Comparative analysis of metaheuristic algorithms-based control for enhancing low voltage ride through in grid-connected photovoltaic systems

Abstract

This paper aims to investigate the improvement of the low voltage ride-through (LVRT) in grid-connected photovoltaic (PV) systems by applying the Gold Rush Optimization (GRO) algorithm to design system PI controllers. This paper overviews the significance of LVRT in PV systems, emphasizing its importance for grid stability and regulatory compliance under symmetrical and asymmetrical faults. The results are compared with Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA) based on overshoot, settling time, and steady-state error. In the 3L-G fault, DC-link voltage V dc, GRO outperforms the other algorithms, achieving a reduction of 4.75% in overshoot compared to PSO and a 2.85% improvement over WOA. Additionally, GRO achieves the fastest settling time, a 2.75% reduction compared to PSO and WOA. In terms of accuracy, GRO demonstrates the lowest percentage error. These findings confirm that (GRO) is an effective optimization approach for improving grid stability, reducing power fluctuations, and enhancing low-voltage ride-through capability in PV systems.