Controller Design of DFIG Based Wind Turbine by Using Evolutionary Soft Computational Techniques

This manuscript illustrates the controller design for a doubly fed induction generator based variable speed wind turbine by using a bioinspired scheme. This methodology is based on exploiting two proficient swarm intelligence based evolutionary soft computational procedures. The particle swarm optimization (PSO) and bacterial foraging optimization (BFO) techniques are employed to design the controller intended for small damping plant of the DFIG. Wind energy overview and DFIG operating principle along with the equivalent circuit model is adequately discussed in this paper. The controller design for DFIG based WECS using PSO and BFO are described comparatively in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power, and DC-Link voltage have slightly improved with the evolutionary soft computational procedure. Lastly, the obtained output is equated with a standard technique for performance improvement of DFIG based wind energy conversion system.