DocumentCode :
2503766
Title :
Artificial neural network based SMES unit for transient stability improvement
Author :
Khanna, Rintu ; Singh, Gurnam ; Nagsarkar, T.K.
fYear :
2010
fDate :
20-23 Dec. 2010
Firstpage :
1
Lastpage :
7
Abstract :
This paper discusses artificial neural network (ANN) controlled superconducting magnetic energy storage (SMES) unit for improvement of transient stability of a power system under various system operating conditions and different fault conditions. The inputs to the ANN controller are the deviation in rotor angular velocity Δω of the machine connected to faulted-bus and the voltage deviation Δν of the faulted bus and are used for estimating the control variables-the active power and the reactive power. The results of investigations carried out regarding effectiveness of ANN controlled SMES in improving transient stability of a critically stable two-machine system are presented and compared with proportional type control of SMES.
Keywords :
neurocontrollers; power system control; power system faults; power system transient stability; proportional control; reactive power control; superconducting magnet energy storage; ANN controller; SMES unit; active power control; artificial neural network; faulted-bus; power system; proportional-type control; reactive power control; rotor angular velocity; superconducting magnetic energy storage unit; transient stability improvement; two-machine system; voltage deviation; Artificial neural networks; Control systems; Performance analysis; Power system stability; Transient analysis; Adaptive control; Back-propagation; SMES; SMIB; artificial neural network; critical fault clearing time; firing angle control; power control; power system stabilization; rotor angular velocity control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics, Drives and Energy Systems (PEDES) & 2010 Power India, 2010 Joint International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4244-7782-1
Type :
conf
DOI :
10.1109/PEDES.2010.5712476
Filename :
5712476
Link To Document :
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