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Two-Level Ambient Oscillation Modal Estimation From Synchrophasor Measurements

机译:同步相量测量的两级环境振荡模态估计

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摘要

This paper proposes a decentralized two-level structure for real-time modal estimation of large power systems using ambient synchrophasor data. It introduces two distributed algorithms that fit the structure well, namely, 1) decentralized frequency domain decomposition and 2) decentralized recursive stochastic subspace identification. As opposed to present-day oscillation monitoring methodologies, the bulk of the algorithmic computations is done locally at the substation level in the two-level framework. Substation modal estimates are sent to the control center where they are grouped, analyzed, and combined to extract system modal properties of local and inter-area modes. The framework and the proposed algorithms provide a scalable methodology for handling oscillation monitoring from a large number of substations efficiently. The two-level structure and the two decentralized algorithms are tested using simulated data from standard test systems and from archived real power system synchrophasor data.
机译:本文提出了一种分散的两级结构,用于使用环境同步相量数据对大型电力系统进行实时模态估计。它介绍了两种非常适合该结构的分布式算法,即1)分散的频域分解和2)分散的递归随机子空间识别。与当今的振动监测方法相反,大部分算法计算是在两级框架中的变电站一级本地完成的。变电站模态估计值将发送到控制中心,在此对其进行分组,分析和组合,以提取局部和区域间模式的系统模态属性。该框架和提出的算法提供了一种可扩展的方法,可以有效地处理来自大量变电站的振荡监视。使用来自标准测试系统的模拟数据和已归档的有功电力系统同步相量数据对两级结构和两种分散算法进行了测试。

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