State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems

The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper pre...

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Detalles Bibliográficos
Autores: Lagos, Ana, Caicedo, Joaquín E., Coria, Gustavo, Romero Quete, Andrés, Martínez, Maximiliano, Suvire, Gastón, Riquelme Santos, Jesús Manuel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/143464
Acceso en línea:https://hdl.handle.net/11441/143464
https://doi.org/10.3390/en15186545
Access Level:acceso abierto
Palabra clave:Wind speed forecasting
Wind power forecasting
Distributed generation
Microgrid
Urban
Residential
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spelling State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power SystemsLagos, AnaCaicedo, Joaquín E.Coria, GustavoRomero Quete, AndrésMartínez, MaximilianoSuvire, GastónRiquelme Santos, Jesús ManuelWind speed forecastingWind power forecastingDistributed generationMicrogridUrbanResidentialThe integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting models for wind turbines located in different segments of power systems, i.e., in large wind farms, distributed generation, microgrids, and micro-wind turbines installed in residences and buildings. This review covers forecasting models based on statistical and physical, artificial intelligence, and hybrid methods, with deterministic or probabilistic approaches. The literature review is carried out through a bibliometric analysis using VOSviewer and Pajek software. A discussion of the results is carried out, taking as the main approach the forecast time horizon of the models to identify their applications. The trends indicate a predominance of hybrid forecast models for the analysis of power systems, especially for those with high penetration of wind power. Finally, it is determined that most of the papers analyzed belong to the very short-term horizon, which indicates that the interest of researchers is in this time horizon.MDPIIngeniería EléctricaTEP196: Sistemas de Energía EléctricaDeutscher Akademischer Austauschdienst (DAAD)Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)CYTED Ciencia y Tecnología para el DesarrolloCERVERA program for Outstanding Research CentersUniversidad Nacional de San JuanSecretaría de Ciencia, Tecnología e Innovación del Distrito Federal (SECITI)Junta de Andalucía2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/143464https://doi.org/10.3390/en15186545reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésEnergies, 15 (18), 6545.718RT0564CER-20191019PDTS 2020-2022PYC20 RE 078 USEhttps://www.mdpi.com/1996-1073/15/18/6545info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1434642026-06-17T12:51:07Z
dc.title.none.fl_str_mv State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
title State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
spellingShingle State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
Lagos, Ana
Wind speed forecasting
Wind power forecasting
Distributed generation
Microgrid
Urban
Residential
title_short State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
title_full State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
title_fullStr State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
title_full_unstemmed State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
title_sort State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems
dc.creator.none.fl_str_mv Lagos, Ana
Caicedo, Joaquín E.
Coria, Gustavo
Romero Quete, Andrés
Martínez, Maximiliano
Suvire, Gastón
Riquelme Santos, Jesús Manuel
author Lagos, Ana
author_facet Lagos, Ana
Caicedo, Joaquín E.
Coria, Gustavo
Romero Quete, Andrés
Martínez, Maximiliano
Suvire, Gastón
Riquelme Santos, Jesús Manuel
author_role author
author2 Caicedo, Joaquín E.
Coria, Gustavo
Romero Quete, Andrés
Martínez, Maximiliano
Suvire, Gastón
Riquelme Santos, Jesús Manuel
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Ingeniería Eléctrica
TEP196: Sistemas de Energía Eléctrica
Deutscher Akademischer Austauschdienst (DAAD)
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
CYTED Ciencia y Tecnología para el Desarrollo
CERVERA program for Outstanding Research Centers
Universidad Nacional de San Juan
Secretaría de Ciencia, Tecnología e Innovación del Distrito Federal (SECITI)
Junta de Andalucía
dc.subject.none.fl_str_mv Wind speed forecasting
Wind power forecasting
Distributed generation
Microgrid
Urban
Residential
topic Wind speed forecasting
Wind power forecasting
Distributed generation
Microgrid
Urban
Residential
description The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting models for wind turbines located in different segments of power systems, i.e., in large wind farms, distributed generation, microgrids, and micro-wind turbines installed in residences and buildings. This review covers forecasting models based on statistical and physical, artificial intelligence, and hybrid methods, with deterministic or probabilistic approaches. The literature review is carried out through a bibliometric analysis using VOSviewer and Pajek software. A discussion of the results is carried out, taking as the main approach the forecast time horizon of the models to identify their applications. The trends indicate a predominance of hybrid forecast models for the analysis of power systems, especially for those with high penetration of wind power. Finally, it is determined that most of the papers analyzed belong to the very short-term horizon, which indicates that the interest of researchers is in this time horizon.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/143464
https://doi.org/10.3390/en15186545
url https://hdl.handle.net/11441/143464
https://doi.org/10.3390/en15186545
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Energies, 15 (18), 6545.
718RT0564
CER-20191019
PDTS 2020-2022
PYC20 RE 078 USE
https://www.mdpi.com/1996-1073/15/18/6545
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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