• DocumentCode
    1493378
  • Title

    Look-ahead voltage and load margin contingency selection functions for large-scale power systems

  • Author

    Chiang, Hsiao-Dong ; Wang, Cheng-Shan ; Flueck, Alexander J.

  • Author_Institution
    Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
  • Volume
    12
  • Issue
    1
  • fYear
    1997
  • fDate
    2/1/1997 12:00:00 AM
  • Firstpage
    173
  • Lastpage
    180
  • Abstract
    Given the current operating condition (obtained from the real-time data), the near-term load demand at each bus (obtained from short-term load forecast), and the generation dispatch (say, based on economic dispatch), we present in this paper a load margin measure (MW and/or MVAr) to assess the system´s ability to withstand the forecasted load and generation variations. We also present a method to predict near-term system voltage profiles. The proposed look-ahead measure and the proposed voltage prediction are then applied to contingency selections for the near-term power system in terms of load margins to collapse and of the bus voltage magnitudes. We evaluate the proposed look-ahead measure and the voltage profile prediction on several power systems including a 1169-bus power system with 53 contingencies with promising results
  • Keywords
    economics; load dispatching; load forecasting; power systems; 1169-bus power system; bus voltage magnitudes; economic dispatch; forecasted load withstand; generation dispatch; generation variations; load margin contingency selection function; load margins; look-ahead voltage function; near-term load demand; near-term power system; near-term system voltage profiles; operating condition; power systems; short-term load forecast; Economic forecasting; Large-scale systems; Load forecasting; Load management; Performance analysis; Power system analysis computing; Power system measurements; Power system stability; Power systems; Voltage;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.574937
  • Filename
    574937