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A statistical model for estimating electricity produced by wind energy

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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