Intelligent Series–Parallel Photovoltaic Array Reconfiguration Using Harris Hawks Optimization for Enhanced Energy Extraction Under Shading Patterns

The increasing penetration of photovoltaic (PV) systems as a renewable energy source faces major challenges. These challenges are due to partial shading conditions causing mismatch losses and the emergence of multiple local peaks in the power–voltage characteristic curve. In order to address this problem, this study proposes an intelligent reconfiguration method. The method is based on the Harris Hawks Optimization algorithm on Series–Parallel type PV arrays. It aims to improve power extraction efficiency without changing the physical structure of the array. The HHO algorithm determines the optimal combination of connections between the upper and the lower sub-substrings by using a switching matrix controller. This controller functions to balance the current and the voltage distribution between strings under non-uniform irradiation conditions. The PV system model has been simulated by using Simulink, in configurations of 6×5, with shadow patterns. The simulation results have showed that the HHO-based reconfiguration method has increased the average Fill Factor from 0.55 to 0.67, has reduced power loss by up to 22%, and has increased power efficiency by 7.21%–15.12% compared to conventional SP configurations. Thus, the proposed method has proven to be effective, adaptable, and realistic for enhancing the performance of PV systems under partial shading conditions, with minimal implementation complexity.