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Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm: Power System Dynamic Stability Enhancement Using Online System Identification

Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm: Power System Dynamic Stability Enhancement Using Online System Identification

Laiq Khan, Rabiah Badar
Copyright: © 2014 |Pages: 42
ISBN13: 9781466644502|ISBN10: 1466644508|EISBN13: 9781466644519
DOI: 10.4018/978-1-4666-4450-2.ch026
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MLA

Khan, Laiq, and Rabiah Badar. "Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm: Power System Dynamic Stability Enhancement Using Online System Identification." Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications, edited by Pandian M. Vasant, IGI Global, 2014, pp. 787-828. https://doi.org/10.4018/978-1-4666-4450-2.ch026

APA

Khan, L. & Badar, R. (2014). Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm: Power System Dynamic Stability Enhancement Using Online System Identification. In P. Vasant (Ed.), Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications (pp. 787-828). IGI Global. https://doi.org/10.4018/978-1-4666-4450-2.ch026

Chicago

Khan, Laiq, and Rabiah Badar. "Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm: Power System Dynamic Stability Enhancement Using Online System Identification." In Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications, edited by Pandian M. Vasant, 787-828. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4450-2.ch026

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Abstract

This work explores the potential of Bspline based Adaptive NeuroFuzzy Wavelet control to damp low frequency power system oscillations using Static Synchronous Series Compensator (SSSC). A comparison of direct and indirect adaptive control based on Hybrid Adaptive Bspline Wavelet Control (ABSWC) is presented by introducing the online identification block. ABSWC with Identification (ABSWCI) provides the sensitivity information of the plant to control system. The parameters of the control and identification block are updated online using gradient descent based back propagation algorithm. The robustness of the proposed control algorithm has been evaluated for local and inter-area modes of oscillations using different faults. The nonlinear time domain simulation results have been analyzed on the basis of different performance indices and time-frequency representation showing that ABSWC effectively damps low frequency oscillations and incorporation of online identification optimizes the control system performance in terms of control effort which reduces the switching losses of the converter.

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