Design and Performance Evaluation of Grid-Connected Solar Photovoltaic Systems Using Advanced MPPT Techniques

Abstract

Grid-connected photovoltaic (PV) generation requires an effective maximum power point tracking (MPPT) controller to extract the largest feasible energy from a nonlinear PV array while maintaining a stable DC link and grid-compliant current injection. This methodology paper develops and evaluates a 5 kW two-stage grid-connected PV architecture using a DC-DC boost converter, a three-phase voltage-source inverter, an LCL filter, phase-locked-loop synchronization, and a common grid-current controller. Four MPPT strategies—Perturb and Observe (P&O), Incremental Conductance (INC), fuzzy-logic control (FLC), and accelerated particle swarm optimization (APSO)—are compared under identical irradiance steps, temperature variation, and a partial-shading interval. Performance is assessed using tracking efficiency, settling time, steady-state oscillation, global maximum power point capture under shading, and captured energy. The numerical evaluation shows a clear progression from conventional to advanced techniques: simulated tracking efficiencies are 91.50% for P&O, 94.66% for INC, 96.80% for FLC, and 98.21% for APSO, with APSO also providing the shortest settling time. The proposed framework demonstrates how advanced MPPT can increase PV-side energy extraction without changing the grid-side converter, while highlighting the trade-off between algorithmic complexity and tracking performance. The methodology is designed to be reproducible in MATLAB/Simulink or an equivalent power-electronic simulation environment and can be extended to hardware-in-the-loop validation.