Abstract

ABSTRACT This manuscript proposes a novel hybrid method based on a single-stage three-phase bridgeless alternating current (AC) to direct current (DC) Cuk converter for wind energy conversion systems (WECS). The proposed hybrid method is the combination of Mexican Axolotl Optimization (MAO) and Fuzzy Wavelet Neural Network (FWNN), hence it is named as MAO-FWNN method. Moreover, the proposed method enhanced the system performance by distributing the defined reactive-power to harmonic reduction and doubly fed induction generator (DFIG). The proposed converter is modelled under a discontinuous mode of the inductor current. The converter’s output inductor is modelled as a continuous inductor current mode, and it functions to provide enhanced power quality (PQ) and low DC (Direct Current) voltage ripple. At that point, the MATLAB platform is used to execute the performance of the proposed method, and it is compared with existing methods. The performance of the proposed method provides the 0.095 to 0.096 times/sec, which is higher than the existing methods. As a result, the proposed technique is well established compared to the existing techniques.

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