two-level dpc strategy based on fnn algorithm of dfig-drwt systems using two-level hysteresis controllers for reactive and active powers

In this paper, a novel switching table (st) of the twelve sectors direct power command (dpc) strategy of doubly-fed induction generator (dfig)-based dual rotor wind power (drwp) is proposed using two-level hysteresis controllers for the reactive and active power and feedforward neural networks (fnns) algorithms. this intelligent technique is used to replace the conventional st in order to reduce the rotor flux ripple, active power ripple, total harmonic distortion (thd) of stator voltage, torque, and reactive power undulations. the simulation and modeling of the proposed strategy are carried out in the matlab software. dfig is tested in association with the drwp system. the simulation results obtained show that dpc with fnn controller (dpc-fnn) reduce the thd values of the stator voltage, rotor flux undulation, active/reactive power undulation, and electromagnetic torque ripple compared to the conventional dpc strategy. according to the results obtained, the current waveform becomes purely sinusoidal with a reduction in the thd rate to 0.64%.