Monitoring, diagnosis and localization of the partial shading fault in a photovoltaic power plant with an approach by artificial neural networks

. This paper aims to propose a useful modeling diagnostic method for solar plants. The study was performed on the basis of the localization of the failing panel obtained by an effective comparison of measured output voltages and estimator voltages. The comparison is done with the ideal solar plant using learning approach based on artificial neuronal network (ANN). The partial shading failure was detected by the given equation d² Δ V/dI²>0. The obtained results using MATLAB/Simulink environment show a satisfactory performance in terms of rapidity and precision under variable shading conditions.