基于密度的智能电网态势感知聚类方案

Ranganath Vallakati, Anupam Mukherjee, P. Ranganathan
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引用次数: 7

摘要

同步相量是最先进的测量传感器,以高数据速率检测电压,电流或频率。本文提出了一种分析同步相量产生的智能电网流数据的方法。采用了一种新颖的单位圆表示来实现实时相量数据的可视化。提出了一种基于密度的聚类(DBSCAN)方法,对相量数据进行聚类,检测出不良数据进行分类,从而识别出各种故障异常。本文使用来自IEEE 14总线系统试验台的数据集来帮助系统操作员进行各种预测分析和决策。
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A density based clustering scheme for situational awareness in a smart-grid
Synchrophasors are the state-of-the-art measuring sensors that sense voltage, current, or frequency with high data rate. This paper presents an approach to analyze the streaming smart-grid data generated by synchrophasors. A novel unit-circle representation is used to visualize the real-time phasor data. A Density based clustering (DBSCAN) method is proposed to cluster the phasor data to detect bad-data for classification, and identifying various fault anomalies. The paper uses datasets from an IEEE 14 bus system test-bed to aid system operators in carrying various predictive analytics and decisions.
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