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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 644266260
doi: 10.4316/AECE


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  3/2012 - 15
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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
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Download PDF pdficon (810 KB) | Citation | Downloads: 579 | Views: 2,630

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

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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

[1] N. G. Hingorani and L. Gyugyi, Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems, IEEE, New York, 2000.

[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.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 24]

[3] W. Qiao and R. G. Harley, "Indirect adaptive external neurocontrol for a series capacitive reactance compensator based on a voltage source PWM converter in damping power oscillations," IEEE Trans. Industrial Electronics, vol. 54, no. 1, pp. 77-85, Feb. 2007.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 22]

[4] W. Qiao and R. G. Harley, "An indirect adaptive external neurocontroller for series capacitive reactance compensator in damping power oscillations", in Proc. 13th International Conference on Intelligent Systems Application to Power Systems, Washington DC, USA, Nov. 6-10, 2005, pp. 234-239.
[CrossRef] [SCOPUS Record]

[5] W. Qiao, R. G. Harley and Ganesh K. Venayagamoorthy, "Neural-Network-based intelligent control for improving dynamic performance of FACTS devices", in 2007 iREP symposium- Bulk Power System Dynamics and Control - VII, Revitalizing Operational Reliability, Charleston, SC, USA, August pp. 19-24, 2007.
[CrossRef] [SCOPUS Record]

[6] S. Panda, N. P. Padhy, R. N. Patel, "Power-system stability improvement by PSO optimized SSSC-based damping controller," Elect. Power Comp. Syst., vol. 36, pp. 468-490, 2008.
[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 55]

[7] S. Panda, S. C. Swain, P. K. Rautray, R. K. Malik, G. Panda, "Design and analysis of SSSC-based damping controller," Simul. Model. Pract. Theor., vol. 18, pp. 1199-1213, 2010.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 43]

[8] S. Panda, "Modeling, simulation and optimal tuning of SSSC based controller in a multi-machine power system", World Jr. Model. and Simul., vol. 6, no. 2, pp. 110-121, 2010.

[9] S. C. Swain, A. K. Balirsingh, S. Mahapatra and S. Panda, "Design of static synchronous series compensator based damping controller employing real coded genetic algorithm", Intr. Jr Elect. Electronic Engg., vol. 5, no. 3, pp. 180-188, 2011.

[10] S. C. Swain, A. K. Balirsingh, S. Mahapatra and S. Panda, "New external neuro-controller for series capacitive reactance compensator in a power network", IEEE Trans. Power. Syst., vol. 9, no. 3, pp. 1462-1472, 2004.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 28]

[11] L. S. Kumar and A. Gosh, "Modeling and control design of a static synchronous series compensator," IEEE Trans. Power Deliv., vol. 14, no. 4, pp. 1448-1453, Oct. 1999.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 63]

[12] Wang, H. F., "Static synchronous series compensator to damp power system oscillations," Elect. Power Syst. Res., vol. 54, pp. 113-119, 2000.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 67]

[13] L. Gu, X. Zhou, M. Liu and H. Shi, "Nonlinear adaptive controller design of SSSC for damping inter-area oscillation," WSEAS Trans. Circu. Syst., vol. 9, no. 4, pp. 228-237, April. 2010.

[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 38] [SCOPUS Times Cited 59]

[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 14] [SCOPUS Times Cited 28]

[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.
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 78]

[17] L. Khan, S. Anjum and R. Badar, "Standard fuzzy model identification using gradient methods," World Appl. Sci. Jr., vol. 8, no. 1, pp. 1-9, 2010.

[18] R. H. Abiyev and O. Kaynak, "Fuzzy wavelet neural networks for identification and control of dynamic plants- A novel structure and a comprehensive study," IEEE Trans. Indus. Elect., vol.55, no.8, pp. 3133-3140, 2008.
[CrossRef] [Web of Science Times Cited 105] [SCOPUS Times Cited 142]

[19] C. K. Lin and S. D. Wang, "Fuzzy modeling using wavelet transform," Electron. Lett., vol. 32, no. 24, pp. 2255-2256, Nov. 1996.
[CrossRef] [Web of Science Times Cited 14]

[20] M. Thuillard, "Fuzzy logic in the wavelet framework," in Proc. Toolmet, Oulu, Finland, Apr. 13-14, 2000.

[21] M. Thuillard, Wavelets in Softcomputing. Singapore: World Scientific, 2001.

[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.

[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 9]

[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.
[CrossRef] [Web of Science Times Cited 169] [SCOPUS Times Cited 213]

[25] R. H. Abiyev, "Controller based of fuzzy wavelet neural network for control of technological processes," in Proc. IEEE Int. CISMA, Giardini Naxos, Italy, 2005, pp. 215-219.
[CrossRef] [SCOPUS Times Cited 11]

[26] R. H. Abiyev, "Time series prediction using fuzzy wavelet neural network model," in Lecture Notes in Computer Sciences, vol. 4132. Berlin, Germany: Springer-Verlag, 2006, pp. 191-200.

[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.

[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.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 34]

[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.
[CrossRef] [SCOPUS Times Cited 3]

[31] E. G. Romera, M. A. Jaramillo and D. C. Fernandez, "Monthly electric energy demand forecasting with neural networks and Fourier series", Energy Conv. Mang., vol. 49, pp. 3135-3142, 2008.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 51]

References Weight

Web of Science® Citations for all references: 616 TCR
SCOPUS® Citations for all references: 930 TCR

Web of Science® Average Citations per reference: 20 ACR
SCOPUS® Average Citations per reference: 30 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 2016-12-05 02:55 in 131 seconds.

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