• DocumentCode
    3602435
  • Title

    Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources

  • Author

    Pengwei Du ; Weifeng Li ; Xinda Ke ; Ning Lu ; Ciniglio, Orlando A. ; Colburn, Mitchel ; Anderson, Phillip M.

  • Author_Institution
    Electr. Reliability Council of Texas (ERCOT), Taylor, TX, USA
  • Volume
    6
  • Issue
    4
  • fYear
    2015
  • Firstpage
    1263
  • Lastpage
    1271
  • Abstract
    This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.
  • Keywords
    power generation planning; probability; wind power plants; ATC assessment; Idaho Power Co; PDF; available transfer capability assessment; load ensembles; planned wind sites; probability density functions; transmission corridor; wind ensembles; wind generation resources; Probabilistic logic; Time series analysis; Wind farms; Wind power generation; Wind speed; Available transfer capacity; composite methods; renewable integration; stochastic planning; transmission planning; uncertainty quantification; variable generation resources; wind scenario generation;
  • fLanguage
    English
  • Journal_Title
    Sustainable Energy, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3029
  • Type

    jour

  • DOI
    10.1109/TSTE.2015.2425354
  • Filename
    7111359