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arXiv 1809.08192eess.SYcs.SY
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从网络测量中估计频率耦合矩阵

Estimating the Frequency Coupling Matrix from Network Measurements

The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto(多伦多大学电气工程与计算机工程系)

Antoine Lesage-Landry, Siyu Chen, Joshua A. Taylor

AI总结:

本文提出了一种从网络测量中估计频率耦合矩阵的方法,通过谐波减少定理计算等效虚拟频率耦合矩阵,并给出了高效的在线算法来估计频率耦合矩阵和谐波线路电导。

摘要:

电力系统中功率转换器的数量正在不断增加。它们是谐波电流和电压的主要来源,这会降低电力质量并触发保护装置。频率耦合矩阵(FCM)是一种通用技术,用于建模转换器谐波。它可以通过实验表征或给定转换器的内部参数直接计算获得。本文中,我们从网络测量中估计FCM。我们为网络不可观测部分给出了一个新的谐波减少定理,用于计算等效、虚拟的FCM。我们从PMU测量中估计FCM和谐波线路电导,并给出了FCM问题的高效在线版本。我们在数值示例中测试了我们的方法,并显示在有噪声观测下估计误差较低。

英文摘要:

Power converters are present in increasing numbers in the electric power grid. They are a major source of harmonic currents and voltages, which can reduce power quality and trip protection devices. The frequency coupling matrix (FCM) is a general technique for modeling converter harmonics. It can be obtained through experimental characterization or, given a converter's internal parameters, direct calculation. In this paper, we estimate FCMs from network measurements. We give a novel harmonic reduction theorem for computing equivalent, virtual FCMs for unobservable portions of a network. We estimate FCMs and harmonic line admittances from PMU measurements, and give an efficient online version for the FCM problem. We test our approaches on a numerical example, and show that the estimation error is low under noisy observations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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