Short-term wind and solar power prediction based on feature selection and improved long-and short-term time-series networks

HIGHLIGHTS

• who: Selection and colleagues from the China Gridcom Co, Ltd, State Grid Information and Telecommunication Group, Shenzhen, China College of Energy and Electrical Engineering, Hohai University, Nanjing, China have published the research: Short-Term Wind and Solar Power Prediction Based on Feature Selection and Improved Long-and Short-Term Time-Series Networks, in the Journal: Mathematical Problems in Engineering 70 of 19/07/2022
• what: Although feature selection has been used to improve the predicted performances for wind and solar power forecasting, most existing studies focused on a single feature selection method such that a . . .
  

   

  

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