• DocumentCode
    2039897
  • Title

    A data-driven approach to interactive visualization of power systems

  • Author

    Jun Zhu ; Zhuang, E. ; Ivanov, C. ; Ziwen Yao

  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Summary form only given. Information visualization appears to be a promising technique for improving the business practices in today´s electric power industry. The legacy power system visualization tools, however, restrict the visualization process to follow a limited number of pre-defined patterns created by human designers, thus hindering users´ ability to discover. This paper proposes a data-driven approach to interactive visualization of power systems. The proposed approach relies on developing powerful data manipulation algorithms to create visualizations based on the characteristics of empirically or mathematically derived data. Based on this approach, a data-driven model exploratory tool has been developed to enable users to visualize the power system´s physical/electrical configurations at various levels and from different perspectives. The conducted case studies have demonstrated that the data-driven approach could result in an interactive and user-driven power system visualization tool that fosters scientific understanding and insight, therefore unleashing the power of visualization.
  • Keywords
    data visualisation; electricity supply industry; power engineering computing; data manipulation algorithms; data-driven approach; electric power industry; information visualization; legacy power system visualization tools; power system interactive visualization process; user-driven power system visualization tool; Algorithm design and analysis; Business; Data visualization; Humans; Industries; Mathematical model; Power systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6344595
  • Filename
    6344595