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.