Estimation and elimination of harmonics in power system using modified FFT with variable learning of Adaline

Neeraj Sharma, R. Gupta, Dulara Sharma, A. Swarnkar, N. Gupta
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引用次数: 5

Abstract

This paper presents a new technique for harmonic detection, estimation and elimination in power system. The approach expresses the input signal in the form of Fourier Transformation and adjusts the Fourier coefficients using Linear Adaptive Filters (Adaline). Two of the existing approaches using conventional Fast Fourier transformation (FFT) and FFT with modified W-H learning have been discussed with their merits and demerits. A new approach has been proposed using a network comprising three different Adalines and involving variable learning rate. This approach is able to mitigate the shortcomings of the existing techniques and is time efficient as well. The detailed architecture for the proposed approach has been discussed and the algorithm has then been tested on different test signals. The approach has been compared with the existing techniques and it's superiority over these has thus been established.
基于Adaline变量学习的改进FFT估计与消除电力系统谐波
提出了一种新的电力系统谐波检测、估计和消除技术。该方法以傅里叶变换的形式表示输入信号,并使用线性自适应滤波器(Adaline)调整傅里叶系数。讨论了传统快速傅里叶变换(FFT)和改进W-H学习的FFT两种现有方法的优缺点。提出了一种新的方法,使用由三个不同的Adalines组成的网络,并涉及可变学习率。这种方法能够减轻现有技术的缺点,而且时间效率高。讨论了该方法的详细结构,并在不同的测试信号上对该算法进行了测试。通过与现有技术的比较,证明了该方法的优越性。
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