Short-term wind power prediction based on lightgbm and meteorological reanalysis

HIGHLIGHTS

• who: Shengli Liao and colleagues from the Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian, China have published the research work: Short-Term Wind Power Prediction Based on LightGBM and Meteorological Reanalysis, in the Journal: Energies 2022, 15, x FOR PEER REVIEW of 26/07/2020
• what: In this paper adopting the ERA5 reanalysis dataset as input a wind power prediction framework is proposed combining light gradient boosting machine (LightGBM) mutual information coefficient (MIC) and nonparametric regression. The results of the study show that the method proposed in this paper can improve the . . .
  

   

  

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