Robust power control of DFIG using artificial neural networks for a wind energy conversion system based energy storage unit
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Date
2018-12-10
Journal Title
Journal ISSN
Volume Title
Publisher
University of Eloued جامعة الوادي
Abstract
This paper presents the control of the dual fed
induction generator (DFIG) using the Artificial Neural Networks
(ANN), used in a variable speed wind energy conversion system.
After having presented the simplified model of the DFIG, we
approached its indirect vector control by stator field orientation. We
focused on PI controllers for the control of active and reactive stator
powers and the impact of its replacement by other neural controllers;
which have a high robustness against parameters variations of
DFIG. Simulation results on a 1.5 MW DFIG system are provided to
demonstrate the robustness of the ANN controllers and the large
interest of energy storage unit in such wind energy conversion
systems.
Description
International Symposium on Mechatronics and Renewable Energies El-Oued 10- 11 December 2018
Keywords
Wind energy, DFIG, Artificial neural networks, Robustness, Storage system.