Comparative Assessment and Benchmarking of Metaheuristic Algorithms for Dynamic Photovoltaic Array Reconfiguration Under Diverse Shading Environments

The solar photovoltaic (PV) installations, which are essential for renewable energy systems, are vulnerable to partial shading, resulting in considerable power losses and operational inefficiencies. The dynamic reconfiguration of PV arrays has become an effective strategy to mitigate these effects by adaptively modifying the array topology to optimize power output. This paper presents a detailed comparative analysis of dynamic PV array reconfigurations for a 6 × 6 total-cross-tied array under various operating conditions. The comparative analysis includes 10 recent metaheuristics that have shown performance in complex optimization problems across different domains. The proposed methodology assesses the effectiveness of each algorithm in identifying optimal reconfiguration patterns, enhancing power extraction, and reducing mismatch losses across both uniform and multiple partial shading conditions. Simulation results prove the strengths and robustness of each algorithm, providing detailed insights into their appropriateness for real-time adaptive PV systems. The findings clarify the potential of metaheuristic-driven dynamic reconfigurations to improve PV system performance and establish a basis for choosing the most effective algorithmic approach in practical applications.