• DocumentCode
    2044909
  • Title

    A unit commitment model with demand response for the integration of renewable energies

  • Author

    Ikeda, Y. ; Ikegami, T. ; Kataoka, K. ; Ogimoto, K.

  • Author_Institution
    Collaborative Res. Center for Energy Eng., Univ. of Tokyo, Tokyo, Japan
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast error for renewable energies and the demand response of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms. First we analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increased with the forecast error. Then the effect of a sudden decrease in wind power is analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total operation cost significantly. Finally, the effects of the demand response in the case of a sudden decrease in wind power are analyzed. We confirm that the number of operating thermal power plants is reduced by the demand response. A power utility has to continue to use thermal power plants for ensuring the supply-demand balance; some of these plants can be decommissioned after installing a large number of wind farms or PV systems, if the demand response is applied with an appropriate price structure.
  • Keywords
    photovoltaic power systems; power generation dispatch; power generation scheduling; pricing; renewable energy sources; thermal power stations; time series; wind power plants; PV systems; demand response; electric power utility; forecast error; operation cost; operation reserves; operational state; photovoltaic systems; price structure; renewable energies integration; thermal power plants; time series; unit commitment model; weather conditions; wind farms; Load management; Power systems; Predictive models; Time series analysis; Wind forecasting; Wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6344788
  • Filename
    6344788