电力系统强迫振荡的数据驱动定位

Wenqing Li, Tong Huangz, Nikolaos M. Frerisy, P. R. Kumarz, Le Xiez
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引用次数: 2

摘要

本文提出了一种数据驱动的方法来定位强迫振荡的来源,这是电力系统正常运行的重要实际要求。通过PMU测量结果的因果关系分析,确定了受迫振荡的来源。为了在接近实时的情况下获得用于因果分析的PMU数据部分,利用稀疏主成分分析来确定强迫振荡的起始点。在IEEE 68总线基准系统中对该方法的有效性进行了测试。大量的仿真结果表明,与现有的定位算法相比,该方法在不需要任何系统模型参数的前提下,可以达到更高的定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-driven Localization of Forced Oscillations in Power Systems
This paper proposes a data-driven approach to locating the source of forced oscillations, which constitutes an important practical requirement for the normal operation of power systems. The source of forced oscillations is pinpointed by conducting Causality Analysis based on PMU measurements. In order to obtain the portion of PMU data for Causality Analysis in nearly real-time, Sparse Principal Component Analysis is leveraged to determine the starting point of forced oscillations. The effectiveness of the proposed approach is tested in the IEEE 68-bus benchmark system. Extensive simulation results showcase that the proposed method can achieve higher accuracy in comparison with a recent localization algorithm, without assuming any knowledge of system model parameters.
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