Review of Power Point Tracking Techniques for PV Systems: From Maximum Tracking Approaches

This paper comprehensively explores the application of Maximum Power Point Tracking (MPPT) technologies specifically in photovoltaic (PV) systems. The primary objective is to analyze and compare various MPPT algorithms to optimize power output and system reliability in different operational conditions, including standard test conditions (STC) and partial shading conditions (PSC). MPPT methods, such as deterministic particle swarm optimization and incremental conductance, maximize power output by dynamically adjusting PV system parameters. The study highlights the strengths and challenges of MPPT in tracking power under complex scenarios like PSC. A detailed review of conventional, artificial intelligence, optimization, and hybrid algorithms underlines their role in improving convergence speed, efficiency, and system stability. The findings suggest that further enhancing the MPPT algorithms can address diverse energy demands and operational constraints in modern PV systems. This work underscores the importance of advanced MPPT technologies in renewable energy systems and encourages further innovation to enhance their scalability, reliability, and real-world applicability.