Power Control of DFIG based WECS using SOSMC and PSO algorithm

In recent years many researches went on to explore the deep and powerful impact of evolutionary algorithms on tuning the control parameters of the Doubly Fed Induction Generator (DFIG). The final purpose for that is to optimize controllers' gain and thus improve the systems' robustness and stability. In this article, we focus on Particle Swarm Optimization (PSO) algorithm in order to tune DFIG's parameters; Firstly, a state of art is addressed for articles that have dealt with both PSO and Super-Twisting (ST) algorithms applied on the DFIG based Wind Energy Conversion Systems (WECS). Secondly, a study is conducted on modeling, simulation and control of the DFIG based WECS using ST and PSO algorithms in order to control active and reactive powers. Finally, a comparative study is conducted for different control scenarios under normal and abnormal conditions in order to demonstrate and highlight the impact of each combination on the performances of a grid connected wind turbine generator.