Optimal Energy Tracking in a Solar Power System Utilizing Synthetic Neural Network

Abstract

In this particular study, an artificial neural network (ANN) was utilized to effectively extract the maximum power from a photovoltaic (PV) installation. The primary objective was to assess the performance of the ANN in comparison to the commonly used perturb and observe (P&O) technique, especially when faced with varying climatic conditions. The results of the study unequivocally demonstrated the superiority of artificial intelligence, specifically the ANN, in enhancing the optimization of PV power. When compared to the traditional P&O technique, the ANN consistently outperformed it in terms of accurately tracking the maximum power point under different climatic conditions. This highlights the remarkable capabilities of artificial intelligence in improving the efficiency and performance of PV systems.