Rapid indirect self-adaptive P&O technique with enhanced scanning feature for PV systems during complex partial shading with repeatable radiation conditions

Conventional maximum power point tracking (MPPT) techniques often fail to accurately track the global maximum power (GMP) for photovoltaic (PV) systems under partial shading circumstances (PSCs). Furthermore, existing GMPPT strategies frequently suffer from slow convergence or complete failure when shading patterns vary abruptly and dynamically. To overcome these limitations, this study proposes an enhanced adaptive Perturb and Observe (P&O) algorithm integrated with a Proportional-Integral-Derivative (PID) controller, designed to achieve rapid and robust GMPP tracking under varying PSC scenarios. The inclusion of the PID controller significantly improves the dynamic response of the PV system, resulting in faster convergence and reduced tracking time. The proposed method extends and refines traditional approaches by integrating a mechanism for PSC detection and targeted GMPP estimation, thereby minimizing unnecessary search iterations and enhancing system efficiency. Experimental validation was conducted using MATLAB/Simulink alongside a real-time Hardware-In-the-Loop (HIL) platform based on NI PXIe-1071, under a range of uniform and non-uniform irradiance conditions. Results demonstrate that the proposed algorithm achieves a power conversion efficiency of 99.7 %, a tracking time of 0.004 s, and an energy harvesting value of 10.5 W s, outperforming conventional methods with a 25 % reduction in GMPP search time. Additionally, the algorithm exhibits superior performance in terms of convergence speed and power stability, with minimal oscillations throughout the tracking process. This work contributes a novel, high-efficiency MPPT framework for PV systems operating in dynamic environments, offering promising implications for smart grid integration, renewable energy systems, and future PV-based applications.