Data-driven Localization and Estimation of Disturbance in the Interconnected Power System
Data-driven Localization and Estimation of Disturbance in the Interconnected Power System
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DOI：
10.1109/smartgridcomm.2018.8587509
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发表时间：
2018-06
期刊：
影响因子：
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通讯作者：
Hyang-Won Lee;Jianan Zhang;E. Modiano
中科院分区：
文献类型：
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作者：
Hyang-Won Lee;Jianan Zhang;E. Modiano
确定扰动的位置及其大小是电力系统稳定运行的重要组成部分。我们研究了互联电力系统中扰动的定位和估计问题。我们通过使用发电机的频率数据，对该问题采用无模型方法。具体而言，我们开发了一种基于逻辑回归的定位方法和一种基于线性回归的扰动大小估计方法。我们的无模型方法不需要了解诸如惯性常数和拓扑结构等系统参数，并且即使在存在测量噪声和数据缺失的情况下，也能实现高度准确的定位和估计性能。
Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from generators. Specifically, we develop a logistic regression based method for localization and a linear regression based method for estimation of the magnitude of disturbance. Our model-free approach does not require the knowledge of system parameters such as inertia constants and topology, and is shown to achieve highly accurate localization and estimation performance even in the presence of measurement noise and missing data.