Title :
Artificial neural networks controller for power system voltage improvement
Author :
Messalti, Sabir ; Boudjellal, Bilal ; Said, Azouz
Author_Institution :
Electr. Eng. Dept., Univ. of M´sila, M´sila, France
Abstract :
In this paper, power system voltage improvement using wind turbine is presented. Two controllers are used: a PI controller and Artificial Neural Networks (ANN) controller are investigated. The power flow exchanged between the wind turbine and the power system has been controlled in order to improve the bus voltage based on reactive power injection (or absorption) produced by variable speed wind turbine. The wind turbine is based on a doubly fed induction generator (DFIG) controlled by field-oriented control. Indirect control is used to control of the reactive power flow exchanged between the DFIG and the power system. The proposed controllers are tested on power system for large voltage disturbances.
Keywords :
PI control; load flow control; machine vector control; neurocontrollers; voltage control; wind turbines; ANN controller; DFIG; PI controller; artificial neural networks controller; bus voltage; doubly fed induction generator; field-oriented control; power system; power system voltage improvement; reactive power injection; variable speed wind turbine; voltage disturbances; Artificial neural networks; Reactive power; Rotors; Stator windings; Voltage control; Wind turbines; Artificial Neural Networks controller; Field-oriented control(FOC); PI controller; double fed induction generator (DFIG); power system voltage improvement;
Conference_Titel :
Renewable Energy Congress (IREC), 2015 6th International
Conference_Location :
Sousse
DOI :
10.1109/IREC.2015.7110897
