Open Access

ARTICLE

A Grey Wolf Optimized 15-Level Inverter Design with Confined Switching Components

S. Caroline^1,*, M. Marsaline Beno²

1 Department of ECE, St. Xavier’s Catholic College of Engineering, Nagercoil, Tamilnadu, India
2 Department of EEE, St. Xavier’s Catholic College of Engineering, Nagercoil, Tamilnadu, India

* Corresponding Author: S. Caroline. Email:

Intelligent Automation & Soft Computing 2022, 31(3), 1753-1769. https://doi.org/10.32604/iasc.2022.020440

Received 24 May 2021; Accepted 27 June 2021; Issue published 09 October 2021

Abstract

Multilevel inverters are a new class of dc-ac converters designed for high-power medium voltage and power applications as they work at high switching frequencies and in renewable applications by avoiding stresses like dv/dt and has low harmonic distortion in their output voltage. In variable speed drives and power generation systems, the use of multilevel inverters is obligatory. To estimate the switching positions in inverter configuration with low harmonic distortion value, a fast sequential optimization algorithm has been established. For harmonic reduction in multilevel inverter design, a hybrid optimization technique combining Firefly and the Genetic algorithm was used. In several real-time systems and for solving complex engineering problems, optimization approaches are gaining popularity. Based on Grey Wolf Optimization (GWO), this research paper proposes a novel multilevel inverter architecture. The GWO algorithm is based on the natural leadership hierarchy and hunting mechanism of grey wolves (Canis lupus). The Grey Wolf Optimizer (GWO) algorithm is used to find the best switching angles for a cascaded multilevel inverter in order to eliminate some high order harmonics while sustaining the desired fundamental voltage. The proposed inverter has 15 stages, and the circuit’s unique feature includes a limited switching device. This proposed method comprises, MOSFET-based switches well as three DC sources in the main circuit. The switching parameters of the inverter topology are tuned using GWO in this methodology. The THD value of the proposed system is reduced to 6.629% compared to that of Multilevel Inverter using Genetic Algorithm, standalone power supply, Firefly assisted Genetic Algorithm, hybrid APSO algorithm, DC voltage regulation and FPGA. A few simulation studies have been included in this paper to affirm the capability of the hybrid topologies with various condition parameters, dynamic changes, and modulation indexes.

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