881 / 2019-04-30 11:54:43
Long-term Solar Radiation Forecasting using a Deep Learning Approach-GRUs
Deep Learning,Renewable Energy,Solar Radiation Forecasting,gated recurrent unit,Long-short term memory,Microgrids
全文录用
Muhammad Aslam / Myongji University
Hyung Seung Kim / Myongji University
Seung Jae Lee / Myongji University
Jae-Myeong Lee / Myongji University
Sugwon Hong / Myongji University
Eui Hyang Lee / Next-Generation Power Technology Center (NPTC)
A long-term solar generation forecasting is an important issue in a microgrid design. Solar generation forecasting mainly depends on solar radiation forecasting. In this paper, Deep Learning approach-GRUs (Gated Recurrent Units) is proposed for forecasting of a year-ahead hourly and daily solar radiation. The proposed GRU model is compared with the state of the art methods like Long Short Term Memory (LSTM) model and numerical model. Its effectiveness for long-term solar radiation forecasting over other methods is verified.
重要日期
  • 会议日期

    10月21日

    2019

    10月24日

    2019

  • 10月13日 2019

    摘要录用通知日期

  • 10月13日 2019

    初稿截稿日期

  • 10月14日 2019

    初稿录用通知日期

  • 10月24日 2019

    注册截止日期

  • 10月29日 2019

    终稿截稿日期

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