Application of an artificial neural network for predicting the sizing curve of stand-alone photovoltaic system: a case study

Abstract

In this paper, an artificial neural network-based (ANN) prediction of the sizing curve of stand-alone PV systems (SAPV) was developed. Numerical method has been used for constructing the sizing curves for different loss of load probability (LLP) corresponding to 40-sites located in Algeria. The feed-forward neural network (FFNN) is trained considering the geographical coordinate and LLP as inputs, the desired data are the sizing curve represented by CA = f(CS) (i.e., 30 points where taken from each sizing curves). Subsequently, the FFNN is tested with results obtained by the numeric method. The results show that the FFNN model can be applied effectively and afford high accuracy. The coefficient of determination (r) is arranged between 85% and 98% and the mean relative error do not exceed 2%.