An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm

An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm

Wind power, as a clean and renewable energy source, plays an increasingly important role in the global transition to low-carbon energy systems. However, its inherent volatility and unpredictability pose challenges for accurate short-term prediction. This study proposes an ultra-short-term wind power...

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Bibliographic Details
Main Authors: Xuehui Wang, Yongsheng Wang, Yongsheng Qi, Jiajing Gao, Fan Yang, Jiaxuan Lu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Energies
Subjects:
wind power prediction
sliding time window
K-line
financial technology indicators
power variation feature
XGBoost
Online Access:https://www.mdpi.com/1996-1073/18/12/3069
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