A New MPPT-based ANN for Photovoltaic System under Partial Shading Conditions

In solar photovoltaic system, tracking the maximum power point (MPP) is challenging task due to varying climatic conditions. Moreover, the tracking algorithm becomes more complicated under the condition of partial shading due to the presence of multiple peaks in the power voltage characteristics. This paper introduces a novel method to track the global maximum power point under partially shaded conditions. The method combines an artificial neural network controller with a scanning algorithm. The PV system along with the proposed MPPT algorithm was simulated using Matlab/Simulink environment. The simulated system was evaluated under uniform and non-uniform irradiation conditions. For comparison, an improved variable step P&O with global scanning (PO&GS) and incremental conductance controller based on a fuzzy duty cycle change estimator (FLE) with direct control were used and the results show that the proposed approach is effective in tracking the MPP and presents fast response time.