Publicaciones en las que colabora con Fermín Rodríguez Lalanne (11)

2023

  1. Ensemble forecaster based on the combination of time-frequency analysis and machine learning strategies for very short-term wind speed prediction

    Electric Power Systems Research, Vol. 214

2022

  1. Forecasting intra-hour solar photovoltaic energy by assembling wavelet based time-frequency analysis with deep learning neural networks

    International Journal of Electrical Power and Energy Systems, Vol. 137

  2. Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control

    Energy, Vol. 239

  3. Very short-term parametric ambient temperature confidence interval forecasting to compute key control parameters for photovoltaic generators

    Sustainable Energy Technologies and Assessments, Vol. 51

2021

  1. A very short-term probabilistic prediction interval forecaster for reducing load uncertainty level in smart grids

    Applied Sciences (Switzerland), Vol. 11, Núm. 6

  2. Ensemble of machine learning and spatiotemporal parameters to forecast very short-term solar irradiation to compute photovoltaic generators’ output power

    Energy, Vol. 229

  3. Very short-term temperature forecaster using MLP and N-nearest stations for calculating key control parameters in solar photovoltaic generation

    Sustainable Energy Technologies and Assessments, Vol. 45

2020

  1. Very short-term load forecaster based on a neural network technique for smart grid control

    Energies, Vol. 13, Núm. 19

  2. Very short-term wind power density forecasting through artificial neural networks for microgrid control

    Renewable Energy, Vol. 145, pp. 1517-1527

2019

  1. Optimization of a solar irradiation forecasting tool based on artificial intelligence

    Renewable Energy and Power Quality Journal, Vol. 17, pp. 62-67

2018

  1. Predicting solar energy generation through artificial neural networks using weather forecasts for microgrid control

    Renewable Energy, Vol. 126, pp. 855-864