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

Abstract

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 and it mainly highlighting on 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 % 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 PWM modulation technique. The THD of output current of five-level RSMLI is 4.47% and it falls within the IEEE 519 norm. Hence, output power quality is enhanced.