This study proposes a two-step method for generating switching angles in renewable energy systems that use multi-level inverters (MLIs) to reduce low-order harmonics. The Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) technique is used for MLI control, but it can be computationally intensive for real-time applications. To address this challenge, the proposed approach consists of a two-stage process. In the first stage, the SHE equations are solved offline using artificial ecosystem-based optimization (AEO). The obtained switching angles are then used to train an artificial neural network (ANN) prediction model in the second stage. The AEO-ANN-based SHE-PWM technique is applied to a reduced-switching, 3-phase, 7-level MLI. Simulations in MATLAB/SIMULINK show that the proposed method achieves accurate voltage control with less than 0.2% error, even for changing voltages, and reduces selected harmonics to less than 0.05%. The desired output voltage exhibits minimal total harmonic distortion (THD). This method offers a promising way to generate switching angles in renewable energy systems that use MLIs, improving power quality and reducing harmonic distortion.
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Yasin Bektaş (2024) studied this question.
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