DocumentCode :
1846305
Title :
Robust design of PID power system stabilizer in multi-machine power system using artificial intelligence techniques
Author :
Jalilvand, A. ; Aghmasheh, R. ; Khalkhali, E.
Author_Institution :
Dept. of Electr. Eng., Zanjan Univ., Zanjan, Iran
fYear :
2010
fDate :
23-24 June 2010
Firstpage :
38
Lastpage :
42
Abstract :
This paper presents robust tuning of Proportional Integral Derivative Power System Stabilizers (PID-PSS) using artificial intelligence (AI) techniques. Tow heuristic methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used to PID-PSS parameters tuning minimizing an objective function and results are compared with each other which Eigen value analysis is used for comparison. The proposed method is confirmed by obtained simulation results of a Three-Machine power system under different operating conditions.
Keywords :
artificial intelligence; eigenvalues and eigenfunctions; genetic algorithms; particle swarm optimisation; power engineering computing; power system stability; PID-PSS parameters tuning; artificial intelligence techniques; eigenvalue analysis; genetic algorithm; multimachine power system; particle swarm optimization; proportional integral derivative power system stabilizers; Artificial intelligence; Generators; Loading; Optimization; Power system dynamics; Power system stability; controllability; observability; particle swarm optimization; power system stabilizer; root locus;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2010 4th International
Conference_Location :
Shah Alam
Print_ISBN :
978-1-4244-7127-0
Type :
conf
DOI :
10.1109/PEOCO.2010.5559178
Filename :
5559178
Link To Document :
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