Controller design of DFIG-based WT by using DE-optimization techniques

This manuscript depicts the controller design for doubly fed induction generator-based variable speed wind turbine by using evolutionary techniques. That is based on exploiting the two efficient swarm intelligence based evolutionary soft computational method, i.e., Differential Evolution Optimization (DEO) and Genetic Algorithm Optimization (GAO) to design the controller for low damping plant of the DFIG. Wind energy overview and DFIG based WT component with operating principle have been discussed appropriately in this paper. The controller design for DFIG based WT using DEO and GAO techniques along with its fitness functions are depicted. The responses of the DFIG system concerning terminal voltage, active-reactive power, and DC-Link voltage have slightly improved with DEO based controller in comparison with GAO based controller. Lastly, the obtained output is equated with a standard technique for performance enhancement of the DFIG based wind energy conversion system.