Forecasting of renewable energy balance on Medium Term.

Otilia Elena Dragomir (1) , Florin Dragomir (2) , Rafael Gouriveau (3) , Eugénia Minca (2)

1 Automation and Information Department - Electrical Engineering Faculty
2 Dep. of Automation, Computer Science and Elec. Eng
3 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

The general purpose of the paper is to explore the way of performing renewable energy balance predictions prognostics so that energy market actors can act consequently. Different aspects of forecasting are discussed to point out pragmatic challenges of this approach. An illustration, with real monitored data, based on a neuro-fuzzy predictor is given. The architecture of the artificial intelligence technique used for forecasting is modified in order to obtain accurate estimations for medium term.

Mots clés: Forecasting; neuro-fuzzy; renewable energy balance; photovoltaic system.; photovoltaic system

Domaines: Automatique / Robotique

Otilia Elena Dragomir, Florin Dragomir, Rafael Gouriveau, Eugénia Minca. Forecasting of renewable energy balance on Medium Term.. Conference "Large Scale Systems, Theory and Applications", LSS'10., Jul 2010, Villeneuve d'Ascq, France. pp.1-6. ⟨hal-00544703⟩