• DocumentCode
    889948
  • Title

    An Algorithm for Automatically Tuning the Weights of Performance Indices for Monitoring Power System Loading or Security

  • Author

    Fischl, R. ; Halpin, T.F. ; Helferty, J.J. ; Gershman, V. ; Mercede, F.

  • Author_Institution
    Department of Electrical and Computer Engineering Drexel University Philadelphia, PA 19104
  • Volume
    1
  • Issue
    3
  • fYear
    1986
  • Firstpage
    207
  • Lastpage
    213
  • Abstract
    This paper presents an algorithm for automatically updating the coefficients of performance indices (PI) used to monitor power system´s security, loading or network adequacy, as the system operating conditions change. The objective of the algorithm is to maximize the effectiveness of the PI in terms of predicting operating limit violations. This is accomplished by tuning the PI coefficients so that the PI measures the robustness of the operating point to system changes in terms of how far the point is from the operating limits. The approach taken is to formulate the coefficient optimization problem as a constrained volume maximization problem, in which the PI coefficients are used to maximize the volume of an approximate convex set (defined by the PI) inside the set of all feasible operating points. By exploiting the salient properties of the volume maximization problem, an efficient sequential gradient minimization algorithm has been developed to tune the PI coefficients. This algorithm was implemented to tune the coefficients of the PI used to rank contingencies of the EPRI 39-bus system in accordance to the severity of voltage problems.
  • Keywords
    Computerized monitoring; Constraint optimization; Current measurement; Load flow; Power system reliability; Power system security; Power transmission lines; Reactive power; Transmission line measurements; Voltage;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.1986.4334983
  • Filename
    4334983