• DocumentCode
    1330225
  • Title

    Representative Operating and Contingency Scenarios for the Design of UFLS Schemes

  • Author

    Sigrist, Lukas ; Egido, Ignacio ; Sánchez-Úbeda, Eugenio F. ; Rouco, Luis

  • Author_Institution
    Sch. of Eng. ICAI, Univ. Pontificia Comillas, Madrid, Spain
  • Volume
    25
  • Issue
    2
  • fYear
    2010
  • fDate
    5/1/2010 12:00:00 AM
  • Firstpage
    906
  • Lastpage
    913
  • Abstract
    This paper studies an approach to identify representative operating and contingency (OC) scenarios for the design of underfrequency load-shedding (UFLS) schemes. In small isolated power systems, contingency scenarios are outages of generating units. Usually, only N-1 outages are considered. In this paper, simultaneous outages of several units are also taken into account. Data mining techniques such as K-Means and Fuzzy C-Means algorithms are used to group scenarios in terms of system frequency and to identify representative OC scenarios. The approach has been applied to the design of UFLS schemes of two of the Spanish isolated power systems. The results have also been compared to the common practice of scenario selection. Clustering techniques yielded to satisfactory results, i.e., representative OC scenarios can be identified. Furthermore, these representative OC scenarios cover a wider range of possible system responses than the scenarios selected following the common practice.
  • Keywords
    data mining; load shedding; pattern clustering; power engineering computing; power system stability; Spanish isolated power systems; UFLS scheme design; clustering techniques; data mining techniques; frequency stability; fuzzy C-means algorithms; k-mean algorithm; power systems stability; underfrequency load-shedding scheme design; Clustering methods; frequency stability; load shedding;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2009.2031839
  • Filename
    5332249