Arbitrated Ensemble for Solar Radiation Forecasting

  • Vítor CerqueiraEmail author
  • Luís Torgo
  • Carlos Soares
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10305)


Utility companies rely on solar radiation forecasting models to control the supply and demand of energy as well as the operability of the grid. They use these predictive models to schedule power plan operations, negotiate prices in the electricity market and improve the performance of solar technologies in general. This paper proposes a novel method for global horizontal irradiance forecasting. The method is based on an ensemble approach, in which individual competing models are arbitrated by a metalearning layer. The goal of arbitrating individual forecasters is to dynamically combine them according to their aptitude in the input data. We validate our proposed model for solar radiation forecasting using data collected by a real-world provider. The results from empirical experiments show that the proposed method is competitive with other methods, including current state-of-the-art methods used for time series forecasting tasks.


Solar radiation forecasting Renewable energy Ensemble methods Metalearning Time series 



This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013; Project “NORTE-01-0145-FEDER-000036” is financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Vítor Cerqueira
    • 1
    • 2
    Email author
  • Luís Torgo
    • 1
    • 2
  • Carlos Soares
    • 1
    • 2
  1. 1.INESC TECPortoPortugal
  2. 2.University of PortoPortoPortugal

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