Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications

In this article, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in cascaded H-Bridge multilevel inverter for solar photovoltaic (PV). Harmonics are extracted by excellent choice of opting switching angles exploiting Selective Harmonic Elimination (SHE) PWM technique accompanying unified algorithm order optimize and reduce Total Distortion (THD). ANN trained with optimum angles, estimates generated initial guess NR. study, CHB-MLI combined traditional boost converter, it boosts PV voltage superior dc-link Perturb Observe (P&O) based Maximum Power Point Tracking (MPPT) used getting stable output efficient operation PV. The proposed system proved over an eleven-level H-bridge inverter, work carried out MATLAB/Simulink environment, respective results confirmed that efficient, offers actual firing few iterations better capability confronting local optima values. suggested justified experimental development inverter.