Statistical profiling of site wind resource speed and directional characteristics

Bruce Stephen, Stuart Galloway, David McMillan, Lucy Anderson, Graham Ault

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Construction of a wind farm without a reliable plant margin forecast can jeopardize potential returns on investment from the outset. Meteorological and topological factors influence the wind characteristics across any site which in turn affects wind farm output, critical for localized generation, and also the dynamic loading of the turbine structure. The models developed in this paper follow the generally advocated use of probability density estimation as a means of representing wind resource characteristics but, owing to difference in characterization that may be encountered, do not assume a single distribution form across all sites. A mixture modelling approach is adopted that removes the need for choosing distribution forms on a site by site basis. Advancing previous work constructing statistical distributions over congruent wind speed and direction observations of the wind resource characteristics at a given site, the proposed model, as a consequence of using a mixture distribution, captures both recurring regimes in the site behaviour along with their frequency of occurrence. Preliminary results using data sets from a diverse range of locations in Scotland demonstrate the variation in the forms of model learned; comparisons of the model with current and alternate practices are given through visualization and resource assessment illustrations.
LanguageEnglish
Pages583-592
Number of pages10
JournalIET Renewable Power Generation
Volume7
Issue number6
Early online date31 Oct 2013
DOIs
Publication statusPublished - Nov 2013

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Keywords

  • wind speed
  • statistical profiling
  • wind energy
  • mixture modelling approach
  • site wind resource speed representation

Cite this

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abstract = "Construction of a wind farm without a reliable plant margin forecast can jeopardize potential returns on investment from the outset. Meteorological and topological factors influence the wind characteristics across any site which in turn affects wind farm output, critical for localized generation, and also the dynamic loading of the turbine structure. The models developed in this paper follow the generally advocated use of probability density estimation as a means of representing wind resource characteristics but, owing to difference in characterization that may be encountered, do not assume a single distribution form across all sites. A mixture modelling approach is adopted that removes the need for choosing distribution forms on a site by site basis. Advancing previous work constructing statistical distributions over congruent wind speed and direction observations of the wind resource characteristics at a given site, the proposed model, as a consequence of using a mixture distribution, captures both recurring regimes in the site behaviour along with their frequency of occurrence. Preliminary results using data sets from a diverse range of locations in Scotland demonstrate the variation in the forms of model learned; comparisons of the model with current and alternate practices are given through visualization and resource assessment illustrations.",
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Statistical profiling of site wind resource speed and directional characteristics. / Stephen, Bruce; Galloway, Stuart; McMillan, David; Anderson, Lucy; Ault, Graham.

In: IET Renewable Power Generation, Vol. 7, No. 6, 11.2013, p. 583-592.

Research output: Contribution to journalArticle

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