ARTEMISA AI@IFIC Hackday: Predicting renewable energy outputs using Machine Learning

1001-Primera-135 - Nave Exp. Sala de Audiovisuales (Universe)

1001-Primera-135 - Nave Exp. Sala de Audiovisuales


Jose Enrique Garcia Navarro (IFIC (Instituto de Fisica Corpuscular)), Veronica Sanz (University of Sussex)

Artemisa is co-funded by European Funds through the 2014-2020 ERDF Operative Programme of Comunitat Valenciana, project IDIFEDER/2018/048.

Note the new room -- Audiovisuales en la Nave Experimental

This is the first of AI@IFIC hackdays, this time focusing on an issue important to climate change, the accurate prediction of variable energy sources such as wind and solar. 

During this half-day we will explore the use of Machine Learning techniques to forecast variable low-carbon energy sources. We will start by using public sources such as 

Photovoltaic UK data

and correlate them with weather measurements and projections to predict future production. 

The idea is to explore a range of methods such as RNNs and LSTMs as well as regular NNs.

Previous to the meeting, we ask participants to register in Google Colab and/or setup their computers to run jupyter notebooks and conda. We may release a docker for this meeting.

For more details, please consult this Google Docs

Google Doc with links and instructions


Registration-- just to estimate room size
  • Alvaro Fernandez Casani
  • Andrew Laing
  • Carlos García Montoro
  • Carmen Garcia
  • Florencia Luciana Castillo
  • Gabriel Szalkowski
  • Gabriela Barenboim
  • Héctor Ramírez
  • Iván Rosario
  • Javier Muñoz
  • Jesus Guerrero Rojas
  • Jose Enrique Garcia Navarro
  • Josh Renner
  • Juan Jose Hernandez
  • Marco Taoso
  • Maria Moreno Llácer
  • Marija Kekic
  • Mario Gonzalez
  • Miguel Folgado
  • Pablo Martínez-Agulló
  • Pablo Villanueva Domingo
  • Pilar Hernandez
  • Roberto Bruschini
  • Santiago Gonzalez de la Hoz
  • Stefano Gariazzo
  • Tomáš Husek
  • Veronica Sanz
  • Victor Muñoz