Software-in-the-Loop Validation of an Adaptive Particle Swarm Optimization-Based MPPT Controller for Real-Time Photovoltaic System - ODEYEMI, Emmanuel T.; HARUNA, Ya’u S.; BAKARE, Ganiyu A.; MAMMAN, Hassan B.; HASSAN, Sabo M. (FUDMA Journal of Engineering and Technology, 2026)
Maximum Power Point Tracking (MPPT) is essential for maximizing energy yield in photovoltaic (PV) systems under dynamic environmental conditions. This study presents a comparative evaluation and real-time Software-in-the-Loop (SIL) validation of conventional and intelligent MPPT algorithms for a 1.5 MW standalone PV system, representing a utility-scale installation with high current and dynamic complexity. The Adaptive Particle Swarm Optimization (APSO) algorithm is characterized by dynamic adjustments of inertia weight and acceleration coefficients, enhancing convergence speed and tracking accuracy. A high-fidelity MATLAB/Simulink model, integrating a DC–DC boost converter and dynamic irradiance profiles, was developed. P&O, INC, GA, and APSO were evaluated based on tracking efficiency, convergence speed, and steady-state ripple. The results show that APSO achieved the highest tracking efficiency (99.3%), the fastest convergence (0.8 s), and the lowest ripple (1.8%), outperforming GA, P&O, and INC. SIL validation further confirmed the feasibility and robustness of APSO, maintaining 99.0% efficiency and 1.6% ripple under real-time constraints. These findings establish APSO as a reliable, implementation-ready MPPT solution for large-scale PV systems.
Keywords: Adaptive Particle Swarm Optimization, Maximum Power Point Tracking, Software-in-the-Loop, Solar Photovoltaic Systems, and Dynamic Irradiance.