标题:Transient stability assessment of power systems based on slow feature analysis
作者:Si, Yabin ;Liu, Daowei ;Yang, Hongying ;Li, Zonghan ;Wang, Youqing
作者机构:[Si, Yabin ;Wang, Youqing ] College of Information Science and Technology, Beijing University of Chemical Technology, Beijing; 100029, China;[Li, Zong 更多
会议名称:38th Chinese Control Conference, CCC 2019
会议日期:27 July 2019 through 30 July 2019
来源:Chinese Control Conference, CCC
出版年:2019
卷:2019-July
页码:7334-7339
DOI:10.23919/ChiCC.2019.8865842
关键词:Data-driven; Power Systems; Slow Feature Analysis (SFA); Transient Stability Assessment (TSA)
摘要:The classify technology to transient stability assessment (TSA) has been studied and applied as an effective method for real-time transient monitoring. However, Large power systems usually have the high dimensionality of variables, which raises the curse of dimensionality and requires an extra dimensionality reduction technique to make the TSA methods appropriate in practice. This paper firstly employs a prevailing data-driven method, slow feature analysis (SFA), to assess transient stability, and shows its suitability for TSA. SFA-based TSA can be a classifier also an online monitoring tool, which simultaneously keeps high performance in handling the curse of dimensionality and outperforms in computational complexity. The algorithm of SFA is conceptually explained, and the IEEE 10-machine, 39-bus New England case is utilized to verify the validity and effectiveness of SFA-based TAS. © 2019 Technical Committee on Control Theory, Chinese Association of Automation.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074402106&doi=10.23919%2fChiCC.2019.8865842&partnerID=40&md5=632240615876dc3353e3184b42bcaa15
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