VARIABILTY OF LONG TERM ESTIMATES OF HYDRO POWER GENERATION ON A EUROPEAN SCALE

Valentina Sessa (1) , Edi Assoumou (1) , Sílvia Carvalho (2)

1 CMA - Centre de Mathématiques Appliquées
2 CCIAM - Climate Change Impact Adaptation And Modelling [Lisboa]

Hydropower is the world's most dominant (86%) source of renewable electrical energy. It strictly depends on the geography and weather peculiarity of locations where power plants are settled. We use machine learning techniques for producing long term estimates of hydro power capacity factors for all European countries based on future climate scenarios.

Domaines: Optimisation et contrôle [math.OC]; Machine Learning [stat.ML]

Valentina Sessa, Edi Assoumou, Sílvia Carvalho. VARIABILTY OF LONG TERM ESTIMATES OF HYDRO POWER GENERATION ON A EUROPEAN SCALE. Internation Conference on Applied Energy, Aug 2019, Vasteras, Switzerland. ⟨hal-02317459⟩