Implications of the Weibull K Factor in Resource Assessment

Autores
Thamhain, Mathias; Storm, Brandon
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
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.
Laboratorio de Capa Límite y Fluidodinámica Ambiental
Grupo Fluidodinámica Computacional
Materia
Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/100216

id SEDICI_455dba2a7ad652fb1c1ae78b2c07017e
oai_identifier_str oai:sedici.unlp.edu.ar:10915/100216
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Implications of the Weibull K Factor in Resource AssessmentThamhain, MathiasStorm, BrandonIngeniería AeronáuticaIngeniería AeronáuticaWeibull wind speed distributionEnergy production of a wind turbine generatorThis 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.Laboratorio de Capa Límite y Fluidodinámica AmbientalGrupo Fluidodinámica Computacional2012info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/100216enginfo:eu-repo/semantics/altIdentifier/url/http://www.aero.ing.unlp.edu.ar/cliv2/public/actas%20congreso/31.Thamhain.CLIV2.pdfinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:21:49Zoai:sedici.unlp.edu.ar:10915/100216Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:21:50.147SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Implications of the Weibull K Factor in Resource Assessment
title Implications of the Weibull K Factor in Resource Assessment
spellingShingle Implications of the Weibull K Factor in Resource Assessment
Thamhain, Mathias
Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
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
dc.creator.none.fl_str_mv Thamhain, Mathias
Storm, Brandon
author Thamhain, Mathias
author_facet Thamhain, Mathias
Storm, Brandon
author_role author
author2 Storm, Brandon
author2_role author
dc.subject.none.fl_str_mv Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
topic Ingeniería Aeronáutica
Ingeniería Aeronáutica
Weibull wind speed distribution
Energy production of a wind turbine generator
dc.description.none.fl_txt_mv 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.
Laboratorio de Capa Límite y Fluidodinámica Ambiental
Grupo Fluidodinámica Computacional
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.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/100216
url http://sedici.unlp.edu.ar/handle/10915/100216
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.aero.ing.unlp.edu.ar/cliv2/public/actas%20congreso/31.Thamhain.CLIV2.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844616094111760384
score 13.070432