,
  author    = {Bresgott, Jannes},
  title     = {How can artificial intelligence be used to find areas for wind turbines and solve other challenges associated with wind energy?},
  series = {Educational Journal of Renewable Energy Short Reviews},
  journal   = {Educational Journal of Renewable Energy Short Reviews},
  doi       = {10.25974/ren_rev_2024_02},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-176393},
  pages     = {9 -- 13},
  year      = {2024},
  abstract  = {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.},
  language  = {en}
}