Affiliations: [a] Department of Electrical Engineering, Adhiyamaan Polytechnic College, Hosur, Tamilnadu, India
| [b] Department of Electrical Engineering, Muthayammal Engineering College, Rasipuram, Tamilnadu, India
| [c] Department of Electrical Engineering, Erode Sengunthar Engineering College (Autonomous), Erode, Tamilnadu, India
Correspondence:
[*]
Corresponding author. Rajarathinam Palanisamy, Research Scholar, Department of Electrical Engineering, Adhiyamaan Polytechnic College, Hosur, Tamilnadu, India. E-mail: [email protected].
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.
Keywords: Asymmetric multilevel inverter, modified genetic algorithm, proportional integral, fuzzy logical control, distributed power flow intelligent control
