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A generalized linear model approach to seasonal aspects of wind speed modeling

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  • Alain Bensoussan
  • Pierre Bertrand
  • Alexandre Brouste

Abstract

The aim of the article is to identify the intraday seasonality in a wind speed time series. Following the traditional approach, the marginal probability law is Weibull and, consequently, we consider seasonal Weibull law. A new estimation and decision procedure to estimate the seasonal Weibull law intraday scale parameter is presented. We will also give statistical decision-making tools to discard or not the trend parameter and to validate the seasonal model.

Suggested Citation

  • Alain Bensoussan & Pierre Bertrand & Alexandre Brouste, 2014. "A generalized linear model approach to seasonal aspects of wind speed modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1694-1707, August.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:8:p:1694-1707
    DOI: 10.1080/02664763.2014.888543
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    References listed on IDEAS

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    1. Lun, Isaac Y.F & Lam, Joseph C, 2000. "A study of Weibull parameters using long-term wind observations," Renewable Energy, Elsevier, vol. 20(2), pages 145-153.
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    Cited by:

    1. Ren'e Aid & Pierre Gruet & Huy^en Pham, 2015. "An optimal trading problem in intraday electricity markets," Papers 1501.04575, arXiv.org.
    2. Lepore, Antonio & Palumbo, Biagio & Pievatolo, Antonio, 2020. "A Bayesian approach for site-specific wind rose prediction," Renewable Energy, Elsevier, vol. 150(C), pages 691-702.
    3. René Aïd & Pierre Gruet & Huyên Pham, 2015. "An optimal trading problem in intraday electricity markets," Working Papers hal-01104829, HAL.

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