Optimal PI controller design for high-efficiency DC–DC boost converters with enhanced perturb-and-observe MPPT in photovoltaic systems

Abstract The maximum power point tracking (MPPT) algorithm and the power converter must be precisely controlled in order to maximize energy extraction from photovoltaic (PV) systems. Four high-power DC–DC boost converters are modeled, designed, and optimized in this work. The system uses a two-stage control architecture where a proportional-integral (PI) controller controls the converter output and an Enhanced Perturb and Observe (EPO) algorithm predicts the maximum power point (MPP) voltage. Accelerated Particle Swarm Optimization (APSO), the Adaptive Spiral Dynamic Algorithm (ASDA), and a hybrid APSO–ASDA approaches were used to adjust the PI gains. The hybrid algorithm delivered the best overall performance, achieving fast rise times (0.3671–0.5691 s), short settling durations (0.5853–0.9267 s), and almost eliminating overshoots. Under typical test conditions, the converters' extraction efficiencies exceeded 98%, and they showed good performance in the face of changes in temperature, irradiance, load disturbances, and PV shades. System-level grid-integration study, including deployment inside an 11 kV multilevel inverter interface, is specified as future work because this work solely concentrates on converter-level performance.