• DocumentCode
    51974
  • Title

    Identifying Parameter Errors via Multiple Measurement Scans

  • Author

    Liuxi Zhang ; Abur, Ali

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
  • Volume
    28
  • Issue
    4
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    3916
  • Lastpage
    3923
  • Abstract
    This paper investigates the problem of network parameter error detection and identification in power systems. Recently, a parameter error identification method which is based on Lagrange multipliers corresponding to a single measurement scan has been developed. This paper provides an improvement of this method via the use of multiple measurement scans which increases the local redundancy at no additional cost. This leads to identification of errors which could otherwise not be identified. The paper presents a detailed analysis of the limitations of the single scan method and also shows the relationship between the number of scans, the normalized Lagrange multipliers and the normalized residuals. The presented method is easy to implement since estimation of different scans can be executed independent of each other by using an existing state estimation program. Simulations on IEEE 14-, 30-, and 118-bus systems are provided to illustrate the proposed approach of parameter error identification.
  • Keywords
    IEEE standards; power system measurement; power system parameter estimation; power system state estimation; IEEE 118-bus system; IEEE 14-bus system; IEEE 30-bus system; costing; multiple measurement scanning; network parameter error detection; normalized Lagrange multiplier; parameter error identification method; power system identification; state estimation program; Bad data processing; multiple measurement scans; optimization; parameter errors; state estimation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2013.2254504
  • Filename
    6514677