Power factor correction in SMPS with optimized converter: a hybrid optimization approach

Abstract

In this research work, a novel hybrid optimization model based on an optimized Mahafzah controller is introduced for power factor correction (PFC). The precision, speed, and stability are improved by the overlapping dc–dc SEPIC converter. Additionally, the control settings of the Mahafzah controller will be adjusted using the new hybrid optimization model to improve the system's response time. Additionally, the control parameters of the Mahafzah controller are adjusted using the new hybrid optimization model to improve the system's response time. The proposed hybrid technique is the hybrid methodology of Artificial Gorilla Troops Optimizer (GTO) and Tree Seed Algorithm (TSA) and hence it is named as GTO–TSA technique. Finally, the proposed system's performance characteristics are examined and contrasted with those of traditional optimization algorithms. At that point, the performance of the suggested technique has been tested in the MATLAB program and is in contrast with that of other methods already in use. The proposed method outperforms existing algorithms across a wide range of input voltages, with a power factor ranging from 0.98 to 0.995 and %THD (Total harmonic distortion) with lower values ranging from 1.6 to 1.15. Similarly, when the load resistance is varied, the proposed method has the highest power factor of 0.981–0.999 and the lowest %THD of 18.0 to 1.2 compared to other algorithms.