Circuits and Systems

Volume 7, Issue 9 (July 2016)

ISSN Print: 2153-1285   ISSN Online: 2153-1293

Google-based Impact Factor: 0.48  Citations  

Harmonic Minimization in Seven-Level Cascaded Multilevel Inverter Using Evolutionary Algorithm

HTML  XML Download Download as PDF (Size: 2046KB)  PP. 2309-2322  
DOI: 10.4236/cs.2016.79201    2,124 Downloads   3,756 Views  Citations

ABSTRACT

Inverters are power electronic devices that change over DC to sinusoidal AC quantity. Be that as it may, in down to earth, these devices produce non-sinusoidal yield which contains harmonics, so as to blend a close sinusoidal component and to lessen the harmonic distortion multilevel inverters developed. Mathematical methods, which were developed, are derivative based and need initial considerations. To overcome this, evolutionary algorithms, which are derivative free and accurate, were developed for obtaining multi levels of output voltage. The proposed work uses two evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. These algorithms are used to generate the switching angles by satisfying the non linear transcendental equations that govern the low order harmonic components. A seven level cascaded full bridge inverter is designed using MATLAB/Simulink and the results validate the results for switching angles. The Total Harmonic Distortion (THD) value obtained for GA and PSO is 11.81% and 10.84% respectively. The solution obtained from GA algorithm was implemented in hardware using dsPIC controller to validate the simulation results. The THD value obtained for cascaded seven-level multilevel inverter in the hardware prototype is 25.9%.

Share and Cite:

Rajaiah, J. , Ramar, V. and Parasunath, V. (2016) Harmonic Minimization in Seven-Level Cascaded Multilevel Inverter Using Evolutionary Algorithm. Circuits and Systems, 7, 2309-2322. doi: 10.4236/cs.2016.79201.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.