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

机译:单相并网多电平逆变器的新型神经控制,可更好地降低谐波

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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.
机译:介绍了单相级联H桥(CHB)并网多电平逆变器,并详细讨论了所提出的新型神经控制器,以提高可再生能源的集成效率和电能质量。多电平逆变器系统中使用了LCL(电感-电容-电感)滤波器,以实现更好的谐波衰减。拟议的神经网络(NN)控制器执行内部电流控制并跟踪从外部环路生成的参考,以满足电压或功率控制的要求。在仿真模型的开发中,采用了两种基于多载波的脉宽调制(PWM)技术(相移调制和电平移位调制)来驱动多电平逆变器系统,以评估神经控制技术。进行仿真以证明所提出的用于并网多电平逆变器的神经网络控制器的有效性和有效结果。与传统的基于比例积分(PI)控制器的矢量控制策略相比,所提出的神经控制的优点包括更快的响应速度和更少的振荡。特别地,神经网络控制技术提供了更好的谐波降低能力。

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