Power system event classification via dimensionality reduction of synchrophasor data
Power system event classification via dimensionality reduction of synchrophasor data
复制标题
通过同步相量数据降维进行电力系统事件分类
DOI：
10.1109/sam.2014.6882337
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
P. Kumar
中科院分区：
文献类型：
--
作者：
Yang Chen;Le Xie;P. Kumar
本文探索了一种利用在线同步相量测量对电力系统事件进行快速分类的潜在方法。该方法基于新兴的环境相量测量单元(PMU)数据的降维。与基于模型的分析相比，该方法不需要系统模型。它将实时PMU数据投影到由事前数据构成的核心子空间上，然后利用核心子空间的散点图对系统事件进行检测和分类。位于核心子空间之外的投影表示事件的发生，这些投影的拓扑形状对事件进行分类。通过使用合成PMU数据的数值算例，验证了该方法的有效性。
This paper explores a potential approach to fast classifying power system events using online synchrophasor measurements. The approach is based on dimensionality reduction of the emerging ambient phasor measurement unit (PMU) data. In contrast with model-based analysis, the proposed approach does not require a system model. It projects real-time PMU data onto the core subspace constructed from pre-event data, and then utilizes their scatter plots to detect and classify the system events. Projections lying outside the core subspace indicate the occurrence of an event, and the topological shapes of these projections classify the events. Numerical examples using synthetic PMU data are conducted to demonstrate the efficacy of the proposed approach.