Experimental investigation and comparative harmonic optimization of AMLI incorporate modified genetic algorithm using for power quality improvement

Rajarathinam Palanisamy, Vijayakumar Govindaraj, Saravanan Siddhan, Johny Renoald Albert

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)

Abstract

A super-lift mechanism has made tremendous progress in DC/DC conversion technology. In comparison to the asymmetrical form of MLI, the novel Asymmetric Multilevel Inverter (AMLI) technology proposes a minimized number of components. The Fuzzy-PI (Proportional integral) and Modified Genetic Algorithm (MGA) utilizes to minimize the harmonic content considerably using a variety of modulation index and firing angle values in open-loop and closed-loop control. This architecture for designing single-phase 7-level AMLI with an intelligent algorithm proposed for Renewable Energy (RE) applications. This circuit uses a single MOSFET switch with less switching stress and a single DC source. The effectiveness of the proposed MGA optimization eliminates the lower-order harmonics. MGA and Fuzzy-PI based Distributed Power Flow Intelligent Control (DPFIC) algorithms are applied with multilevel structures while maintaining the fundamental frequency for both MATLAB platform and hardware implementation. During this analysis, the losses is also find to investigate the influence of modulation index and output power factor on inverter efficiency. Simulations and experimental findings confirm the proposed inverter capacity to create high-quality multilayer output voltage. However, the proposed closed loop simulation circuit gives 0.47% minimum THD level, and 10.4% in experimental results.

Original languageEnglish
Pages (from-to)1163-1176
Number of pages14
JournalJournal of Intelligent and Fuzzy Systems
Volume43
Issue number1
DOIs
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • Asymmetric multilevel inverter
  • distributed power flow intelligent control
  • fuzzy logical control
  • modified genetic algorithm
  • proportional integral

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