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  • 标题:Hybrid Short-Term Wind Power Prediction Based on Markov Chain
  • 本地全文:下载
  • 作者:Liangsong Zhou ; Xiaotian Zhou ; Hao Liang
  • 期刊名称:Frontiers in Energy Research
  • 电子版ISSN:2296-598X
  • 出版年度:2022
  • 卷号:10
  • DOI:10.3389/fenrg.2022.899692
  • 语种:English
  • 出版社:Frontiers Media S.A.
  • 摘要:This article proposes a combined prediction method based on the Markov chain to realize precise short-term wind power predictions. First, three chaotic models are proposed for the prediction of chaotic time series, which can master physical principles in wind power processes and guide long-term prediction. Then, considering a mechanism switching between different physical models via a Markov chain, a combined model is constructed. Finally, the industrial data from a Chinese wind farm were taken as a study case, and the results validated the feasibility and superiority of the proposed prediction method.
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