Neural network modeling of degradation of solar cells

Recently, there has been substantial interest in solar cells as possible replacements of conventional energy sources, [1, 2]. However, significant light induced degradation of solar cell characteristics such as the conversion efficiency has been observed in the literature, [3,4]. Therefore, there is a need of a model to predict the degradation behavior of solar cells. In this paper, neural network has been used to model the degradation of solar cells. Back propagation algorithm has been used to train the neural network model with different parameters of a solar cell as input and conversion efficiency as output. This model has been developed for experimental data taken from [3] and [4].Some of the data were used for training the network and then the trained network was tested for the rest of the data and computed results were compared with experimental data.