• Mritunjay piplaha
• Dr. Anula Khare
• Mr. Vasant Acharya

The increasing global demand for clean and sustainable energy has driven significant advancements in photovoltaic (PV) technology. This paper presents a comprehensive study of solar PV systems, detailing their fundamental components such as photovoltaic modules, DC-DC converters, controllers, and energy storage units and their role in optimizing energy conversion efficiency. A major focus is placed on Maximum Power Point Tracking (MPPT) techniques, highlighting both classical and advanced intelligent control strategies. Recent developments in machine learning-based MPPT methods are explored, emphasizing their potential to enhance system adaptability and performance under varying environmental conditions. The study also addresses current operational challenges faced by PV systems, including environmental variability, energy storage integration, and system reliability. A detailed literature review categorizes recent innovations, evaluates their effectiveness, and identifies unresolved limitations. Finally, the paper outlines future research directions, particularly the need for isolated DC-DC converter topologies and intelligent optimization strategies to improve efficiency, fault tolerance, and long-term stability in PV systems. This work aims to guide researchers and engineers in developing more robust, adaptive, and intelligent PV energy solutions.

PV system, ML, MPPT, DC-DC CONVERTERS

"A Comprehensive Review of Development of An Intelligent Layer to Improve Solar Power System Performance", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.j697-j705, May-2025, Available :http://www.jetir.org/papers/JETIR2505A62.pdf

"A Comprehensive Review of Development of An Intelligent Layer to Improve Solar Power System Performance", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppj697-j705, May-2025, Available at : http://www.jetir.org/papers/JETIR2505A62.pdf