• DocumentCode
    690719
  • Title

    The unit commitment model with wind power connection based on bad operation scenario set

  • Author

    Liu Youbo ; Gao Hongjun ; Gong Hui ; Song Zhaoou ; Ning Nan ; Zhao Xuan

  • Author_Institution
    Sch. of Electr. Eng. & Inf., Sichuan Univ., Chengdu, China
  • fYear
    2013
  • fDate
    8-11 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Based on the study of uncertainty and fluctuation of wind power, a novel algorithm including bad operation scenarios set and robust optimization method was proposed in the paper trying to solve probabilistic unit commitment problem of power system which has wind power generation. According to the power system probabilistic dispatch theory, the conservative indicator to evaluate the value of deterioration for bad scenarios set is established, and the variance is added in the optimization target to suppress some individual bad scenarios which may lead to deterioration of the overall optimization results. Furthermore, energy storage system, which has an inherent ability to mitigate active power fluctuation, was taken into account to contribute to the presented unit commitment models. Finally, the numerical example which includes cost, storage capacity, robustness metric and conservatism degree analysis verifies the effectiveness and practicality of the proposed methods.
  • Keywords
    energy storage; optimisation; power generation dispatch; power generation scheduling; probability; wind power; bad operation scenario set; conservative indicator; energy storage system; power system probabilistic dispatch; probabilistic unit commitment problem; robust optimization; wind power connection; wind power fluctuation; wind power generation; wind power uncertainty; Dispatching; Energy storage; Fluctuations; Load modeling; Niobium; Robustness; Wind power generation; robust optimization; scenarios set; uncertainty; unit commitment; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific
  • Conference_Location
    Kowloon
  • Type

    conf

  • DOI
    10.1109/APPEEC.2013.6837222
  • Filename
    6837222