article·Applied Energy·Nov 29, 2019Closed access

A hybrid deep learning model for short-term PV power forecasting

PLPengtao LiKZKaile ZhouCorresponding authorXLXinhui LuSYShanlin Yang

Ministry of Education of the People's Republic of China · Hefei University of Technology

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Abstract

No abstract available for this paper.

Citation impact

492
total citations
FWCI
21.76
Percentile
100%
References
55
Citations per year

Authors

4
  • PL
    Pengtao Li

    Ministry of Education of the People's Republic of China, Hefei University of Technology

  • KZ
    Kaile ZhouCorresponding

    Ministry of Education of the People's Republic of China, Hefei University of Technology

  • XL
    Xinhui Lu

    Hefei University of Technology, Ministry of Education of the People's Republic of China

  • SY
    Shanlin Yang

    Ministry of Education of the People's Republic of China, Hefei University of Technology

Topics & keywords

Topics
  • Primary topicSolar Radiation and Photovoltaics100%
  • Energy Load and Power Forecasting100%
  • Photovoltaic System Optimization Techniques100%
Keywords
  • Deep learning
  • Computer science
  • Artificial intelligence
  • Weighting
  • Perceptron
  • Artificial neural network
  • Electric power system
  • Recurrent neural network
No related works found for this paper.

Funding

  • NN
    National Natural Science Foundation of China
    Awards: 71822104, 71521001
  • FR
    Fundamental Research Funds for the Central Universities
    Award: JZ2018HGPA0271