Intelligent Power Harvesting in Grid-tied PV Systems Using Adaptive Grey Wolf Optimization Based MPPT Control Under Partial Shading Conditions

Abstract

In this paper, a Grey Wolf Optimization (GWO)-based Maximum Power Point Tracking (MPPT) controller is proposed for real-time power optimization in a residential on-grid photovoltaic (PV) system. The developed approach addresses the challenges posed by partial shading conditions (PSC), which often lead to multiple local maxima in the power-voltage curve. Unlike traditional MPPT methods, the GWO algorithm demonstrates a highly efficient and adaptive search mechanism that accurately identifies the Global Maximum Power Point (GMPP). The system achieves a peak power output of 395–400 W with a rapid tracking time of ≤0.20 seconds and MPPT efficiency exceeding 97.3%. Voltage stability is maintained within ±1.2%, and the duty cycle converges within a tight range of 0.55–0.62, minimizing switching losses and ensuring consistent performance. This research presents a comprehensive performance evaluation, confirming that the proposed GWO-based MPPT not only enhances energy extraction but also improves overall system responsiveness and reliability under dynamic environmental conditions.