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Nonlinear Adaptive NeuroFuzzy Wavelet Based Damping Control Paradigm for SSSCBADAR, R. , KHAN, L. |
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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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[1] A PSO-DP Based Method to Determination of the Optimal Number, Location, and Size of FACTS Devices in Power Systems, SHOJAEIAN, S., NAEENI, E. S., DOLATSHAHI, M., KHANI, H., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.01017 [CrossRef] [Full text]
[2] Fully Adaptive Recurrent Neuro-Fuzzy Control for Power System Stability Enhancement in Multi Machine System, Saleem, Bushra, Badar, Rabiah, Manzoor, Awais, Judge, Malik Ali, Boudjadar, Jalil, Islam, Saif Ul, IEEE Access, ISSN 2169-3536, Issue , 2022.
Digital Object Identifier: 10.1109/ACCESS.2022.3164455 [CrossRef]
[3] A brand new nonlinear robust control design of SSSC for transient stability and damping improvement of multi-machine power systems via pseudo-generalized Hamiltonian theory, Lei, Bangjun, Fei, Shumin, Control Engineering Practice, ISSN 0967-0661, Issue , 2014.
Digital Object Identifier: 10.1016/j.conengprac.2014.04.011 [CrossRef]
[4] Adaptive NeuroFuzzy damping control for power system stability enhancement, Badar, Rabiah, Khan, Laiq, 2013 IEEE 9th International Conference on Emerging Technologies (ICET), ISBN 978-1-4799-3457-7, 2013.
Digital Object Identifier: 10.1109/ICET.2013.6743485 [CrossRef]
[5] Online adaptive Legendre wavelet embedded neurofuzzy damping control algorithm, Badar, Rabiah, Khan, Laiq, INMIC, ISBN 978-1-4799-3043-2, 2013.
Digital Object Identifier: 10.1109/INMIC.2013.6731316 [CrossRef]
[6] Design, Modelling and Non Linear Control of SSSC to enhance Power Flow in IEEE 5 bus System, S., Parvathy, Thampatty, K.C. Sindhu, Nambiar, T.N. Padmanabhan, 2018 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), ISBN 978-1-5386-9316-2, 2018.
Digital Object Identifier: 10.1109/PEDES.2018.8707718 [CrossRef]
[7] Bibliography of FACTS 2012–2013: IEEE working group report, Rahman, Shah Arifur, Mahendra, A C, Varma, Rajiv K., Litzenberger, Wayne H., 2014 IEEE PES General Meeting | Conference & Exposition, ISBN 978-1-4799-6415-4, 2014.
Digital Object Identifier: 10.1109/PESGM.2014.6939526 [CrossRef]
[8] Input- Output Linearization Control of SSSC for Power Flow Enhancement in a Power System Network, S., Parvathy, Sindhu Thampatty, K. C., Padmanabhan Nambiar, T. N., 2018 15th IEEE India Council International Conference (INDICON), ISBN 978-1-5386-8235-7, 2018.
Digital Object Identifier: 10.1109/INDICON45594.2018.8987196 [CrossRef]
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Stefan cel Mare University of Suceava, Romania
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