Energy yield estimation of thin-film photovoltaic plants by using physical approach and artificial neural networks

In order to verify the effectiveness of the implemented approaches, measured and estimated data have been compared and errors have been calculated by means of different statistical coefficients. Results demonstrate that the HPANN approach allows a more precise estimation of the ac energy yield, obtaining, in the worst case, values of Relative Root Mean Square Error less than 10%.