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An Investigation of Different PMU phasor estimation techniques Based on DFT Using MATLAB

机译:基于MATLAB的DFT的不同PMU相量估计技术的研究。

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Phasor Measurement Unit (PMU) is the essential component in the modern power grid which plays a significant role in monitoring, control and protection of the power system networks in real time. PMUs are able to provide time stamped synchronized measurements of voltage and current phasors using Global Positioning System (GPS) satellites, in microseconds, to maintain the power system network free of faults and hence healthy. Different phasor estimation techniques such as Kalman filter and Discrete Fourier transform (DFT) may be used by PMUs to estimate phasors. In this research work, the implementation of non-recursive, recursive and smart DFT techniques have been investigated for modeling the PMU using MATLAB. Then, mathematical differences among these algorithms are briefly highlighted as well as advantages and drawbacks of each.
机译:相量测量单元(PMU)是现代电网中的重要组成部分,在实时监视,控制和保护电力系统网络中发挥着重要作用。 PMU可以使用全球定位系统(GPS)卫星在几毫秒内提供带时间戳的电压和电流相量同步测量,以保持电力系统网络无故障,从而保持健康。 PMU可以使用不同的相量估计技术(例如卡尔曼滤波器和离散傅立叶变换(DFT))来估计相量。在这项研究工作中,已经研究了非递归,递归和智能DFT技术的实现,以使用MATLAB对PMU进行建模。然后,简要介绍了这些算法之间的数学差异以及每种算法的优缺点。

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