• DocumentCode
    105332
  • Title

    Transmission Planning Under Uncertainties of Wind and Load: Sequential Approximation Approach

  • Author

    Heejung Park ; Baldick, Ross

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA
  • Volume
    28
  • Issue
    3
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    2395
  • Lastpage
    2402
  • Abstract
    This paper introduces a transmission planning model for a system integrating a large amount of remote wind power. We consider uncertainties of wind availability and system load, which are represented by two dependent random variables in the optimization problem. A two-stage stochastic model and sequential approximation approach are applied to solve our total cost minimization problem, which involves a sequence of stochastic optimization problems repeatedly solved with an updated approximation of random parameters until the rate of increment of optimal cost becomes smaller than a positive target value. A wind energy integration goal is achieved by penalizing wind curtailment. As a case study, the Electric Reliability Council of Texas (ERCOT) wind and load data, and a simplified model of its transmission system, is employed.
  • Keywords
    approximation theory; optimisation; power transmission planning; stochastic processes; wind power plants; cost minimization problem; load uncertainty; optimal cost; optimization problem; remote wind power; sequential approximation approach; stochastic optimization problem; transmission planning model; two-stage stochastic model; wind uncertainty; Approximation methods; Generators; Planning; Random variables; Stochastic processes; Uncertainty; Wind power generation; Sequential approximation; stochastic optimization; transmission expansion planning; wind power;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2013.2251481
  • Filename
    6485015