• DocumentCode
    2103944
  • Title

    The Optimal Power Purchase of Distribution Utility Considering the Impact of Decision-Making

  • Author

    Bai, Xiaoli ; Lei, Xia ; Yu, Dongxian

  • Author_Institution
    Sch. of Electr. & Inf., Xihua Univ., Chengdu, China
  • fYear
    2010
  • fDate
    28-31 March 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Distribution utility purchases power in multi-periods, and the decision-making at risk before this period must affect that the distribution utility makes decision to this period. For this reason, Multi-period conditional value at risk (CVaR) is used to measure the dynamic risk when distribution utility purchases power and the decision-making of power purchase are dynamically revised by Bayesian methods. In multi-markets, the optimal model of power purchase is simulated in multi-periods to minimize the risks and achieve the optimal power allocation by genetic algorithm at the given confidence level. As the simulation shows the power purchase model of dynamically revision can better reflect the risk distribution utility faces and the practically revenue rates at minimum risk.
  • Keywords
    decision making; distributed power generation; power engineering computing; power markets; Bayesian methods; decision making; genetic algorithm; optimal power allocation; optimal power purchase; power market; risk distribution utility; Bayesian methods; Contracts; Decision making; Electric variables measurement; Electricity supply industry; Genetic algorithms; Portfolios; Power markets; Power measurement; Reactive power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4812-8
  • Electronic_ISBN
    978-1-4244-4813-5
  • Type

    conf

  • DOI
    10.1109/APPEEC.2010.5448856
  • Filename
    5448856