• DocumentCode
    2252045
  • Title

    Graphical observer design suitable for large-scale DAE power systems

  • Author

    Scholtz, E. ; Lesieutre, B.C.

  • Author_Institution
    ABB Corp. Res., Raleigh, NC, USA
  • fYear
    2008
  • fDate
    9-11 Dec. 2008
  • Firstpage
    2955
  • Lastpage
    2960
  • Abstract
    In this paper we discuss an intuitive observer design approach that is suitable for large-scale systems, such as power systems. In arriving at this approach we drew inspiration from the field of linear structured systems, where qualitative statements (e.g., solvability of the fault detection and identification (FDI) problem, controllability) about the system are made by analyzing the structure of the system. Our emphasis is design and we use information regarding the structure of the system as well as the actual values of specific entries in the system matrices to design observer-based monitors. These monitors can estimate the state of the system or detect and identify specific occurrences of faults in the system, all in the presence of disturbances and uncertainty. In this paper we demonstrate our design approach by designing observer-based monitors for electromechanical dynamics on a small 3-bus and an intermediate-sized 179-bus power system model.
  • Keywords
    CAD; large-scale systems; matrix algebra; observers; power systems; electromechanical dynamics; graphical observer design; intuitive observer design; large-scale DAE power systems; large-scale systems; linear structured systems; observer-based monitors; system matrices; Controllability; Electrical fault detection; Fault detection; Fault diagnosis; Large-scale systems; Power system analysis computing; Power system dynamics; Power system faults; Power system modeling; Power systems; Fault Detection and Isolation; Observers; State Estimation; System-Wide Monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2008. CDC 2008. 47th IEEE Conference on
  • Conference_Location
    Cancun
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-3123-6
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2008.4739260
  • Filename
    4739260