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具有惯性的耦合相位振荡器中的低频振荡。

Low-frequency oscillations in coupled phase oscillators with inertia.

作者信息

Song Huihui, Zhang Xuewei, Wu Jinjie, Qu Yanbin

机构信息

School of New energy, Harbin Institute of Technology-Weihai, Weihai, Shandong, 264209, China.

College of Engineering, Texas A&M University-Kingsville, Kingsville, Texas, 78363, USA.

出版信息

Sci Rep. 2019 Nov 22;9(1):17414. doi: 10.1038/s41598-019-53953-1.

DOI:10.1038/s41598-019-53953-1
PMID:31758069
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6874549/
Abstract

This work considers a second-order Kuramoto oscillator network periodically driven at one node to model low-frequency forced oscillations in power grids. The phase fluctuation magnitude at each node and the disturbance propagation in the network are numerically analyzed. The coupling strengths in this work are sufficiently large to ensure the stability of equilibria in the unforced system. It is found that the phase fluctuation is primarily determined by the network structural properties and forcing parameters, not the parameters specific to individual nodes such as power and damping. A new "resonance" phenomenon is observed in which the phase fluctuation magnitudes peak at certain critical coupling strength in the forced system. In the cases of long chain and ring-shaped networks, the Kuramoto model yields an important but somehow counter-intuitive result that the fluctuation magnitude distribution does not necessarily follow a simple attenuating trend along the propagation path and the fluctuation at nodes far from the disturbance source could be stronger than that at the source. These findings are relevant to low-frequency forced oscillations in power grids and will help advance the understanding of their dynamics and mechanisms and improve the detection and mitigation techniques.

摘要

这项工作考虑了一个在单个节点上受到周期性驱动的二阶Kuramoto振子网络,以模拟电网中的低频强迫振荡。对每个节点处的相位波动幅度以及网络中的扰动传播进行了数值分析。这项工作中的耦合强度足够大,以确保无强迫系统中平衡点的稳定性。研究发现,相位波动主要由网络结构特性和强迫参数决定,而非诸如功率和阻尼等单个节点特有的参数。观察到一种新的“共振”现象,即在强迫系统中,相位波动幅度在某些临界耦合强度处达到峰值。在长链和环形网络的情况下,Kuramoto模型得出了一个重要但有点违反直觉的结果,即波动幅度分布不一定沿传播路径遵循简单的衰减趋势,并且远离干扰源的节点处的波动可能比源处的波动更强。这些发现与电网中的低频强迫振荡相关,将有助于推进对其动力学和机制的理解,并改进检测和缓解技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/c8abe94e2e2b/41598_2019_53953_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/57478ede2b5d/41598_2019_53953_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/35acf9548782/41598_2019_53953_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/0934c132e992/41598_2019_53953_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/24d3b055d2df/41598_2019_53953_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/85ad6d18b0eb/41598_2019_53953_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/36e87ff26920/41598_2019_53953_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/39e1b1258f28/41598_2019_53953_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/c8abe94e2e2b/41598_2019_53953_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/57478ede2b5d/41598_2019_53953_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/35acf9548782/41598_2019_53953_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/0934c132e992/41598_2019_53953_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/24d3b055d2df/41598_2019_53953_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/85ad6d18b0eb/41598_2019_53953_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/36e87ff26920/41598_2019_53953_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/39e1b1258f28/41598_2019_53953_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b1c/6874549/c8abe94e2e2b/41598_2019_53953_Fig8_HTML.jpg

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