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New Research on Harmonic Detection Based on Neural Network for Power System

机译:基于神经网络的电力系统谐波检测的新研究

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Analysis and control for power quality by neural network is a new research field in electrical power system. Rapid and reliable extract the harmonic components determine the overall performance of Active Power Filter (APF). This paper presents a new three-layer feedforward neural network based on error back-propagation algorithm that the training sample without time delay, which can detecting harmonics for power system in real-time. With the simulation study using Matlab, the simulation results illustrate that the harmonic detection method based on neural network is feasible, which can quickly detecting the harmonics for non-linear load.
机译:神经网络对电能质量的分析与控制是电力系统研究的一个新领域。快速可靠地提取谐波分量决定了有源功率滤波器(APF)的整体性能。本文提出了一种基于误差反向传播算法的三层前馈神经网络,该网络的训练样本没有时间延迟,可以实时检测电力系统的谐波。通过Matlab的仿真研究,仿真结果表明,基于神经网络的谐波检测方法是可行的,可以快速检测非线性负载的谐波。

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