• DocumentCode
    2065353
  • Title

    A pre-procedure of bad data detection for smart grid monitoring

  • Author

    Bei Gou ; Kavasseri, R.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., North Dakota State Univ., Fargo, ND, USA
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a pre-procedure to detect and identify gross errors including topology errors for state estimation in smart grid. This pre-procedure is characterized to be fast The key idea behind the procedure is the concept of a solving path, which avoids the chance of divergence when calculating system states using all the measurments in traditional state estimation algorithms. An integer linear programming (ILP) formulation is used to select the solving paths. After a solving path is identified, an error analysis procedure (immune to topology errors) is developed to detect, identify and eliminate gross measurement errors. The subsequent measurement set is used as input to the weighted least squares (WLS) state estimation. The proposed approach is illustrated on the IEEE 14 and 118 bus test systems.
  • Keywords
    error analysis; integer programming; least squares approximations; linear programming; measurement errors; phasor measurement; power system state estimation; smart power grids; IEEE 118 bus test systems; IEEE 14 bus test systems; bad data detection; error analysis; gross errors; gross measurement errors; integer linear programming; power system state estimation; smart grid monitoring; solving paths; topology errors; weighted least squares; Current measurement; Measurement uncertainty; Noise measurement; Phasor measurement units; State estimation; Topology; Voltage measurement; Integer Programming; Phasor Measurement Unit; Solving Path; State Estimation;
  • 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.2012.6345554
  • Filename
    6345554