Modeling of a Photovoltaic Array with Maximum Power Point Tracking Using Neural Networks

Autor: Mohammed Bouzidi, Harrouz Abdelkader, Smail Mansouri, Virgil Dumbrava
Rok vydání: 2022
Předmět:
Zdroj: Applied Mechanics and Materials. 905:53-64
ISSN: 1662-7482
DOI: 10.4028/p-ndl3bi
Popis: In this paper, we present a modeling of the photovoltaic array in order to tracking the maximum power point (MPPT) using a soft computing approach based on artificial neural network, The maximum power point tracking MPPT play a crucial role in photovoltaic systems for their ability to maximize the power output under varying conditions; The photovoltaic array modeled and implemented in matlab simulink environnement using the conventional perturb and observe algorithm for multiple ranges under varying temperatures and irradiances levels, a feed forward neural network collect the training data from the photovoltaic array simulink model, after the training process check, the neural network model tested with new temperatures and irradiance data to predict the maximum power point of the photovoltaic array, The developed neural network model shown an interesting results compared to simulink model based on classic perturb and observe algorithm.
Databáze: OpenAIRE