Efficient PMSG wind turbine with energy storage system control based shuffled complex evolution optimizer

To well manage the quality of the injected electrical power into the grid from a variable speed wind turbine (VSWT), direct power control (DPC) scheme using second order sliding mode control (SOSMC) based on super-twisting algorithm (STA) approach is proposed. Meanwhile, for reaching the adequate gains of STA, an appropriate optimizer should be implemented. Therefore, shuffled complex evolution (SCE) algorithm-based parameter identification is suggested. To verify the effectiveness of the proposed SCE based controller, several well-known algorithms have been tested under various operating conditions namely: particle swarm optimizer (PSO), artificial bee colony optimizer (ABCO), ant colony optimization (ACO), rooted tree optimizer (RTO) and gray wolf optimizer (GWO). The results confirm the superiority of the proposed SCE algorithm among the competing algorithms and classic SMC regarding the active power steady-state error (0.7233%), undershoot percentage (0.1333%), settling time (0.6810 × 10^-3 s), rise time (1.7515 × 10^-4 s), peak value (7.0521 × 10³ W), overall efficiency (99.2800%), and total harmonic distortion (0.7900%). The proposed SCE based controller allows getting important performances under various operating condition of wind speed and load variations with interesting electrical network stability.