Feature extraction of numerical weather prediction results toward reliable wind power prediction

Kazutoshi Higashiyama, Yu Fujimoto, Yasuhiro Hayashi

研究成果: Conference contribution

2 引用 (Scopus)

抄録

Wind power prediction is necessary for stable operation of a power grid under the introduction of significant wind power generation. Wind power prediction approaches based on the results of numerical weather prediction (NWP) have been developed successfully in recent years. However, the high dimensionality of NWP results can be a major obstacle when training models. This paper proposes a feature extraction scheme based on convolutional neural networks to compress high-dimensional NWP results by deriving critically important low-dimensional information for wind power prediction. The experimental results show that the proposed feature extractor can contribute to the improvement of wind power prediction accuracy.

元の言語English
ホスト出版物のタイトル2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1-6
ページ数6
2018-January
ISBN(電子版)9781538619537
DOI
出版物ステータスPublished - 2018 1 16
イベント2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Torino, Italy
継続期間: 2017 9 262017 9 29

Other

Other2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017
Italy
Torino
期間17/9/2617/9/29

Fingerprint

Wind power
Feature extraction
Power generation
Neural networks

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

これを引用

Higashiyama, K., Fujimoto, Y., & Hayashi, Y. (2018). Feature extraction of numerical weather prediction results toward reliable wind power prediction. : 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings (巻 2018-January, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGTEurope.2017.8260216

Feature extraction of numerical weather prediction results toward reliable wind power prediction. / Higashiyama, Kazutoshi; Fujimoto, Yu; Hayashi, Yasuhiro.

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. 巻 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.

研究成果: Conference contribution

Higashiyama, K, Fujimoto, Y & Hayashi, Y 2018, Feature extraction of numerical weather prediction results toward reliable wind power prediction. : 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. 巻. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017, Torino, Italy, 17/9/26. https://doi.org/10.1109/ISGTEurope.2017.8260216
Higashiyama K, Fujimoto Y, Hayashi Y. Feature extraction of numerical weather prediction results toward reliable wind power prediction. : 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. 巻 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6 https://doi.org/10.1109/ISGTEurope.2017.8260216
Higashiyama, Kazutoshi ; Fujimoto, Yu ; Hayashi, Yasuhiro. / Feature extraction of numerical weather prediction results toward reliable wind power prediction. 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. 巻 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6
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