Novel Neural Control of Single-Phase Grid-Tied Multilevel Inverters for Better Harmonics Reduction

Abstract

A single-phase Cascaded H-Bridge (CHB) grid-tied multilevel inverter is introduced with a detailed discussion of the proposed novel neural controller for better efficiency and power quality in the integration of renewable sources. An LCL (inductor-capacitor-inductor) filter is used in the multilevel inverter system to achieve better harmonic attenuation. The proposed Neural Network (NN) controller performs the inner current control and tracks the references generated from the outer loop to satisfy the requirements of voltage or power control. Two multicarrier-based Pulse Width Modulation (PWM) techniques (phase-shifted modulation and level-shifted modulation) are adopted in the development of the simulation model to drive the multilevel inverter system for the evaluation of the neural control technique. Simulations are carried out to demonstrate the effectiveness and efficient outcomes of the proposed neural network controller for grid-tied multilevel inverters. The advantages of the proposed neural control include a faster response speed and fewer oscillations compared with the conventional Proportional Integral (PI) controller based vector control strategy. In particular, the neural network control technique provides better harmonics reduction ability.