Assessment of hybrid MPPT for SPV based high gain cubic boost converter interfaced with reduced switch multilevel inverter for power quality enhancement

Abstract

A high-gain cubic boost converter (HG-CBC) with hybrid-based maximum power point tracking (MPPT) through a neural network (NN) aided by the P&O technique (HNN-PO MPPT) has been suggested to acquire optimum power from a solar photovoltaic (SPV) model under varying climatic conditions. The SPV’s output is enhanced using the suggested HG-CBC as per the requirement. A detailed comparison of different conventional boost converters (BC) with the suggested HG-CBC is presented, mainly highlighting part count and boost factor (B). Using the MATLAB tool, the functionality of the developed HNN-PO MPPT technique has been examined for constant and different irradiation (G) levels. The hybrid-based MPPT helps quickly attain maximum power point (MPP) with minimum oscillations at the output. The convergence period is very short with high precision in comparison with P&O and NN MPPT. The results are examined between the suggested and traditional MPPT methods in relation to the percentage of oscillations and rise time. The Reduced Switch Multilevel Inverter (RSMLI) is proposed to integrate the SPV with the RL load. The RSMLI is compared with the conventional standard five-level MLI in relation to the quantity of DC sources, diodes, switches, capacitors, and other parts utilized. The suggested MLI involves a reduced switch count, which mitigates the overall losses during switching and hence improves the efficiency of an inverter. MLI switches are controlled using a sine Pulse Width Modulation (PWM) technique. The THD of the output current of a five-level RSMLI is 4.47%, and it falls within the IEEE 519 norm. Hence, output power quality is enhanced.