Implications of the Weibull K Factor in Resource Assessment

This study investigates the implication of the site specific wind speed distribution on the energy production of a wind turbine generator. It will proof that the average wind speed and the power density are not a good measure on how well a turbine will perform; the performance depends on how well a...

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Autores principales: Thamhain, Mathias, Storm, Brandon
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2012
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/100216
http://www.aero.ing.unlp.edu.ar/cliv2/public/actas%20congreso/31.Thamhain.CLIV2.pdf
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id I19-R120-10915-100216
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
spellingShingle Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
Thamhain, Mathias
Storm, Brandon
Implications of the Weibull K Factor in Resource Assessment
topic_facet Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
description This study investigates the implication of the site specific wind speed distribution on the energy production of a wind turbine generator. It will proof that the average wind speed and the power density are not a good measure on how well a turbine will perform; the performance depends on how well a power curve corresponds to the wind speed distribution. The Weibull distribution is commonly used to describe the probability distribution of wind speed at a given location. Two parameters, the scale factor (c, also sometimes referred to as A) and the shape factor (k) are sufficient to describe a curve which approximates the probability distribution of the wind speed.The Rayleigh distribution (defined as a Weibull distribution with the shape factor k = 2), is considered frequently as a reference frequency distribution. EAPC ́s practical experience in wind resource assessment in Southern Latin America has revealed a broad variety of shape factors beyond the standard k=2. We have also found that for a given mean wind speed, different shape factors lead to different magnitude of annual energy production on the other. This is especially the case for high wind speeds, where impact on annual energy production can be 15% or higher.
format Objeto de conferencia
Objeto de conferencia
author Thamhain, Mathias
Storm, Brandon
author_facet Thamhain, Mathias
Storm, Brandon
author_sort Thamhain, Mathias
title Implications of the Weibull K Factor in Resource Assessment
title_short Implications of the Weibull K Factor in Resource Assessment
title_full Implications of the Weibull K Factor in Resource Assessment
title_fullStr Implications of the Weibull K Factor in Resource Assessment
title_full_unstemmed Implications of the Weibull K Factor in Resource Assessment
title_sort implications of the weibull k factor in resource assessment
publishDate 2012
url http://sedici.unlp.edu.ar/handle/10915/100216
http://www.aero.ing.unlp.edu.ar/cliv2/public/actas%20congreso/31.Thamhain.CLIV2.pdf
work_keys_str_mv AT thamhainmathias implicationsoftheweibullkfactorinresourceassessment
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