基于开关神经网络的多电平逆变器谐波降频问题研究

F. Bonanno, G. Capizzi, G. L. Sciuto
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引用次数: 1

摘要

多电平逆变器由于其显著的优点和较低的电压输出谐波含量,在集成发电系统(IGSs)中越来越受到重视。本文提出了一种基于切换神经网络(SNN)的切换模式降谐波方法。我们执行这个新范例的实现,以建立一个五电平三相逆变器的开关模式。所提供的结果以及SNN软件和硬件实现的主要指导方针表明了这种方法的重要性。
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Solving harmonics reduction problem in multilevel inverters by switching neural networks-based approach
Multilevel inverters are increasingly considered in integrated generation systems (IGSs) due their significant advantages and low voltage output harmonics content. In this paper a switching neural network (SNN)-based method to provide the switching pattern for harmonics reduction is proposed. We perform the implementation of this new paradigm to establish the switching pattern for a five level three-phase inverter. The provided results as well as the main guidelines for SNN software and hardware implementation show the significance of this approach.
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