DocumentCode
2501017
Title
UPFC online PI controller design using particle swarm optimization algorithm and artificial neural networks
Author
Asadi, Mohammad Reza ; Sadr, Vahid Gohari
Author_Institution
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran
fYear
2008
fDate
1-3 Dec. 2008
Firstpage
473
Lastpage
478
Abstract
Sometimes power utilities in contingency conditions should work far away from their pre-designed conditions. Various control strategies have been reported recently to control UPFC in different operating conditions. PI regulators used for controlling UPFC suffer from the inadequacies of providing suitable control and transient stability enhancement over a wide range of system operating conditions. A new adaptive controller using particle swarm optimization (PSO) algorithm and artificial neural networks (ANN) is proposed to improve efficiency of UPFCpsilas PI controller in damping power system oscillations. The effectiveness of the proposed method is demonstrated through computer simulation using a multi-machine power system with a single UPFC.
Keywords
PI control; neural nets; particle swarm optimisation; power system control; PI regulators; UPFC online PI controller design; adaptive controller; artificial neural networks; computer simulation; multi-machine power system; particle swarm optimization algorithm; power system oscillations; transient stability enhancement; Adaptive control; Algorithm design and analysis; Artificial neural networks; Control systems; Particle swarm optimization; Power system simulation; Power system stability; Power system transients; Programmable control; Regulators; Power system stability; UPFC; adaptive controller; inter-area oscillations; neural networks; particle swarm optimization (PSO);
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International
Conference_Location
Johor Bahru
Print_ISBN
978-1-4244-2404-7
Electronic_ISBN
978-1-4244-2405-4
Type
conf
DOI
10.1109/PECON.2008.4762520
Filename
4762520
Link To Document