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

Ana Lagos, Joaquín E. Caicedo, Gustavo Coria, Andrés Romero Quete, Maximiliano Martínez, Gastón Suvire and Jesús Riquelme ()
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Ana Lagos: Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan 5400, Argentina
Joaquín E. Caicedo: Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110311, Colombia
Gustavo Coria: Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan 5400, Argentina
Andrés Romero Quete: Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan 5400, Argentina
Maximiliano Martínez: Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan 5400, Argentina
Gastón Suvire: Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan 5400, Argentina
Jesús Riquelme: Departamento de Ingeniería Eléctrica, Universidad de Sevilla, 41092 Sevilla, Spain

Energies, 2022, vol. 15, issue 18, 1-40

Abstract: 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.

Keywords: wind speed forecasting; wind power forecasting; distributed generation; microgrid; urban; residential (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:18:p:6545-:d:909362

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