Maximum Power Point Tracking (MPPT) using Artificial Neural Networks (ANNs)

Hadjab, Moufdi; Berrah, Smail; Hadji, Souad

JOURNAL OF RENEWABLE ENERGY SYSTEMS AND MANAGEMENT
Volume 1, Numéro 2, Pages 1-8
2026-06-30

Maximum Power Point Tracking (mppt) Using Artificial Neural Networks (anns)

Authors : Hadjab Moufdi . Berrah Smail . Hadji Souad .

Abstract

ABSTRACT – The aim of this work is to optimize the operation of photovoltaic generators. Photovoltaic (PV) solar energy is produced through the direct conversion of solar radiation into electrical energy using photovoltaic cells. These cells are made of semiconductor materials that are sensitive to solar radiation wavelengths and temperature. By interconnecting several PV cells in series and/or parallel, a photovoltaic generator (PVG) is formed, characterized by a nonlinear current–voltage I(V) curve containing a maximum power point (MPP) under specific operating conditions. This work focuses on maximum power point tracking (MPPT) using two techniques. The first technique is the classical Perturb and Observe (P&O) method, while the second is based on artificial intelligence (AI) using an artificial neural network (ANN).