• DocumentCode
    112221
  • Title

    Price-Based Unit Commitment With Wind Power Utilization Constraints

  • Author

    Qianfan Wang ; Jianhui Wang ; Yongpei Guan

  • Author_Institution
    Ind. & Syst. Eng. Dept., Univ. of Florida, Gainesville, FL, USA
  • Volume
    28
  • Issue
    3
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    2718
  • Lastpage
    2726
  • Abstract
    This paper proposes an optimal bidding strategy for independent power producers (IPPs) in the deregulated electricity market. The IPPs are assumed to be price takers, whose objectives are to maximize their profits considering price and wind power output uncertainties, while ensuring high wind power utilization. The problem is formulated as a two-stage stochastic price-based unit commitment problem with chance constraints to ensure wind power utilization. In our model, the first stage decision includes unit commitment and quantity of electricity submitted to the day-ahead market. The second stage decision includes generation dispatch, actual usage of wind power, and amount of energy imbalance between the day-ahead and real-time markets. The chance constraint is applied to ensure a certain percentage of wind power utilization so as to comply with renewable energy utilization regulations. Finally, a sample average approximation (SAA) approach is applied to solve the problem, and the computational results are reported for the proposed SAA algorithm showing the sensitivity of the total profit as the requirement of wind power utilization changes.
  • Keywords
    approximation theory; power generation dispatch; power generation scheduling; power markets; power utilisation; wind power; IPP; SAA; deregulated electricity market; energy imbalance; generation dispatch; independent power producers; optimal bidding strategy; renewable energy utilization regulations; sample average approximation; stochastic price; unit commitment problem; wind power utilization constraints; Convergence; Electricity; Generators; Real-time systems; Stochastic processes; Uncertainty; Wind power generation; Chance constrains; mixed integer programming; price based unit commitment; sample average approximation; stochastic programming; wind power;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2012.2231968
  • Filename
    6401219