Design and implementation of optimal controller for DFIG-WT using autonomous groups particle swarm optimization

Abstract

There are many types of generators used within wind energy such as doubly fed induction generator (DFIG). Particle swarm optimization (PSO) algorithm is simple, robust and easy to implement. In addition to the privilege of PSO, autonomous groups particle swarm optimization (AGPSO) has the advantages of using diverse autonomous groups which result in more randomized and directed search. Applying AGPSO to tune PI controller to control DFIG is proposed in this paper. An implemented laboratory prototype consists of brushless DC motor (BLDC) for simulating the various wind speeds. Wound rotor induction machine, working as DFIG. This system is a stand-alone system. System identification strategy was introduced in this work. In this study, AGPSO is suggested for tuning the PI controller. Different case studies are performed, such as step changes in both speed and electrical load for showing the effectiveness of the proposed algorithm. For comparison PSO is used to tune the PI controller. Results from experiments clarify the feasibility of the proposed methodology. It is approved that AGPSO achieves the prevalent control execution (quicker transient response and more modest steady state error (ess)) contrasted with the PSO in tuning PI controller when applied to be used with off-grid systems.