• DocumentCode
    1721934
  • Title

    Comparing wind generation profiles: A circular data approach

  • Author

    Martins, Ana ; Carvalho, Alda ; Sousa, Jorge A. M.

  • Author_Institution
    BRU-UNIDE, ISEL, Lisbon, Portugal
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour(s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour(s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese sys- em.
  • Keywords
    environmental factors; government policies; statistical analysis; wind power plants; Portugal; Portuguese power system; circular data statistical methods; energy policies; environmental policies; farm production; power systems; spatial wind generation profiles; time 15 min; wind power energy; wind power profiles; wind production profiles; Histograms; Power systems; Production; Standards; Wind farms; Wind power generation; Wind speed; Renewable generation; circular statistics; wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Energy Market (EEM), 2015 12th International Conference on the
  • Conference_Location
    Lisbon
  • Type

    conf

  • DOI
    10.1109/EEM.2015.7216766
  • Filename
    7216766