Experimental validation of a region-segmented MPPT with disturbance detection and Lyapunov-Based damping for enhanced PV energy extraction

This paper introduces a Region-Segmented Perturb and Observe (RS-P&O) algorithm for Maximum Power Point Tracking (MPPT) in photovoltaic (PV) systems operating under dynamic conditions. The proposed strategy synergistically integrates three main innovations: a region-segmentation scheme that dynamically adjusts the perturbation step-size based on the slope of the P−V curve, ensuring fast convergence and precise tracking; a disturbance detection mechanism rooted in Incremental-Conductance (IncCond) theory, which instantly identifies external perturbations from irradiance or load changes and triggers a corrective recovery mode; and a Lyapunov-inspired damping formulation that enforces monotonic stability, actively suppressing steady-state oscillations around the Maximum Power Point (MPP). A formal stability analysis is provided confirming asymptotic convergence. Comprehensive simulation studies, conducted using step-changes and real-world solar irradiance profiles, demonstrate the algorithm's superior performance over conventional P&O and advanced variants, including Modified P&O and Dual-Tracking methods in terms of tracking speed, accuracy, and robustness. Experimental validation on a Single-Ended Primary-Inductor Converter (SEPIC) converter and real PV system under abrupt load variations verifies these improvements, achieving a tracking accuracy exceeding 99.8 % and a transient recovery time of less than 0.5s. The RS-P&O algorithm thus presents a high-performance, stability-guaranteed MPPT solution well-suited for real-world PV applications characterized by rapid environmental and electrical transients.