Medium term load forecasting using ANFIS predictor.

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)

Nowadays, there are huge ranges of energy market participants. Commercial success of this area actor depends on the ability to submit competitive predictions relative to energy balance trends Thus, it seems convenient to "anticipate" this parameter evolution in time in order to act consequently and resort to protective actions. In this context, this paper proposes a tool for energy balance prediction based on ANFIS (Adaptive Neuro Fuzzy Inference System). This neuro- fuzzy predictor is modified in order to obtain an accurate forecasting for medium term. The solutions are illustrated on a real application and take into account the known "future”: the programmed actions.

Mots clés: ANFIS (Adaptive Neuro Fuzzy Inference System); forecasting; renewable energy; medium term.; medium term

Domaines: Automatique / Robotique

Otilia Elena Dragomir, Florin Dragomir, Rafael Gouriveau, Eugénia Minca. Medium term load forecasting using ANFIS predictor.. 18th Mediterranean Conference on Control & Automation, MED'10., Jun 2010, Marrakech, Morocco. pp.551-556. ⟨hal-00544696⟩