• DocumentCode
    134840
  • Title

    Early detection and optimal corrective measures of power system insecurity in enhanced look-ahead dispatch

  • Author

    Yingzhong Gu ; Le Xie

  • Author_Institution
    ECE, Texas A&M Univ., College Station, TX, USA
  • fYear
    2014
  • fDate
    27-31 July 2014
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Summary form only given. This paper presents a novel algorithm for the early detection and optimal corrective measures of power system insecurity in an enhanced look-ahead dispatch framework. By introducing short-term dispatchable capacity (STDC) into the proposed look-ahead security management (LSM) scheme, the algorithm is capable of predicting and identifying future infeasibilities that pose security risks to the system under both normal conditions and assumed contingency conditions. An optimal recovery plan can be computed to prevent system insecurity at a minimal cost. Early awareness of such information is of vital importance to the system operators for taking timely actions with more flexible and cost-effective measures. This, in addition to the economic benefits studied in the literature, demonstrate the advantage of security improvement of the look-ahead dispatch framework. The performance of the proposed algorithms is illustrated in a revised 24 bus IEEE Reliability Test System as well as in a practical 5889 bus system.
  • Keywords
    load dispatching; power system management; power system security; IEEE reliability test system; LSM scheme; STDC; contingency conditions; early detection; enhanced look-ahead dispatch framework; look-ahead security management scheme; minimal cost; optimal corrective measures; optimal recovery plan; power system insecurity; security risks; short-term dispatchable capacity; Economics; Educational institutions; Power measurement; Power system reliability; Prediction algorithms; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PES General Meeting | Conference & Exposition, 2014 IEEE
  • Conference_Location
    National Harbor, MD
  • Type

    conf

  • DOI
    10.1109/PESGM.2014.6938982
  • Filename
    6938982