Comparative Study of Different MPPT Algorithms for Photovoltaic Systems under Partial Shading Conditions

We are interested in tracking the maximum power of a partially shaded photovoltaic (PV) system, using a DC-DC converter as the power conditioning unit. To meet this objective, many structures of power converters and different conventional and non-conventional control methods have been proposed, studied, and optimized. Among them the conventional method of perturbation and observation (P&O), and the unconventional method of particle swarm optimization (PSO), which remain the most known MPPT techniques due to their simplicity. But their dynamic response and accuracy remain low compared to other optimized methods. This work presents a comparative analysis between five control strategies: i) the conventional (P&O) method with fixed iteration step, ii) variable step (VSP&O), iii) modified adjustable step (imVSP&O). iv) The improved perturbation and global scanning and observation method (VSPO&GS). V) The unconventional method based on artificial intelligence PSO. The simulation results of these algorithms are analyzed and compared in the Matlab/Simulink environment in order to show the performances and the limits of each method in the tracking of the point of maximum power.