Maximizing Solar Panel Efficiency in Partial Shade: The Improved POA Solution for MPPT

This paper presents an innovative approach to improving Maximum Power Point Tracking (MPPT) in solar photovoltaic (PV) systems affected by partial shading, a common challenge that significantly reduces efficiency. Our research focuses on enhancing the Pelican Optimization Algorithm (POA), a promising tool in solar energy optimization, to better tackle the efficiency drop observed under shaded conditions. The enhancements to the POA involve the integration of advanced adaptive mechanisms that enable more precise response to the fluctuating irradiance patterns typical of partially shaded environments. This revised version of the POA demonstrates remarkable adaptability and precision in identifying and tracking the maximum power point, significantly outperforming its original iteration. The methodology of this study encompasses a series of rigorous simulations and real-world testing scenarios, designed to evaluate the POA's performance under various degrees and patterns of shading. The results show a notable improvement in efficiency, with the enhanced POA maintaining high levels of energy capture even in suboptimal sunlight conditions. Additionally, the improved algorithm exhibits robustness against the rapid changes in irradiance, which is characteristic of partially shaded solar PV systems. Our findings underscore the potential of the enhanced POA as a robust, adaptive solution for optimizing solar energy collection, offering significant benefits for solar installations in geographies prone to shading. This work not only contributes to the field of renewable energy optimization but also provides valuable insights for the development of more resilient and efficient solar energy systems.

@article{Mhanni2024,
  title     = {Maximizing Solar Panel Efficiency in Partial Shade: The Improved POA Solution for MPPT},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {3},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Youssef Mhanni and Youssef Lagmich},
  doi       = {10.14569/IJACSA.2024.0150397},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150397}
}