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Journal of Artificial Intelligence in Electrical Engineering
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(2013). Design of A Self-Tuning Adaptive Power System Stabilizer. Journal of Artificial Intelligence in Electrical Engineering, 2(5), 11-21.
. "Design of A Self-Tuning Adaptive Power System Stabilizer". Journal of Artificial Intelligence in Electrical Engineering, 2, 5, 2013, 11-21.
(2013). 'Design of A Self-Tuning Adaptive Power System Stabilizer', Journal of Artificial Intelligence in Electrical Engineering, 2(5), pp. 11-21.
Design of A Self-Tuning Adaptive Power System Stabilizer. Journal of Artificial Intelligence in Electrical Engineering, 2013; 2(5): 11-21.

Design of A Self-Tuning Adaptive Power System Stabilizer

Article 2, Volume 2, Issue 5, Spring 2013, Page 11-21  XML PDF (879 K)
Abstract
Power system stabilizers (PSSs) must be capable of providing appropriate stabilization signals over a
broad range of operating conditions and disturbances. The main idea of this paper is changing a
classic PSS (CPSS) to an adaptive PSS using genetic algorithm. This new genetic algorithm based on
adaptive PSS (GAPSS) improves power system damping, considerably. The controller design issue is
formulated as an optimization problem that is solved by GA to identify PSS parameters in various
operating conditions. Numerical simulation studies have been done on a modified model of IEEE
second benchmark. The consequence of these studies shows that, the performance of the suggested
genetic algorithm based adaptive PSS in damping of electromechanical oscillations of power system is
better than CPSS.
Keywords
Power System Stabilizer; Genetic Algorithm; Adaptive Controller; Electromechanical Oscillations
References
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Dynamics”, Academic Press, 1983.
[2] P.Hoang, K. Tomsovic, “Design and Analysis
of an Adaptive Fuzzy Power System
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[3] Abdelazim, Tamer, O. P. Malik, “An Adaptive
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Engineering Society 2003 General Meeting,
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[4] P. Shamsollahi, O. P. Malik, “An Adaptive
Power System Stabilizer Using On-Line
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on Energy Conversion, Vol. 12, Page(s): 382-
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[6] K.A. Folly, “Design of Power System
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Learning”, IEEE Power Engineering Society
General Meeting, on CD, June 2006.
[7] V.Miranda, S.Srinivasan, L.Proenca,
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89-98, January 1998.
[8] E.R.C.Viveros, G.N.Taranto, D.M.Falcao,
“Coordinated Tuning of AVRs and PSSs by
Multi-Objective Genetic Algorithms”, ISAP
2005, Page(s): 247-252, 2005.
[9] K. J. Astrom, B. Wittenmark, “Adaptive
Control”, Addison Wesley, 1989.
[10] Benjamin C. Kua, “Automatic control
systems”, Prentice Hall of India, 2003.

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