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A Data-Driven Platform for Predicting the Position of Future Wind Turbines

  • Olivier ParisotEmail author
Conference paper
  • 158 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12341)

Abstract

Optimal location of wind turbines is a complex decision problem involving environmental, performance, societal and other parameter. This paper investigates the domain by describing WindturbinesPlanner: by providing machine learning models trained on various data sources, the platform can help to anticipate the potential location of future onshore wind turbines in Luxembourg, France, Belgium and Germany.

Keywords

Wind turbines Predictive analytics Visualisation 

Notes

Acknowledgments

This work was carried out as part of the FEDER Data Analytics Platform project (http://tiny.cc/feder-dap-project). Special thanks to Anne Hendrick for her support.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Luxembourg Institute of Science and Technology (LIST)Esch-sur-AlzetteLuxembourg

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