Modelling of sizing the photovoltaic system parameters using artificial neural network

The objective of this work is to use an Artificial Neural Network (ANN) to predict the sizing parameters of photovoltaic (PV) system with a minimum of input data. A neural network has been trained by using 54 known sizing parameter data corresponding to 54 locations. In this way the network was trained to accept and even handle a number of unusual cases. Known data were subsequently used to investigate the accuracy of prediction. Prediction with maximum deviation of 6% was obtained. This result indicates that the proposed method can successfully be used for the estimation of sizing parameters data for any locations.