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Prethodno priopćenje
https://doi.org/10.17559/TV-20191011133311

Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning

Sedat Nazlibilek* ; School of Electrical and Electronics Engineering, Baskent University, 06810, Ankara
Issa Ali ; Department of Electric and Electronic Engineering, Higher Institute of Science and Technology, 16328, Jadu, Libya
Alyaseh Askir ; Department of Mechatronics Engineering, AL- Zawia University, 16418, Zawia, Libya

Puni tekst: engleski, pdf (545 KB) str. 657-662 preuzimanja: 22* citiraj
APA 6th Edition
Nazlibilek*, S., Ali, I. i Askir, A. (2021). Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning. Tehnički vjesnik, 28 (2), 657-662. https://doi.org/10.17559/TV-20191011133311
MLA 8th Edition
Nazlibilek*, Sedat, et al. "Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning." Tehnički vjesnik, vol. 28, br. 2, 2021, str. 657-662. https://doi.org/10.17559/TV-20191011133311. Citirano 12.05.2021.
Chicago 17th Edition
Nazlibilek*, Sedat, Issa Ali i Alyaseh Askir. "Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning." Tehnički vjesnik 28, br. 2 (2021): 657-662. https://doi.org/10.17559/TV-20191011133311
Harvard
Nazlibilek*, S., Ali, I., i Askir, A. (2021). 'Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning', Tehnički vjesnik, 28(2), str. 657-662. https://doi.org/10.17559/TV-20191011133311
Vancouver
Nazlibilek* S, Ali I, Askir A. Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning. Tehnički vjesnik [Internet]. 2021 [pristupljeno 12.05.2021.];28(2):657-662. https://doi.org/10.17559/TV-20191011133311
IEEE
S. Nazlibilek*, I. Ali i A. Askir, "Improvement of Power System Small-Signal Stability by Artificial Neural Network Based on Feedback Error Learning", Tehnički vjesnik, vol.28, br. 2, str. 657-662, 2021. [Online]. https://doi.org/10.17559/TV-20191011133311

Sažetak
Electrical power systems usually suffer from instabilities because of some disturbances occurring due to environmental conditions, system failures, and loading conditions. The most frequently encountered problem is the loss of synchronization between the rotor angle and the stator magnetic angle for synchronous generators. The contribution of this study is that a nonlinear adaptive control approach called feedback error learning (FEL) is utilized to improve the small-signal stabilities of an electric power system. The power system under study is composed of a synchronous machine connected to infinite bus. Many advantages of FEL control approach makes it capable to robustly adapting with all possible operating conditions rather than using optimization algorithms for tuning the conventional power system stabilizer (CPSS) that is still unsatisfactory especially at some critical operating points. The performances of two controllers, namely the proposed FEL scheme and the conventional controller CPSS, are tested by Matlab simulations. It is found that the FEL controller can be effectively used as an alternative stabilizer for improving small-signal stabilities of the power

Ključne riječi
artificial neural network; conventional PSS; conventional power system stabilizer; feedback error learning; SMIB power system

Hrčak ID: 255883

URI
https://hrcak.srce.hr/255883

Posjeta: 47 *