Selective Harmonic Elimination in Multilevel Inverters Using Metaheuristic Optimization Algorithms: A MATLAB-Based Simulation Study

Selective Harmonic Elimination in Multilevel Inverters Using Metaheuristic Optimization Algorithms: A MATLAB-Based Simulation Study

Taha Ahmad HUSSEIN, Dahaman ISHAK, Muhammad Najwan HAMIDI, Jawad Hasan Alkhateeb

Abstract. Optimizing switching angles in multilevel inverters is explored in this study based on MATLAB simulation. The objective is to achieve selective harmonic elimination (SHE) to eliminate specific low order harmonics while having the fundamental output voltage. The work emphases solution of transcendental equations in SHE for a range of modulation indices from 0 to 1 by employing a group of metaheuristic algorithms including genetic algorithm (GA), gray wolf optimization (GWO), particle swarm optimization (PSO), slim Mould algorithm (SMA), and whale optimization algorithm (WOA). The algorithm performance in terms of the total harmonic distortion (THD) governs the selection of the optimal switching angles for a specific value of the modulation index. The analysis and visualization of algorithm performance are tested within MATLAB environment which offers insights into the effectiveness of biologically inspired optimization techniques for power quality enhancement in multilevel inverter systems.

Keywords
SHE, MLI, Metaheuristic Optimization Algorithms, THD

Published online 4/25/2026, 8 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Taha Ahmad HUSSEIN, Dahaman ISHAK, Muhammad Najwan HAMIDI, Jawad Hasan Alkhateeb, Selective Harmonic Elimination in Multilevel Inverters Using Metaheuristic Optimization Algorithms: A MATLAB-Based Simulation Study, Materials Research Proceedings, Vol. 64, pp 872-879, 2026

DOI: https://doi.org/10.21741/9781644904091-108

The article was published as article 108 of the book Energy Futures

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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