• DocumentCode
    1774715
  • Title

    A operational optimization model for wind power and pumped-storage plant based on stochastic programming

  • Author

    Chunliui Liu ; Liudong Zhang ; Wanxia Liu

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2014
  • fDate
    23-26 Sept. 2014
  • Firstpage
    1589
  • Lastpage
    1595
  • Abstract
    Based on the day-ahead forecast of system load and wind power output. A joint operation of pumped-storage and wind power plants model is built with the purpose of minimizing the system operation cost. In order to achieve the higher system flexibility and reduce the impact of volatility of wind power, pumped-storage units are incorporated into the unit commitment (UC) problem with wind power. The UC problem of the joint operation of pumped-storage and wind power plants is formulated as the mixed-integer convex program, which is optimized by Cplex. Conducted on a ten-unit system simulation, we can get the conclusion that the joint operation of pumped-storage and wind power plants is effective to reduce the impact of volatility of wind power on the power grid operation. At the same time, economic benefit is remarkable.
  • Keywords
    convex programming; cost reduction; integer programming; load forecasting; power generation dispatch; power generation economics; power generation scheduling; pumped-storage power stations; stochastic programming; wind power plants; Cplex optimization; UC problem; day-ahead forecasting system; mixed-integer convex program; operation cost minimization; operational optimization model; power grid operation; power system economics; pumped-storage plant; stochastic programming; unit commitment problem; wind power plant; Abstracts; Analytical models; Flowcharts; IP networks; Problem-solving; Programming; Vectors; joint operation; mixed-integer programming; pumped-storage; wind power; wind power scenario;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electricity Distribution (CICED), 2014 China International Conference on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/CICED.2014.6991974
  • Filename
    6991974