Abstract

This study explores the application of a passivity-based control technique (PBC) with an artificial neuro-fuzzy inference system (ANFIS) in a grid-connected Solar Photovoltaic (SPV) generating system for estimating reference grid currents. To optimise the tracking of the maximum power point (MPPT) between the solar photovoltaic (SPV) system and the DC bus, a DC – DC boost converter (BC) is utilised. This converter is connected to a four-leg, three-level neutral-point-clamped converter (4-leg 3L-NPC), interfaced with a three-phase, four-wire distribution system. The four-leg 4-leg 3L-NPC of the SPV generating system with Space vector pulse width modulation technique (SVPWM) is utilised for reducing common-mode voltage (CMV), leakage current (LC), reactive power for zero voltage regulation, power factor correction, load balancing, and the elimination of load harmonic currents in the proposed distribution system.The performance analysis of the proposed system is conducted on the Matlab/Simulink platform. Additionally, a comparative analysis is presented, contrasting the proposed system with a 3-phase 4-leg T-type neutral-point-clamped converter (TNPC) employing the PBC technique followed by ANFIS.

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