A short-term photovoltaic power forecasting method combining a deep learning model with trend feature extraction and feature selection

HIGHLIGHTS

• who: Kaitong Wu and collaborators from the Department of Electrical Engineering, School of Automation, Guangdong University of Technology have published the paper: A Short-Term Photovoltaic Power Forecasting Method Combining a Deep Learning Model with Trend Feature Extraction and Feature Selection, in the Journal: Energies 2022, 15, x FOR PEER REVIEW of /2022/
• what: In this paper a combination deep learning forecasting method based on variational mode decomposition (VMD) a fast correlation-based filter (FCBF) and bidirectional long short-term memory (BiLSTM) network is developed to minimize PV power forecasting error. Two sets of experiments . . .
  

   

  

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