Bektaş, Yasin2024-07-032024-07-0320242090-4479https:/dx.doi.org/10.1016/j.asej.2024.102719https://hdl.handle.net/20.500.12451/12023This 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.eninfo:eu-repo/semantics/openAccessArtificial Ecosystem-based OptimizatioArtificial Neural NetworkMulti-Level InverterPower QualityPulse Width Modulation;Selective Harmonic EliArticle15610.1016/j.asej.2024.102719Q1N/A