A short-term wind power prediction method based on dynamic and static feature fusion mining
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DOI: 10.1016/j.energy.2023.128226
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Cited by:
- Zhigang Liu & Jin Wang & Tao Tao & Ziyun Zhang & Siyi Chen & Yang Yi & Shuang Han & Yongqian Liu, 2023. "Wave Power Prediction Based on Seasonal and Trend Decomposition Using Locally Weighted Scatterplot Smoothing and Dual-Channel Seq2Seq Model," Energies, MDPI, vol. 16(22), pages 1-17, November.
- Yang, Mao & Guo, Yunfeng & Huang, Yutong, 2023. "Wind power ultra-short-term prediction method based on NWP wind speed correction and double clustering division of transitional weather process," Energy, Elsevier, vol. 282(C).
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Keywords
Hort-term wind power prediction; Deep residual network; Dynamic and static feature mining; Error evaluation;All these keywords.
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