Application of BERT in Wind Power Forecasting-Teletraan's Solution in Baidu KDD Cup 2022

Longxing Tan, Hongying Yue
7/18/2023
cs.LGeess.SP

Official code: LongxingTan/KDDCup2022-WPF (155 stars, last commit 2023-09-21).

Abstract

Nowadays, wind energy has drawn increasing attention as its important role in carbon neutrality and sustainable development. When wind power is integrated into the power grid, precise forecasting is necessary for the sustainability and security of the system. However, the unpredictable nature and long sequence prediction make it especially challenging. In this technical report, we introduce the BERT model applied for Baidu KDD Cup 2022, and the daily fluctuation is added by post-processing to make the predicted results in line with daily periodicity. Our solution achieves 3rd place of 2490 teams. The code is released athttps://github.com/LongxingTan/KDD2022-Baidu

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Code Implementations(1)

LongxingTan/KDDCup2022-WPFOfficial71%

3rd Place Solution of KDD Cup 2022-Spatial Dynamic Wind Power Forecasting

15524Shell, PythonJul 21, 20223 years ago
bertdeep-learningkdd2022kddcupspatio-temporal+2 more

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Cite this paper

@article{tan2023application,
  title  = {Application of BERT in Wind Power Forecasting-Teletraan's Solution in Baidu KDD Cup 2022},
  author = {Longxing Tan and Hongying Yue},
  year   = {2023},
  eprint = {2307.09248},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.09248v1}
}

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