Title :
Prediction global solar radiation and modeling photovoltaic module based on artificial neural networks
Author :
Miloudi, Lalia ; Acheli, Dalila
Author_Institution :
Dept. Electr. Eng., Univ. M´hamed Bougara, Boumerdès, Algeria
Abstract :
At the beginning of this study a comprehensive literature review on application of artificial neural networks in the various domains of engineering was conducted. Followed by the presentation of artificial neural networks tested for the simulation study and mathematical models for determining global solar radiation. Artificial neural networks are used for the performance estimation the global solar radiation and modeling curves (I-V) of PV module. The structures tested are MLP and RBF. The obtained coefficients of correlation R were very satisfactory, what shows the efficiency of the ANNs to predict the behavior of the photovoltaic systems.
Keywords :
multilayer perceptrons; neural nets; photovoltaic cells; radial basis function networks; solar cells; solar radiation; sunlight; ANN; MLP; PV module; RBF; artificial neural network; global solar radiation prediction; multiple-layer perceptron; performance estimation; photovoltaic module; radial basic function; Artificial neural networks; Mathematical model; Meteorology; Photovoltaic systems; Predictive models; Solar radiation; Artificial neural network (ANNs); characteristic current-tension; global solar radiation; multiple-layer perceptron (MLP); photovoltaic module; radial basic function (RBF);
Conference_Titel :
Control, Engineering & Information Technology (CEIT), 2015 3rd International Conference on
Conference_Location :
Tlemcen
DOI :
10.1109/CEIT.2015.7233111