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Short-term wind speed forecasting in Uruguay using computational intelligence.
Zucatelli, P J; Nascimento, E G S; Aylas, G Y R; Souza, N B P; Kitagawa, Y K L; Santos, A A B; Arce, A M G; Moreira, D M.
Afiliación
  • Zucatelli PJ; Federal University of Espírito Santo-UFES, ES, Brazil.
  • Nascimento EGS; Manufacturing and Technology Integrated Campus - SENAI CIMATEC, BA, Brazil.
  • Aylas GYR; Manufacturing and Technology Integrated Campus - SENAI CIMATEC, BA, Brazil.
  • Souza NBP; Federal University of Espírito Santo-UFES, ES, Brazil.
  • Kitagawa YKL; Federal University of Espírito Santo-UFES, ES, Brazil.
  • Santos AAB; Manufacturing and Technology Integrated Campus - SENAI CIMATEC, BA, Brazil.
  • Arce AMG; Universidad de la República - UDELAR, Montevideo, Uruguay.
  • Moreira DM; Federal University of Espírito Santo-UFES, ES, Brazil.
Heliyon ; 5(5): e01664, 2019 May.
Article en En | MEDLINE | ID: mdl-31193100
Short-term wind speed forecasting for Colonia Eulacio, Soriano Department, Uruguay, is performed by applying an artificial neural network (ANN) technique to the hourly time series representative of the site. To train the ANN and validate the technique, data for one year are collected by one tower, with anemometers installed at heights of 101.8, 81.8, 25.7, and 10.0 m. Different ANN configurations are applied for each site and height; then, a quantitative analysis is conducted, and the statistical results are evaluated to select the configuration that best predicts the real data. This method has lower computational costs than other techniques, such as numerical modelling. For integrating wind power into existing grid systems, accurate short-term wind speed forecasting is fundamental. Therefore, the proposed short-term wind speed forecasting method is an important scientific contribution for reliable large-scale wind power forecasting and integration in Uruguay. The results of the short-term wind speed forecasting showed good accuracy at all the anemometer heights tested, suggesting that the method is a powerful tool that can help the Administración Nacional de Usinas y Transmissiones Eléctricas manage the national energy supply.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies País/Región como asunto: America do sul / Uruguay Idioma: En Revista: Heliyon Año: 2019 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies País/Región como asunto: America do sul / Uruguay Idioma: En Revista: Heliyon Año: 2019 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido