Title :
State space neural network control (SSNNC) of UPFC for compensation power
Author :
Abdelkrim Bouanane;Mohamed Amara;Abdelkader Chaker
Author_Institution :
Electrotechnical Engineering Laboratory, Department of electrical engineering, University Dr. Moulay Taher Saida Algeria
Abstract :
In our present communication, we present the effectiveness of the controller´s Unified Power Flow Controller UPFC with the choice of a control strategy. This Unified Power Flow Controller (UPFC) is used to control the power flow in the transmission systems by controlling the impedance, voltage magnitude and phase angle. This controller offers advantages in terms of static and dynamic operation of the power system. It also brings in new challenges in power electronics and power system design. To evaluate the performance and robustness of the system, we proposed a hybrid control combining the concept of identification neural networks with conventional regulators (SSNNC) and with the changes in characteristics of the transmission line in order to improve the stability of the electrical power network. With its unique capability to control simultaneously real and reactive power flows on a transmission line as well as to regulate voltage at the bus where it is connected, this device creates a tremendous quality impact on power system stability. The result which has been obtained from using Matlab and Simulink software showed a good agreement with the simulation result.
Keywords :
"Mathematical model","Reactive power","Aerospace electronics","Neural networks","Load flow","Inverters","Power system stability"
Conference_Titel :
Renewable and Sustainable Energy Conference (IRSEC), 2015 3rd International
Electronic_ISBN :
2380-7393
DOI :
10.1109/IRSEC.2015.7455135