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首页> 外文期刊>Latin America Transactions, IEEE (Revista IEEE America Latina) >Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System
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Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System

机译:基于神经网络的单相非线性负载谐波含量识别方法

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In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.
机译:本文提出了一种基于人工神经网络的替代方法来确定具有非线性负载的单相电力系统负载电流中的谐波分量,其参数由于负载的特性行为而变化很大,这是由于人为干预。使用时变波形中包含的信息确定负载电流中的前六个分量。通过在单相有功功率滤波器中使用该方法并通过对交流控制器消耗的电流进行选择性补偿,可以验证该方法的有效性。将该方法与快速傅里叶变换进行了比较。

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