Abstract
Abstract The expanding need for electricity has stimulated research and development of novel supply sources for energy production, conversion, and storage. Many studies are being done to increase the effectiveness of conversion systems as renewable energy is integrated into power networks on a larger scale. The global challenge is to minimize manufacturing costs and increase the use of sustainable resources. In this sense, photovoltaics is viewed as a particularly promising source due to the low cost of implementation and the wide range of applications it could be used for. This research focuses on the analysis, modeling, and simulation of a smart controller for a step-up converter that uses an artificial neural network (ANN) as a maximum power point tracking (MPPT) technique to provide maximum power. The proposed ANN-based algorithm is performed in Matlab/Simulink software, and its effectiveness has been demonstrated under varying climatic conditions.
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