TITLE:
Adaptive Control Strategy for a Triple-Hybrid MPPT System Based on FLC-Supervised P&O and PSO for Residential Solar PV Systems
AUTHORS:
Orebanjo Olusesan, Dedacus N. Ohaegbuchi, Onyegbadue Ikenna Augustine, Izilein Fred Abiebhode
KEYWORDS:
Photovoltaic (PV), Tracking Efficiencies, Maximum Power Point Tracking (MPPT), Perturb and Observe (P&O), Particle Swarm Optimization (PSO), Renewable Energy Sources
JOURNAL NAME:
Energy and Power Engineering,
Vol.17 No.12,
December
25,
2025
ABSTRACT: The increasing energy demand and initiatives to lower carbon emissions have elevated the significance of renewable energy sources. Photovoltaic (PV) systems are pivotal in converting solar energy into electricity and have a significant role in sustainable energy production. Therefore, it is critical to implement maximum power point tracking (MPPT) controllers to optimize the efficiency of PV systems by extracting accessible maximum power. This research work investigates the performance and comparison of various MPPT control algorithms for a standalone PV system. Several cases involving individual MPPT controllers, as well as hybrid combinations using three controllers, have been simulated in MATLAB/SIMULINK. The sensed parameters, i.e., output power, voltage, and current, specify that though individual controllers effectively track the maximum power point, hybrid controllers achieve superior performance by utilizing the combined strengths of each algorithm. The results indicate that individual MPPT controllers, such as perturb and observe (P&O) and particle swarm optimization (PSO), achieved tracking efficiencies of 91.2% and 94.5%, respectively. This research work also proposes a new hybrid triple-MPPT controller combining P&O-PSO-FL, which surpassed both individual controllers, achieving an impressive efficiency of 98.6%. Finally, a comparison of two cases of MPPT control algorithms is presented, highlighting the advantages and disadvantages of individual as well as hybrid approaches.