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Because the existing method does not consider the difference of wind power output characteristics under different meteorological conditions, a short-term wind power forecasting method based on different meteorological scenarios is proposed. Meteorological factors affecting wind power were processed, and AP clustering was used to aggregate and classify numerical weather forecast, and typical meteorological scenarios were screened out. Secondly, based on different meteorological scenarios, the combined prediction model is constructed. Finally, the prediction method is verified by the actual wind farm data in Shandong Province. Finally, it shows that the method is feasible.

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Short-Term Combined Power Prediction of Wind Power Based on Different Meteorological Scenarios

  • 会议论文

  • 发表日期：

    2025年

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  • Fei Wang,
  • Liping Liu,
  • Chen Xing,
  • Wenhao Gao,
  • Xinhua Chen,
  • Liqun Han,
  • Yuanhe Zhang

摘要

Because the existing method does not consider the difference of wind power output characteristics under different meteorological conditions, a short-term wind power forecasting method based on different meteorological scenarios is proposed. Meteorological factors affecting wind power were processed, and AP clustering was used to aggregate and classify numerical weather forecast, and typical meteorological scenarios were screened out. Secondly, based on different meteorological scenarios, the combined prediction model is constructed. Finally, the prediction method is verified by the actual wind farm data in Shandong Province. Finally, it shows that the method is feasible.