Intelligent control of grid connected unified doubly-fed induction generator

A nonlinear adaptive neuro-fuzzy inference system (ANFIS) based controller is proposed for power electronic systems (PES) of grid connected unified doubly-fed induction generators (DFIG). The unified DFIG utilizes an additional series grid-side converter (SGSC) connected in series with the stator winding of the DFIG to inject voltage into the grid for compensation purposes. The SGSC is useful in tolerating voltage disturbances at the point of common coupling, compared to the conventional DFIG. The conventional proportional integrator (PI) controller of the PES of a unified DFIG is replaced with a nonlinear adaptive neuro-fuzzy inference system (ANFIS) based controller applied for adaptive, fast, and efficient control of power electronic systems. The performance of the conventional PI and ANFIS based controllers are compared on a test system. The transient response of ANFIS based controllers is found to be better compared to the conventional PI controllers.

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