• DocumentCode
    694978
  • Title

    Value at risk estimation of a power system including wind generation

  • Author

    Usman, M. Dzulhafizi ; Shaaban, Mohamed

  • Author_Institution
    Centre of Electr. Energy Syst. (CEES), Univ. Teknol. Malaysia (UTM), Skudai, Malaysia
  • fYear
    2013
  • fDate
    16-17 Dec. 2013
  • Firstpage
    534
  • Lastpage
    539
  • Abstract
    Reckoning the risk of load loss, corresponding to a certain event, into a single MW value can be of premium importance to system operators to quickly initiate a remedial action, if necessary. In this paper, risk to system load loss, due to the inclusion of variable wind generation, is estimated using the value at risk (VaR) concept. Monte Carlo simulation (MCS) is used to construct the wind speed model, through Weibull statistical distribution and a multistate model, as well as the annual load profile, through randomization. A six-bus test system is used to apply the developed notions. Results of incorporating wind turbine generation with the test system, among other conventional generators, have shown that the risk levels increases appreciably. The ease at which the system risk is identified and encapsulated into a quantifiable MW estimate, remains the salient attractive feature of the developed tool.
  • Keywords
    Monte Carlo methods; Weibull distribution; power system management; risk management; wind power plants; Monte Carlo simulation; Weibull statistical distribution; load loss of; multistate model; power system; risk estimation; value at risk concept; variable wind generation; wind speed model; wind turbine generation; Correlation; Load modeling; Reactive power; Uncertainty; Wind power generation; Wind speed; Monte Carlo simulation; power systems; value at risk; wind generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research and Development (SCOReD), 2013 IEEE Student Conference on
  • Conference_Location
    Putrajaya
  • Type

    conf

  • DOI
    10.1109/SCOReD.2013.7002649
  • Filename
    7002649