Optimizing Photovoltaic Array Performance Using a Hybrid PSO–ANN MPPT Algorithm

Abstract

In this study, we present a novel method for increasing the performance of photovoltaic (PV) arrays by utilizing a hybrid optimization algorithm involving Particle Swarm Optimization and Artificial Neural Networks (PSO-ANN) to track maximum power points. Increasing global energy challenges have resulted in an increase in demand for efficient solar energy conversion techniques. The proposed hybrid MPPT algorithm combines the strengths of both PSO and ANN to overcome the limitations of traditional MPPT methods, which often have difficulty adapting to changing environments. As a result of this research, PV systems will yield significantly more energy, leading to more sustainable and reliable renewable energy generation.