Graph Neural Networks in Wind Power Forecasting

Javier Castellano, Ignacio Villanueva
6/30/2025
cs.LGeess.SY

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Abstract

We study the applicability of GNNs to the problem of wind energy forecasting. We find that certain architectures achieve performance comparable to our best CNN-based benchmark. The study is conducted on three wind power facilities using five years of historical data. Numerical Weather Prediction (NWP) variables were used as predictors, and models were evaluated on a 24 to 36 hour ahead test horizon.

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Cite this paper

@article{castellano2025graph,
  title  = {Graph Neural Networks in Wind Power Forecasting},
  author = {Javier Castellano and Ignacio Villanueva},
  year   = {2025},
  eprint = {2507.00105},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.00105v1}
}

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