Estimation of solar power output using ANN model: A case study of a 20-MW solar PV plan at Adrar, Algeria

In this this paper, the Artificial Neural Networks (ANN) model have been exploited for estimation of the energy production of the 20-MW solar photovoltaic (PV) plant installed in Adrar in terms of energy yield, using a minimal knowledge of meteorological parameter include global solar radiation, relative humidity, wind speed, and ambient or air temperature. A comparative analysis has been carried out between the proposed artificial neural networks model and multiple linear regression (MLR) models in PV output estimation and performance is measured based on evaluation indexes, namely mean absolute percentage error, normalized mean absolute error, and normalized root mean square error respectively. Further, the comparison of the ANN model with MLR based models reveals the advantages and supremacy of the ANN model.