Abstract

The paper comprises a solar photovoltaic (PV) system, well furnished with Maximum Power Point Tracking (MPPT) controller to obtain maximum power. There are several MPPT techniques available for assisting the controller, to achieve maximum power. The Artificial Neural Network (ANN) based MPPT algorithm is simple to develop and can provide a faster response with less oscillation. To validate this result a detailed analysis and a comparative assessment have been done between ANN and other conventional Maximum PowerPoint (MPP) algorithms such as Perturb & Observe (P&O) and Incremental Conductance (INC). Moreover, the MPPT algorithms are evolved through MATLAB/SIMULINK software. The obtained results show ANN based MPPT algorithm has a faster execution time, and improved output responses than the remaining examined algorithms, which supports its implementation for dynamic irradiance conditions.

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