Wind energy forecasting with neural networks: a literature review

Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecast...

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Detalles Bibliográficos
Autores: Manero, Jaume, Béjar Alonso, Javier|||0000-0001-5281-3888, Cortés García, Claudio Ulises|||0000-0003-0192-3096
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/129113
Acceso en línea:https://hdl.handle.net/2117/129113
https://dx.doi.org/10.13053/CyS-22-4-3081
Access Level:acceso abierto
Palabra clave:Machine learning
Neural networks (Computer science)
Forecasting
Wind power
Wind power forecast
Wind speed forecast
Short-term prediction
Deep learning
Literature review
Aprenentatge automàtic
Xarxes neuronals (Informàtica)
Previsió
Energia eòlica
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
Àrees temàtiques de la UPC::Energies::Energia eòlica
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oai_identifier_str oai:upcommons.upc.edu:2117/129113
network_acronym_str ES
network_name_str España
repository_id_str
spelling Wind energy forecasting with neural networks: a literature reviewManero, JaumeBéjar Alonso, Javier|||0000-0001-5281-3888Cortés García, Claudio Ulises|||0000-0003-0192-3096Machine learningNeural networks (Computer science)ForecastingWind powerWind power forecastWind speed forecastShort-term predictionDeep learningLiterature reviewAprenentatge automàticXarxes neuronals (Informàtica)PrevisióEnergia eòlicaÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàticÀrees temàtiques de la UPC::Energies::Energia eòlicaRenewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these methods are being used commercially around the world. But one family of new methods for wind power fore castingis surging based on Machine Learning Deep Learning techniques. This paper analyses the characteristics of the Wind Speed time series data and performs a literature review of recently published works of wind power forecasting using Machine Learning approaches (neural and deep learning networks), which have been published in the last few years.Peer Reviewed20182018-01-0120192019-02-14journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/129113https://dx.doi.org/10.13053/CyS-22-4-3081reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1291132026-05-27T15:37:01Z
dc.title.none.fl_str_mv Wind energy forecasting with neural networks: a literature review
title Wind energy forecasting with neural networks: a literature review
spellingShingle Wind energy forecasting with neural networks: a literature review
Manero, Jaume
Machine learning
Neural networks (Computer science)
Forecasting
Wind power
Wind power forecast
Wind speed forecast
Short-term prediction
Deep learning
Literature review
Aprenentatge automàtic
Xarxes neuronals (Informàtica)
Previsió
Energia eòlica
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
Àrees temàtiques de la UPC::Energies::Energia eòlica
title_short Wind energy forecasting with neural networks: a literature review
title_full Wind energy forecasting with neural networks: a literature review
title_fullStr Wind energy forecasting with neural networks: a literature review
title_full_unstemmed Wind energy forecasting with neural networks: a literature review
title_sort Wind energy forecasting with neural networks: a literature review
dc.creator.none.fl_str_mv Manero, Jaume
Béjar Alonso, Javier|||0000-0001-5281-3888
Cortés García, Claudio Ulises|||0000-0003-0192-3096
author Manero, Jaume
author_facet Manero, Jaume
Béjar Alonso, Javier|||0000-0001-5281-3888
Cortés García, Claudio Ulises|||0000-0003-0192-3096
author_role author
author2 Béjar Alonso, Javier|||0000-0001-5281-3888
Cortés García, Claudio Ulises|||0000-0003-0192-3096
author2_role author
author
dc.subject.none.fl_str_mv Machine learning
Neural networks (Computer science)
Forecasting
Wind power
Wind power forecast
Wind speed forecast
Short-term prediction
Deep learning
Literature review
Aprenentatge automàtic
Xarxes neuronals (Informàtica)
Previsió
Energia eòlica
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
Àrees temàtiques de la UPC::Energies::Energia eòlica
topic Machine learning
Neural networks (Computer science)
Forecasting
Wind power
Wind power forecast
Wind speed forecast
Short-term prediction
Deep learning
Literature review
Aprenentatge automàtic
Xarxes neuronals (Informàtica)
Previsió
Energia eòlica
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
Àrees temàtiques de la UPC::Energies::Energia eòlica
description Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these methods are being used commercially around the world. But one family of new methods for wind power fore castingis surging based on Machine Learning Deep Learning techniques. This paper analyses the characteristics of the Wind Speed time series data and performs a literature review of recently published works of wind power forecasting using Machine Learning approaches (neural and deep learning networks), which have been published in the last few years.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01
2019
2019-02-14
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/129113
https://dx.doi.org/10.13053/CyS-22-4-3081
url https://hdl.handle.net/2117/129113
https://dx.doi.org/10.13053/CyS-22-4-3081
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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