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The Prediction of a Floating Photovoltaic Generation Utilizing RNN

  • The Transactions of The Korean Institute of Electrical Engineers
  • Korean Institute of Electrical Engineers
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Renewable energy has advantages in environmental aspects such as greenhouse gas reduction and fine dust reduction, but the stability of the power system is lowered due to the variability & uncertainty of renewable energy sources. Therefore, it is important to predict the amount of generation of renewable energy, which can contribute to system stabilization. In order to predict the power generation of floating photovoltaic(FPV), the generation amount of 500㎾ FPV and meteorological data were used to predict the power generation through the Recurrent Neural Network(RNN). To perform appropriate prediction, identifying the correlation between variables, removing multicollinearity, handling missing values properly are performed and the amount of power generation is predicted through appropriate RNN. In addition, it is analyzed how the influence of wind affects the amount of power generation of FPV

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DOI
10.5370/kiee.2022.71.8.1126
OpenAlex
W4293083125
Document type
article
Language
EN
Source
The Transactions of The Korean Institute of Electrical Engineers
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