• DocumentCode
    3510150
  • Title

    Probabilistic reliability assessment in the optimization of hybrid power generating units

  • Author

    Kumar, Ajit ; Zaman, Muhammad H. ; Goel, Nishith ; Goel, Nishith ; Church, Ron

  • Author_Institution
    Tecsis Corp., Ottawa, ON, Canada
  • fYear
    2012
  • fDate
    10-12 Oct. 2012
  • Firstpage
    75
  • Lastpage
    79
  • Abstract
    The unit size optimization analysis for a typical IT company is performed considering hybrid wind - solar systems. The stochastic effects in all the parameters in the optimization models are taken into consideration for estimating power reliability. While weibull distributions are representatives of wind speed and solar insolation data, normal distributions are assumed for hourly load variations. Both deterministic optimization analysis and probabilistic risk assessment results are presented. Typically 15 PVC, 19 wind turbines and 27 battery units meet the power demand at a cost of energy around 0.55 $/ kWhr. Power reliability is estimated to increase steeply with power generating units initially, but tends to get saturated thereafter with diminishing slope.
  • Keywords
    Weibull distribution; battery storage plants; hybrid power systems; optimisation; power generation reliability; risk management; solar power stations; stochastic processes; wind power plants; IT company; Weibull distributions; battery units; deterministic optimization analysis; hybrid power generating unit optimization; hybrid wind-solar systems; power demand; power reliability estimation; probabilistic reliability assessment; probabilistic risk assessment; solar insolation data; stochastic effects; wind speed data; wind turbines; Batteries; Hybrid power systems; Optimization; Power demand; Probabilistic logic; Reliability; Wind turbines; Renewable energy; hybrid system; monte carlo simulation (MCS); power reliability; stochastic effects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Power and Energy Conference (EPEC), 2012 IEEE
  • Conference_Location
    London, ON
  • Print_ISBN
    978-1-4673-2081-8
  • Electronic_ISBN
    978-1-4673-2079-5
  • Type

    conf

  • DOI
    10.1109/EPEC.2012.6474983
  • Filename
    6474983