Advanced Harmonic Mitigation in Photovoltaic Grid-Connected Systems: Jellyfish Search Optimization Approach

Abstract

Increasing prevalence of nonlinear loads (NLL) in modern power systems poses significant challenges, particularly in terms of harmonic distortion. This distortion degrades the performance and efficiency of photovoltaic (PV) grid-connected systems (PV-GCS), demanding advanced control strategies. This study presents a unique optimization-based method that employs the Jellyfish Search Optimization (JSO) algorithm to enhance the Shunt Active Power Filter (SAPF) for effective harmonic reduction in PV-GCS with a high penetration of NLL in the distribution network. The study aims to reduce total harmonic distortion (THD) and regulate the DC-bus voltage (Vdc) in SAPF. A comprehensive comparison examination is performed between JSO and three frequently utilized optimization algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and golden eagle algorithm (GE), to investigate the efficiency of JSO algorithm. The reduced THD by the JSO is only 1.32 percent, smoothly regulated the Vdc with a short settling time, without overshooting. These findings indicate that JSO outperforms others, emphasizing that it has the potential to improve power quality (PQ) in PV-GCS with NLL. This study presents a strong foundation for minimizing harmonics in PV integrating to the grids, which contributes to improved system reliability and efficiency.