Information processing and visualization of power system wide area time varying data

S. Dutta, T. J. Overbye

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a methodology for analyzing volumes of time varying data from wide area power systems and intelligently extracting information. The contributions are two-fold. Firstly, algorithms have been developed to identify distinct features of the system dynamic response, flagging outliers in the same process. The second contribution is in the use of advanced visualization tools such as 'spark-lines' on geographic overlays to represent this information. The proposed methodology has been applied on 20 sec transient stability data in a system with over 2400 generators. The developed algorithms analyzed generator speeds and identified abnormal response characteristics in 2 generators. These abnormal responses were caused by errors in these generators' exciter models that were previously undetected and were subsequently corrected. This provides evidence of the capability and effectiveness of the proposed methodology as an operational tool.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 IEEE Computational Intelligence Applications in Smart Grid, CIASG 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Pages6-12
Number of pages7
DOIs
StatePublished - Dec 16 2013
Event2013 IEEE Computational Intelligence Applications in Smart Grid, CIASG 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 - Singapore, Singapore
Duration: Apr 16 2013Apr 19 2013

Publication series

NameIEEE Symposium on Computational Intelligence Applications in Smart Grid, CIASG
ISSN (Print)2326-7682
ISSN (Electronic)2326-7690

Other

Other2013 IEEE Computational Intelligence Applications in Smart Grid, CIASG 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Country/TerritorySingapore
CitySingapore
Period4/16/134/19/13

Keywords

  • clustering
  • data explosion
  • model errors
  • power system visualization
  • spark lines
  • transient stability data

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Computer Science Applications

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