Dynamic Behavior Analysis for Optimally Tuned On-Grid DFIG Systems

Salah Soued (1) , Haitham Saad Mohamed Ramadan (1) , Mohamed Becherif (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

Metaheuristic Optimization Techniques (MOTs) such as the Artificial Bee Colony (ABC) algorithms and Grey Wolf Optimizer (GWO) can be conveniently used for reaching the Maximum Power Point Tracking (MPPT) of Wind Energy Conversion System (WECS). This paper presents an enhanced control strategy for both Rotor Side Converter (RSC) and Grid Side Converter (GSC) of the Doubly Fed Induction Generator (DFIG)-based WECS using the ABC and the GWO algorithms to ensure the MPPT for the WECS. The control strategy for the RSC and GSC are verified via 9 MW DFIG Wind Turbine (WT) using MATLABTM/Simulink. The dynamic performance improvement of the DFIG depends on the appropriate choice of the optimal PI controllers’ gains. The numerical simulation results show the superiority of the proposed GWO-PI and the ABC-PI optimal controllers over the traditional PI regulators towards enhancing the DFIG system dynamic performance.

Domains: Electric power; Thermics [physics.class-ph]; Automatic; Fluid mechanics [physics.class-ph]

Salah Soued, Haitham Saad Mohamed Ramadan, Mohamed Becherif. Dynamic Behavior Analysis for Optimally Tuned On-Grid DFIG Systems. Energy Procedia, 2019, 162, pp.339 - 348. ⟨hal-02472629⟩