With the transformation of transmission and distribution networks into smart grids, where renewable energy sources are becoming more dominant, power electronics-based inverters that improve power quality are becoming increasingly important. To achieve better power quality in the grid to reduce harmonic distortions, it is essential to have efficient inverter operation that directly influences the power efficiency and reliability of the system. In addition, Selective Harmonics Elimination (SHE) technique allows reduced harmonics at the output by eliminating desired-order harmonic components with improved power quality. In this study, the SHE problem in multi-level inverters is addressed using two innovative optimization algorithms: the Mother Optimization Algorithm (MOA) and the Starfish Optimization Algorithm (SFOA). MOA and SFO are applied to the SHE-PWM optimization problem, achieving population diversity and resistance to local optima and speed and efficiency in high-dimensional, complex search spaces, respectively. The performance of the proposed algorithms is validated through comparisons with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Bonobo Optimization Algorithm (BOA). During the simulations, the optimization model was solved by varying modulation indices for 7-level and 11-level output waveforms. The analysis revealed that the SFOA and MOA algorithms provided lower total harmonic distortion (THD) values for different modulation indices.
Taha et al. (Sat,) studied this question.