• DocumentCode
    270930
  • Title

    An approach to achieving global optimum of AC electric power system state estimators

  • Author

    Yang Weng ; Ilić, Marija D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2014
  • fDate
    19-22 Feb. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper is motivated by the open questions concerning the ability to compute the global optimum of nonlinear state estimators (SE). The major cause of these problems comes from the highly nonlinear functions relating measurements and voltages defined by the AC power flow models. Conventional approaches in today´s AC electric power system SE are prone to sub-optimal solutions, which, in turn, creates unacceptably large differences between the true and estimated voltages. In this paper, we first formulate the problem as an equivalent convex optimization problem. We then account for the specific structure of the problem, and arrive at an efficient algorithm for finding the global optimum, namely the most accurate estimate of the state. Notably, under the no noise assumption this approach for the first time solved the problem exactly. Further, we show that our estimate is close to the global optimum even when measurement noise is present, while currently used SE only finds a local optimum. Simulations are shown to illustrate improved results obtained using the SE formulation proposed in this paper over the results obtained using today´s SE.
  • Keywords
    convex programming; load flow; power system measurement; power system state estimation; AC electric power system state estimator; AC power flow model; SE; equivalent convex optimization problem; noise measurement; nonlinear state estimator; voltage estimation; Noise; Noise measurement; Optimization; Polynomials; Power systems; State estimation; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/ISGT.2014.6816456
  • Filename
    6816456