An Approach Based on Golden Eagle Optimization Algorithm for Maximum Power Point Tracking of PV Panel Under Partial Shading Conditions

This study introduces an innovative Maximum Power Point Tracking (MPPT) technique utilizing the Golden Eagle Optimization (GEO) method, specifically designed to enhance the efficiency of photovoltaic (PV) systems under partial shading conditions. Unlike traditional MPPT approaches that struggle with local peaks in power-voltage curves caused by shading, the GEO method leverages the hunting behavior-inspired algorithm to accurately locate the global maximum power point (GMPP). The effectiveness of the GEO MPPT technique is demonstrated through extensive simulations across three diverse case scenarios, each representing different partial shading patterns. In all scenarios, the GEO method outperforms conventional MPPT techniques, showcasing its adaptability and superior performance in challenging conditions. The successful implementation of GEO MPPT leads to substantial improvements in PV panel energy extraction efficiency, even when faced with the complexities of partial shading. This research contributes significantly to the advancement of solar PV systems, enhancing their reliability and performance in real-world environments. By mitigating the impact of partial shading, this work promotes the wider adoption of solar energy as a viable and sustainable power solution.