• DocumentCode
    1406688
  • Title

    Integrating AI applications in an energy management system

  • Author

    Bann, Jeffrey J. ; Irisarri, Guillermo D. ; Mokhtari, Sasan ; Kirschen, Daniel S. ; Miller, Bradley N.

  • Author_Institution
    Siemens Power Transmission Distributing, Brooklyn Park, MN, USA
  • Volume
    12
  • Issue
    6
  • fYear
    1997
  • Firstpage
    53
  • Lastpage
    59
  • Abstract
    To effectively integrate expert system applications in an energy management system, the authors created an environment that supports all the interfaces between the AI applications and the EMS. This environment also maintains a model of the power system common to all the AI applications. With this environment in place, users can easily plug AI applications into the EMS. The authors have designed and implemented such an environment, which supports three distinct AI applications: intelligent alarm processing, fault diagnosis, and power system restoration. To illustrate the benefits of this approach, they present case studies based on implementations of this environment in three different EMS architectures
  • Keywords
    alarm systems; expert systems; fault diagnosis; load management; power system analysis computing; power system restoration; EMS; artificial intelligence applications; case studies; energy management system; expert system applications; fault diagnosis; intelligent alarm processing; power system model; power system restoration; Artificial intelligence; Computer architecture; Data structures; Energy management; Expert systems; Medical services; Plugs; Power system dynamics; Power system modeling; Power system security;
  • fLanguage
    English
  • Journal_Title
    IEEE Expert
  • Publisher
    ieee
  • ISSN
    0885-9000
  • Type

    jour

  • DOI
    10.1109/64.642962
  • Filename
    642962