Abstract
In order to contribute to the integration of photovoltaic renewable energy into power system, this paper addresses the problem of forecasting solar irradiance or Global Horizontal Irradiation (GHI). The collection, adjustment and processing of meteorological data used as input is carried out, in addition various Deep Neural Networks (DNN) models are implemented and analyzed, among which are the Artificial Neural Networks (ANN) of type as Transformer, LSTM, GRU, and mixed between Convolutional ANN (CNN)-LSTM, and CNN-GRU. These ANN variants are implemented, and a comparative study are made. Finally, the results obtained show that the ANN transformer has less error in the GHI forecasting.
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