Application of Five-Level NPC Inverter in DPC-ANN of Doubly Fed Induction Generator for Wind Power Generation Systems

This paper presents the five-level direct power control (DPC) using artificial neural networks (ANNs) controller of a doubly fed induction generator (DFIG) based wind power generation systems (WPGSs). The validity of the proposed strategies is verified by simulation tests of an induction generator. The harmonic distortion of stator current, reactive power, and stator active power are determined and compared to the above strategies. The five-level DPC strategy with ANN controller is shown to be able to minimize the reactive power, harmonic distortion of stator current, and stator active power ripples and to improve performance DPC control scheme.