• DocumentCode
    3760568
  • Title

    A study on short-term trading and optimal operation strategy for virtual power plant

  • Author

    Chunfa Dong;Xin Ai;Shuai Guo;Kunyu Wang;Yiran Liu;Le Li

  • Author_Institution
    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China
  • fYear
    2015
  • Firstpage
    2672
  • Lastpage
    2677
  • Abstract
    A virtual power plant (VPP) model, which consists of a wind power plant, interruptible loads, a pumped storage plant and a gas turbine, is built considering the uncertainty of the power output of renewable energy sources (RES) as well as the participation of demand response (DR) resources. Multi-scenario method is used to deal with the uncertainty of day-ahead market price and power output of wind power plant. A short-term trading model, which is based on multi-stage stochastic programming with the objective of maximization of VPP bidding profits in day-ahead market combined with penalty in balancing market, is constructed considering the characteristic that the uncertainty of stochastic variables reduces when time approaches. It is shown that the model constructed could notably promote the certainty gain of VPP.
  • Keywords
    "Stochastic processes","Decision support systems","Uncertainty","Programming","Optimization","Wind power generation"
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2015 5th International Conference on
  • Type

    conf

  • DOI
    10.1109/DRPT.2015.7432700
  • Filename
    7432700