"Numerous methods exist and were developed for global radiation forecasting. The two most popular types are the numerical weather predictions (NWP) and the predictions using stochastic approaches. This article presents a methodology for determining the best method to use, according to a rule related to the spatial resolution, temporal step and location. We propose to compute a parameter noted constructed in part from the mutual information which is a quantity that measures the mutual dependence of two variables. Both of these are calculated with the objective to establish the more relevant method between NWP and stochastic models concerning the current problem."
Outre l'aspect sélection, nous montrerons aussi une nouvelle méthodologie d'inclinaison du rayonnement global utilisant les ANN, ci-dessous le résumé:
"Calculation of solar global irradiation on tilted planes from horizontal global one is difficult when the time step is small.We used an Artificial Neural Network (ANN) to realize this conversion at a 5-min time step for solar irradiation data of Bouzareah (Algeria). The ANN is developed and optimized on the basis of two years of solar data (1.5 year or training and 0.5 year for test) and the accuracy of the optimal configuration is around 8% for the nRMSE."