Open AccessArtificial Intelligence Control Applied in Wind Energy Conversion System
Author(s) -
Arama Fatima Zohra,
Bousserhane Ismail Khalil,
Slimane Laribi,
Youcef Sahli,
B. Mazari
Publication year - 2018
Publication title -
international journal of power electronics and drive systems (ijpeds)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.322
H-Index - 21
ISSN - 2088-8694
DOI - 10.11591/ijpeds.v9.i2.pp571-578
Subject(s) - control theory (sociology) , robustness (evolution) , regulator , vector control , matlab , doubly fed electric machine , wind power , computer science , induction generator , artificial neural network , ac power , control engineering , engineering , control (management) , induction motor , voltage , artificial intelligence , chemistry , biochemistry , electrical engineering , gene , operating system
The objective of this paper is to study the dynamic response of the wind energy conversion system (WECS) based on the Doubly Fed Induction Generator (DFIG). The DFIG rotor is connected to the grid via a converter. The active and reactive power control is realized by the DFIG rotor variables control, using the field oriented control (FOC). The vector control of DFIG is applied by the use of tow regulators PI and the neural network regulator (NN). The generator mathematical model is implemented in Matlab/ Simulink software to simulate a DFIG of 1.5 MW in order to show the efficiency of the performances and robustness of the studied control systems. The simulation obtained results shows that the robustness and response time of the neural network regulator is better than those obtained by the PI classical regulator.