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Nonlinear Adaptive NeuroFuzzy Wavelet Based Damping Control Paradigm for SSSCBADAR, R.![]() ![]() ![]() ![]() ![]() ![]() |
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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
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. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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