• DocumentCode
    601440
  • Title

    A Practical Sizing Method of Energy Storage System Considering the Wind Uncertainty for Wind Turbine Generation Systems

  • Author

    Gao, David Wenzhong ; Babazadeh, Hamed ; Li Lin

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Denver, Denver, CO, USA
  • fYear
    2013
  • fDate
    4-5 April 2013
  • Firstpage
    127
  • Lastpage
    133
  • Abstract
    In this paper, we introduce a new method for finding the proper size of energy storage system (ESS). This design is dedicated to reduce the size of ESS considering the uncertainty of wind speed. It considers the statistical behavior and also the state of charge (SOC) of ESS. The impact of wind uncertainty on power production and its impact on the SOC of ESS are studied. The optimization is done by using the defined uncertainty limits and some other criteria. The probability density function and cumulative density function are calculated in this method. The presented method provides a significant reduction in the size of ESS in terms of power and energy capacity which consequently reduces a considerable capital cost of ESSs for applications in wind turbine generators. The main goal of this design is to reduce the unnecessarily large capacity of ESS which causes the high cost of ESS.. All the calculations and plotting are done using MATLAB.
  • Keywords
    energy storage; mathematics computing; optimisation; probability; turbogenerators; wind power plants; wind turbines; ESS; Matlab; SOC; cumulative density function; energy storage system; optimization; power production; practical sizing method; probability density function; statistical behavior; wind speed uncertainty; wind turbine generation system; wind uncertainty; Batteries; Uncertainty; Wind forecasting; Wind power generation; Wind speed; Wind turbines; Energy storage sizing; probability density function; state of charge; wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Technologies Conference, 2013 IEEE
  • Conference_Location
    Denver, CO
  • ISSN
    2166-546X
  • Print_ISBN
    978-1-4673-5191-1
  • Type

    conf

  • DOI
    10.1109/GreenTech.2013.27
  • Filename
    6520040