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PMUVis:一个在智能电网中协助电力系统运营商的大规模平台。

PMUVis : A Large-Scale Platform to Assist Power System Operators in a Smart Grid.

作者信息

Arunkumar Anjana, Gupta Nitin, Pinceti Andrea, Sankar Lalitha, Bryan Chris

出版信息

IEEE Comput Graph Appl. 2022 Nov-Dec;42(6):84-95. doi: 10.1109/MCG.2022.3171506. Epub 2022 Dec 13.

Abstract

Electric transmission power grids are being revamped with the widespread deployment of GPS-enabled phasor measurement units (PMUs) for real-time wide-area monitoring and control via precise, time-synchronized measurements of voltage and current. Large, concurrently produced volumes of noisy data hinder PMU usability, particularly for the analysis of power oscillation and load fluctuation events in the grid. We examine visualization challenges for events in the electric power grid and develop PMUVis, a visualization platform that supports scalable analysis of grid network topology and anomalous events in near time. PMUVis incorporates a novel FFT-based approach over raw and temporally aggregated data to examine oscillation event propagation through the grid network. We validate PMUVis with expert reviews and a case study and discuss how visualization can be leveraged to enhance real-time spatiotemporal grid analysis by advancing operator capabilities.

摘要

随着全球定位系统(GPS)支持的相量测量单元(PMU)广泛部署,用于通过对电压和电流进行精确的、时间同步的测量来实现实时广域监测和控制,输电电网正在进行改造。大量同时产生的噪声数据阻碍了PMU的可用性,特别是在分析电网中的功率振荡和负载波动事件时。我们研究了电网事件的可视化挑战,并开发了PMUVis,这是一个可视化平台,支持对电网网络拓扑和异常事件进行近实时的可扩展分析。PMUVis在原始数据和时间聚合数据上采用了一种新颖的基于快速傅里叶变换(FFT)的方法,以检查振荡事件在电网网络中的传播。我们通过专家评审和案例研究对PMUVis进行了验证,并讨论了如何通过提高操作员能力来利用可视化增强实时时空电网分析。

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