Tackling Photovoltaic (PV) Estimation Challenges: An Innovative AOA Variant for Improved Accuracy and Robustness

Optimizing photovoltaic (PV) cell/module modeling is key to advancing solar power and achieving net zero carbon goals.Challenges in accurate PV parameter estimation arise from environmental variability, aging, and incomplete manufacturer data.Traditional Arithmetic Optimization Algorithm (AOA) often struggles with premature convergence due to imbalanced exploration and exploitation.This paper presents an enhanced AOA variant, incorporating chaotic maps and oppositional-based learning to better balance the optimization process.Our extensive simulations show that this improved AOA variant significantly enhances accuracy and robustness in PV cell/module parameter estimation compared to the conventional method.