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基于相量测量单元(PMU)测量的电力系统模型在智能电网中识别与抑制低频振荡

Identification and suppression of low-frequency oscillations using PMU measurements based power system model in smart grid.

作者信息

Zuhaib Mohd, Rihan Mohd, Gupta Saket, Sufyan Marwan Ahmad Abdullah

机构信息

Department of Electrical Engineering, GLA University, Mathura, Uttar Pradesh, India.

Department of Electrical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India.

出版信息

Sci Rep. 2025 Jan 30;15(1):3822. doi: 10.1038/s41598-025-88389-3.

DOI:10.1038/s41598-025-88389-3
PMID:39885334
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11782510/
Abstract

Low-frequency oscillations (LFO) are inherent to large interconnected power systems. Timely detection and mitigation of these oscillations is essential to maintain reliable power system operation. This paper presents a methodology to identify and mitigate low-frequency oscillations ( forced and inter-area) using a wide area monitoring system (WAMS) based power system model utilizing phasor measurement units (PMUs). These models accurately identify the behavior and location of generators contributing to low-frequency oscillations in real-time and hence can efficiently improve the performance of WADC to mitigate them. The proportional resonant power system stabilizer (PR-PSS) is utilized to suppress these LFOs, as determined from the Wide Area Power System Model. The damping structure based on PR-PSS with measurements from WAMS effectively suppresses both forced and inter-area oscillation modes.

摘要

低频振荡(LFO)是大型互联电力系统所固有的。及时检测和缓解这些振荡对于维持电力系统的可靠运行至关重要。本文提出了一种利用基于广域监测系统(WAMS)的电力系统模型和相量测量单元(PMU)来识别和缓解低频振荡(强迫振荡和区域间振荡)的方法。这些模型能够实时准确地识别导致低频振荡的发电机的行为和位置,从而可以有效地提高广域阻尼控制器(WADC)缓解振荡的性能。根据广域电力系统模型的结果,采用比例谐振电力系统稳定器(PR-PSS)来抑制这些低频振荡。基于PR-PSS并结合来自WAMS测量值的阻尼结构能够有效地抑制强迫振荡和区域间振荡模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/8f900346f8b6/41598_2025_88389_Fig13_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/8f900346f8b6/41598_2025_88389_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/7041e5484791/41598_2025_88389_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/8ddd7fdc53d3/41598_2025_88389_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/47721f529e08/41598_2025_88389_Fig4_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/60be8e700541/41598_2025_88389_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/cfc75cb41854/41598_2025_88389_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/6b7cdc598c20/41598_2025_88389_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/84eef972a8bf/41598_2025_88389_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/a26d30792280/41598_2025_88389_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/7a246cd2b8b4/41598_2025_88389_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/a0f0a66cdea8/41598_2025_88389_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1b/11782510/8f900346f8b6/41598_2025_88389_Fig13_HTML.jpg

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