Publication Type : Journal Article
Source : Asian Journal of Information Technology, Vol.13(10), pp.627-632, 2014
Url : https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9433502
Campus : Coimbatore
School : School of Engineering
Verified : No
Year : 2014
Abstract : In this article, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced
to mitigate the undesired lower-order harmonic content in the cascaded H-Bridge multilevel inverter for
solar photovoltaic (PV). Harmonics are extracted by the excellent choice of opting switching angles by
exploiting the Selective Harmonic Elimination (SHE) PWM technique accompanying a unified algorithm in
order to optimize and reduce the Total Harmonic Distortion (THD). ANN is trained with optimum switching
angles, and the estimates generated by the ANN are the initial guess for NR. In this study, the CHB-MLI is
combined with a traditional boost converter, it boosts the PV voltage to a superior dc-link voltage Perturb
and Observe (P&O) based Maximum Power Point Tracking (MPPT) algorithm is used for getting a stable
output and efficient operation of solar PV. The proposed system is proved over an eleven-level H-bridge
inverter, the work is carried out in MATLAB/Simulink environment, and the respective results are confirmed
that the proposed technique is efficient, and offers an actual firing angles with a few iterations results in a
better capability of confronting local optima values. The suggested algorithm is justified by the experimental
development of eleven-level cascaded H-bridge inverter.
Cite this Research Publication : M.S.Sivagama Sundari & P.Melba Mary, “Artificial Neural Network based Optimized Harmonic Stepped Waveform Technique for Cascaded H-Bridge Eleven Level Inverter” Asian Journal of Information Technology, Vol.13(10), pp.627-632, 2014.