Sessions
Forecasting: deep learning meets secure data sharing
When: Thursday, 23 April 2026, 13:30 - 14:15
Where: N107, N108
Session description
The more renewables we get on the grid, the more and the better forecasts of the production over the next minutes, days and weeks we need. In this session we investigate how to make the forecasts better with the use of AI, and how to provide more and better input data from neighbouring wind farms while preserving the commercially sensitive information.
Presentations
A Unified Multi-Horizon Forecasting Framework for Wind Power Using AI
Rubén Martínez
Data Scientist, Instituto de Ingeniería del Conocimiento (IIC)
Combining Deep Learning, PCA and Gradient Boosting for Short-Term Wind Energy Forecasting
Ignacio Villanueva
CEO and Full Professor in Mathematics, Ravenwits
Privacy-preserving data sharing for collaborative spatio-temporal wind power forecasting
Georges Kariniotakis
Professor, Mines Paris - PSL
