Design of an artificial intelligence model for predicting solar photovoltaic cells potential

Abstract

In apparent, the artificial intelligence model is employed to predict the potential for unknown area. The Artificial Neural Network (ANN) consists of three layers such as the input layer, hidden layer and the output layer. Each five hidden layer of the artificial neural network consists of ten neurons. The various six types of training algorithm is applied in Artificial Neural Network (ANN) such as Scaled Conjugate Gradient (SCG), Resilient Algorithm (RA), Levenberg-Marquardt algorithm (LMA), Conjugate Gradient Algorithm (CGA), Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and Bayesian Regularization (BR) Algorithm. In these algorithms Levenberg-Marquardt algorithm (LMA) shows better in performance. In this research three input parameters are given to input layer namely solar irradiation, wind speed and temperature it has been processed in hidden layer to reveal output as voltage and current.