DocumentCode
753643
Title
Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Author
Abdel-magid, Y.L. ; Abido, M.A.
Author_Institution
Electr. Eng. Dept., King Fahd Univ. of Pet. & Minerals, Dhahran, Saudi Arabia
Volume
18
Issue
3
fYear
2003
Firstpage
1125
Lastpage
1132
Abstract
Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. A conventional speed-based lead-lag PSS is used in this work. The multimachine power system operating at various loading conditions and system configurations is treated as a finite set of plants. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all plants to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. The effectiveness of the suggested technique in damping local and interarea modes of oscillations in multimachine power systems, over a wide range of loading conditions and system configurations, is confirmed through eigenvalue analysis and nonlinear simulation results.
Keywords
damping; eigenvalues and eigenfunctions; genetic algorithms; oscillations; power system dynamic stability; dynamic stability; eigenvalue analysis; eigenvalue-based multiobjective function; genetic algorithms; interarea modes; lightly damped electromechanical modes; loading conditions; local modes; multimachine power system; nonlinear simulation; optimal multiobjective design; optimization; robust multimachine power system stabilizers; robust power system stabilizers; speed-based lead-lag PSS; undamped electromechanical modes; Algorithm design and analysis; Damping; Genetic algorithms; Power system analysis computing; Power system dynamics; Power system simulation; Power system stability; Power systems; Robust stability; Robustness;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2003.814848
Filename
1216155
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