Design of an Optimized Asymmetric Multilevel Inverter with Reduced Components Using Newton-Raphson Method and Particle Swarm Optimization. (11th April 2023)

• Record Type: Journal Article
• Authors: Gireesh Kumar, Devineni; Venkata Sireesha, Nagineni; Ganesh, Aman; Kotb, Hossam; AboRas, Kareem M.; Zeinoddini-Meymand, Hamed; Kamel, Salah
• Other Names: Dhanamjayulu C. Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2023(2023)
• Publication Date: 2023-04-11
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2023/9966708
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Multilevel inverters have great scope in current developments of grid-connected solar PV systems. Two-level inverters are the simplest kind of multilevel inverter available (MLI). As the number of output levels is raised, the total harmonic distortion decreases. In classic MLI topologies, more electronic components are utilized to get higher-level outputs, which raise the cost, complexity, and volume of typical MLI installations. By reducing the design components, the cost of the system will be reduced. Furthermore, the two- and three-level inverters produce constant dv/dt output, which increases the stress on the power switches. This research proposes an asymmetric MLI topology that is suitable for PV applications and utilizes less number of DC sources and switches. The proposed inverter is controlled by selective harmonic elimination-based pulse width modulation (SHEPWM) to eliminate the lower-order dominant harmonics. The nonlinear equations produced by the SHEPWM are solved for the switching angles of the proposed inverter using the Newton-Raphson (NR) method and particle swarm optimization (PSO) method for various modulation indexes. The performance of the proposed inverter is analyzed based on the total harmonic distortion (THD) of the output for different operating levels of the inverter by comparing similar topologies in the literature. The THD obtained by the NR method is 7.3% and by using PSO is 4.23% at 0.9 modulation index.