1 code implementation • 13 Dec 2020 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
The performances of supervised and unsupervised learning methods in cloud segmentation are evaluated.
2 code implementations • 21 Jan 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
We explain how to remove cyclostationary biases in global solar irradiance measurements.
Time Series Analysis Instrumentation and Methods for Astrophysics Image and Video Processing
1 code implementation • 12 Feb 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
Photovoltaic systems are sensitive to cloud shadow projection, which needs to be forecasted to reduce the noise impacting the intra-hour forecast of global solar irradiance.
no code implementations • 15 Feb 2021 • Guillermo Terrén-Serrano, Adnan Bashir, Trilce Estrada, Manel Martínez-Ramón
The energy available in Micro Grid (MG) that is powered by solar energy is tightly related to the weather conditions in the moment of generation.
1 code implementation • 19 Feb 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds.
1 code implementation • 3 Mar 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
Moving clouds affect the global solar irradiance that reaches the surface of the Earth.
1 code implementation • 7 May 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
The optimal decision criterion to find the number of clusters in the mixture models is analyzed and compared between different Bayesian metrics and a sequential hidden Markov model.
no code implementations • 11 Oct 2021 • Guillermo Terrén-Serrano, Manel Martínez-Ramón
The uncertainty of the energy generated by photovoltaic systems incurs an additional cost for a guaranteed, reliable supply of energy (i. e., energy storage).
no code implementations • 20 Sep 2023 • Guillermo Terrén-Serrano, Michael Ludkovski
We propose and analyze the application of statistical functional depth metrics for the selection of extreme scenarios in day-ahead grid planning.