Open AccessOptimal tuning of PI controllers using adaptive particle swarm optimization for doubly-fed induction generator connected to the grid during a voltage dip
Author(s) -
Elmostafa Chetouani,
Youssef Errami,
Abdellatif Obbadi,
Smail Sahnoun
Publication year - 2021
Publication title -
bulletin of electrical engineering and informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 12
ISSN - 2302-9285
DOI - 10.11591/eei.v10i5.2843
Subject(s) - control theory (sociology) , particle swarm optimization , induction generator , stator , maximum power principle , ac power , rotor (electric) , wind power , vector control , pid controller , voltage , converters , engineering , computer science , control engineering , induction motor , electrical engineering , temperature control , control (management) , machine learning , artificial intelligence
This paper proposes the adaptive particle swarm optimization (APSO) technique to control the active and reactive power produced by a variable wind energy conversion system and the exchanged power between the electric grid and the system during a voltage dip (VD). Besides, to get the variable speed wind energy maximum power, a maximum power point (MPP) methodology is utilized. The system under study is a 5 MW wind turbine connected via a gearbox to a doubly-fed induction generator (DFIG). The DFIG stator is branched directly to the electrical network, while the Back-to-Back converters couple the rotor to the grid. The decoupled vector control of the rotor side converter and the grid side converter is established primarily by a conventional proportional-integral (PI) and a second level by an intelligent PI whose gains are tuned using the proposed control. The performances and results obtained by APSO tuned PI controllers are analyzed and compared with those attained by classical PI controllers through the MATLAB/Simulink. The superiority of the advised technique is examined during a two-phase short-circuit fault condition and confirmed by the reduced oscillations.