Improvement of LVRT capability of grid‐connected wind‐based microgrid using a hybrid GOA‐PSO‐tuned STATCOM for adherence to grid standards

Abstract

Abstract The increase in wind power‐based microgrids emphasizes the importance of addressing stability challenges during low‐voltage ride‐through (LVRT) events in weak AC grid‐connected doubly fed induction generator systems. Compliance with grid standards, notably LVRT capabilities, is critical as wind power plants integrate increasingly into power systems, raising concerns about generation loss and post‐fault oscillations in microgrids. Previously, researchers have utilized techniques like fuzzy logic, ant colony, and genetic algorithms for static synchronous compensator (STATCOM) tuning to enhance microgrid stability during fault scenarios. This study uses the grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), and a novel hybrid GOA‐PSO. On the main grid, the power system is subject to both symmetrical and asymmetrical faults. The proposed novel technique aims to improve LVRT, minimize generation loss during faults, and reduce after‐fault oscillations by optimizing reactive power flow between the point of common coupling and the microgrid while adhering to the LVRT grid code. MATLAB/Simulink is utilized to evaluate the LVRT performance of a 16 MW DFIG‐based microgrid operating in grid‐connected mode. The performance of the GOA‐PSO‐tuned STATCOM is evaluated by comparing it with conventional, PSO, and GOA‐tuned STATCOM in three fault scenarios. The comparison shows that GOA‐PSO‐tuned STATCOM improves grid stability and reliability.

Keywords

• DFIG
• grasshopper optimization algorithm (GOA)
• LVRT
• microgrid
• particle swarm optimization (PSO)
• STATCOM