Solar resource estimation using artificial neural networks and comparison with other correlation models

Artificial Neural Network (ANN) based models for estimation of monthly mean daily and hourly values of solar global radiation are presented in this paper. Solar radiation data from 13 stations spread over India around the year have been used for training and testing the ANN. The solar radiation data from 11 locations (six from South India and five from North India) were used for training the neural networks and data from the remaining two locations (one each from South India and North India) were used for testing the estimated values. The results of the ANN model have been compared with other empirical regression models. The solar radiation estimations by ANN are in good agreement with the actual values and are superior to those of other available models. The maximum mean absolute relative deviation of predicted hourly global radiation tested is 4.07%. The results indicate that the ANN model shows promise for evaluating solar global radiation possibilities at the places where monitoring stations are not established