Optimization of Multilevel Inverters Using Novelty-driven Multi-verse Optimization Algorithm

Abstract

All over the world, renewable energy technologies which need power electronics based inverters in their designs are becoming more and more popular, thus detailed analysis to test the operational efficiency is required. This paper utilizes a new adaptive Multi-verse Optimization (MVO) Algorithm combined with novelty search method to solve harmonic elimination problem in multilevel inverters. We compare the obtained numerical simulations to those obtained by using the grey wolf optimization and standard MVO algorithm. The numerical simulations are performed on 7, 11, and 15 level inverters with different modulation indexes. From the simulation results, we observe that adaptive novelty search Multi-verse Optimization (MVO) based approach was able to obtain less total harmonic distortion for different modulation indexes.