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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2012 - 15
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 HIGH-IMPACT PAPER 

Nonlinear Adaptive NeuroFuzzy Wavelet Based Damping Control Paradigm for SSSC

BADAR, R. See more information about BADAR, R. on SCOPUS See more information about BADAR, R. on IEEExplore See more information about BADAR, R. on Web of Science, KHAN, L. See more information about KHAN, L. on SCOPUS See more information about KHAN, L. on SCOPUS See more information about KHAN, L. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (810 KB) | Citation | Downloads: 671 | Views: 3,653

Author keywords
SSSC, SMIB power system, power system stability, adaptive neurofuzzy control, wavelet neural network

References keywords
power(15), series(12), fuzzy(11), control(9), wavelet(8), controller(8), panda(7), neural(7), damping(7), compensator(7)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 97 - 104
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03015
Web of Science Accession Number: 000308290500015
SCOPUS ID: 84865851562

Abstract
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Static Synchronous Series Compensator (SSSC) is a series compensating Flexible AC Transmission System (FACTS) controller with primary objective of power flow control on a line by injecting a voltage in series with transmission line. However, it can efficiently be used for improving the system stability by using a supplementary damping control system. In this work, Adaptive Neurofuzzy Wavelet Control (ANFWC) paradigm for SSSC supplementary damping control system has been proposed and successfully applied to a Single Machine Infinite Bus (SMIB) power system. Gradient descent based back propagation algorithm, being simple with sufficient efficiency, has been used to update the controller parameters. The robustness of the proposed control strategy has been validated using nonlinear time domain simulations for different faults and various operating conditions of power system. Finally, the results have been compared with Conventional Adaptive Takagi-Sugino Controller (CATC) on the basis of different performance indices.


References | Cited By  «-- Click to see who has cited this paper

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[2] M. El-Mousri, A. M. Sharaf and K. El-Arroudi, "Optimal control schemes for SSSC for dynamic series compensation," Elect. Power Syst. Research, vol. 78, no. 4, pp. 646-656, April. 2008.
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[CrossRef] [SCOPUS Times Cited 3]


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[CrossRef] [SCOPUS Times Cited 7]


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[14] V. Topalov, G. L. Cascella, V. Giordano, F. Cupertino, and O. Kaynak, "Sliding mode neuro-adaptive control of electrical drives," IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 671-679, Feb. 2007.
[CrossRef] [Web of Science Times Cited 54] [SCOPUS Times Cited 70]


[15] L. Khan and K. L. Lo, "Hybrid micro-GA based FLCs for TCSC and UPFC in a multi-machine environment," Intr. Jr. Electr. Power Syst. Research, vol. 76, no. 9-10, pp. 832-843, Jun. 2006.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 33]


[16] M. J. Er and Y. Gao, "Robust adaptive control of robot manipulators using generalized fuzzy neural networks," IEEE Trans. Ind. Electron., vol. 50, no. 3, pp. 620-628, Jun. 2003.
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[CrossRef]


[22] Q.J. Guo, H.-B. Yu, and A.-D. Xu, "Wavelet fuzzy network for fault diagnosis," in Proc. Int. Conf. Commun. Circuits Syst., 2005, pp. 993-998.
[CrossRef]


[23] Y. Lin and F.-Y. Wang, "Predicting chaotic time-series using adaptive wavelet-fuzzy inference system," in Proc. IEEE Intell. Veh. Symp., 2005, pp. 888-893.
[CrossRef] [SCOPUS Times Cited 13]


[24] D. W. C. Ho, P.-A. Zhang, and J. Xu, "Fuzzy wavelet networks for function learning," IEEE Trans. Fuzzy Syst., vol. 9, no. 1, pp. 200-211, Feb. 2001.
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[CrossRef] [SCOPUS Times Cited 21]


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[CrossRef] [SCOPUS Times Cited 15]


[27] A. Kazemi, A. Badri and S. Jadid, "Investigation of two vector control based methods for static synchronous series compensator," IJEEE, vol. 1, no. 4, pp. 1-6, 2005.

[28] J. W. Park, R. G. Harley and G. K. Venayagamoorthy, "Power system optimization and coordination of damping controls by series FACTS devices," in Inaugural IEEE PES Conference and Exhibition, Durban, South Africa, July 11-15, 2005, pp. 293-298.
[CrossRef]


[29] M. Torii and M. T. Hagan, "Stability of steepest descent with momentum for quadratic functions", IEEE Trans. Neural Nets., vol. 13, no. 3, pp. 752-756, May 2002.
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[30] S. Panda, "Robust coordinated design of excitation and STATCOM-based controller using genetic algorithm", Int. Jr. Innov. Comp. and Appl., vol. 1, no. 4, pp. 244-251, 2008.
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[CrossRef] [Web of Science Times Cited 60] [SCOPUS Times Cited 76]


References Weight

Web of Science® Citations for all references: 925 TCR
SCOPUS® Citations for all references: 1,250 TCR

Web of Science® Average Citations per reference: 30 ACR
SCOPUS® Average Citations per reference: 40 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-08-09 04:03 in 165 seconds.




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