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