IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v36y2011i2p823-828.html
   My bibliography  Save this article

A statistical model for estimating electricity produced by wind energy

Author

Listed:
  • Tar, Károly
  • Szegedi, Sándor

Abstract

Potential wind power for a given period (e.g. a day) can be determined from wind speed data measured in certain hours of a period. Obviously, the sum of the cubes of wind speeds measured depends on the number of measurements. This dependence can be reduced in two ways: determining the average and the relative wind energy for a given time within a given period. The method of sliding averages uses both. Applying this method a given hourly average wind speed cube of a day is estimated on the basis of wind speeds measured in that hour of the day. Cubes of the wind speeds are in proportion with the total daily potential and produced wind energy. This model requires long-time series of wind speed data that are available only for weather stations in Hungary, where hourly average winds speeds are registered.

Suggested Citation

  • Tar, Károly & Szegedi, Sándor, 2011. "A statistical model for estimating electricity produced by wind energy," Renewable Energy, Elsevier, vol. 36(2), pages 823-828.
  • Handle: RePEc:eee:renene:v:36:y:2011:i:2:p:823-828
    DOI: 10.1016/j.renene.2010.06.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148110002880
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2010.06.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tar, Károly, 2008. "Energetic characterization of near surface windfield in Hungary," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 250-264, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Economic performance indicators of wind energy based on wind speed stochastic modeling," Applied Energy, Elsevier, vol. 154(C), pages 290-297.
    2. Marvuglia, Antonino & Messineo, Antonio, 2012. "Monitoring of wind farms’ power curves using machine learning techniques," Applied Energy, Elsevier, vol. 98(C), pages 574-583.
    3. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tar, Károly & Farkas, István & Rózsavölgyi, Kornél, 2011. "Climatic conditions for operation of wind turbines in Hungary," Renewable Energy, Elsevier, vol. 36(2), pages 510-518.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:36:y:2011:i:2:p:823-828. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.