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Robust design of PSS and SVC using teaching-learning based optimization algorithm

V. Talavat, S. Galvani, S. Rezaeian-Marjani

10th International Conference on Electrical and Electronics Engineering - ELECO 2017, Bursa (Turquía). 30 noviembre - 02 diciembre 2017


Resumen:

Power System Stabilizers (PSS) are very effective controllers in generation of supplementary feedback stabilizing signals. Using of PSS in power systems lonely, not only may not improve voltage stability but also cause great variations in the voltage. In the other hand, Flexible AC Transmission Systems (FACTS) such as Static VAr Compensations (SVC) has been used for dynamic control voltage, increasingly. Incoordination of PSS and SVC parameters can have undesirable effects on generator angle and voltage oscillations. So, simultaneous coordination of PSS and SVC parameters is highly regarded. This paper determines the optimal parameters of PSS and SVC using Teaching-Learning based Optimization (TLBO) algorithm in such a way that the power system withstands against a wide range of contingencies, effectively.


Fecha de publicación: noviembre 2017.



Cita:
Talavat, V., Galvani, S., Rezaeian-Marjani, S., Robust design of PSS and SVC using teaching-learning based optimization algorithm, 10th International Conference on Electrical and Electronics Engineering - ELECO 2017, Bursa (Turquía). 30 noviembre - 02 diciembre 2017.

IIT-17-273C

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