Artificial Neural Network-based Modeling And Monitoring Of Photovoltaic Generator

Résumé: In this paper, an artificial neural network based-model (ANNBM) is introduced for partial shading detection losses in photovoltaic (PV) panel. A Multilayer Perceptron (MLP) is used to estimate the electrical outputs (current and voltage) of the photovoltaic module using the external meteorological data: solar irradiation G (W/m2) and the module temperature T (°C). Firstly, a database of the BP150SX photovoltaic module operating without any defect has been used to train the considered MLP. Subsequently, in the first case of this study, the developed model is used to estimate the output current and voltage of the PV module considering the partial shading effect. Results confirm the good ability of the ANNBM to detect the partial shading effect in the photovoltaic module with logical accuracy. The proposed strategy could also be used for the online monitoring and supervision of PV modules.

Publié dans la revue: Mediterranean Journal of Modeling and Simulation