Maximum Power Point TrackingAlgorithms forSolar-PV Systems: A Review

Abstract

The increasing demand for renewable energy solutions has positioned solar PV systems as a vital contributor to the global energy mix. However, the efficiency of  Photovoltaics (PV) systems is challenged by non-linear characteristics, environmental variability, and the limitations of existing Maximum Power Point Tracking (MPPT) algorithms. Traditional MPPT methods, while simple and cost-effective, often fail under highly demanding conditions and partial shading, causing ineficiency performance. Advanced optimization techniques such as Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) have demonstrated higher efficiency and adaptability but require significant computational resources. Hybrid MPPT methods, which combine the advantages of traditional and advanced techniques, have emerged as a promising solution to enhance scalability, reduce oscillations, and improve tracking accuracy. This review examines these MPPT strategies, categorizing them and highlighting their strengths, limitations, and future potential.