Prediction of Small-Wind Turbine Performance from Time Series Modelling Using Intelligent Techniques

• Santiago Porras ^[1] ; Esteban Jove ^[2] ; Bruno Baruque ^[1] ; José Luis Calvo-Rolle ^[2]
  1. [1] Universidad de Burgos

     Universidad de Burgos

     Burgos, España

     
  2. [2] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
• Localización: Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference: Guimarães, Portugal; November 4–6, 2020. Proceedings / Cesar Analide (ed. lit.), Paulo Novais (ed. lit.) , David Camacho Fernández (ed. lit.) , Hujun Yin (ed. lit.), Vol. 2, 2020 (Part II), ISBN 978-3-030-62365-4, págs. 541-548
• Idioma: inglés
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• Resumen

  • The present research work deals the model creation obtaining for power generation prediction of a small-wind turbine, based on the atmospheric variables of its location. For testing purposes, a real dataset has been obtained of a bio-climate house located in Sotavento Experimental Wind Farm in the north of Spain. A deep study of the system and atmospheric variables has been performed. Then, some different regression techniques have been tested for accomplishing prediction, obtaining excellent results.