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Optimum Damping of Inter-Area Oscillations Using a Wavelet Neural PI Network Controlled Static Synchronous Series Compensator

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This paper recommends a wavelet neural PI controller (WNPIC) to increase the damping of static synchronous series compensator (SSSC) in order to mitigate the inter-area oscillations. The closedloop control system contains two wavelet neural networks (WNNs). The first is a feed-forward wavelet neural network that is used as a predictive model of the controlled plant. The second one is a wavelet neural PI-like controller which combines abilities of a wavelet neural network and PI controller. Both networks are trained by using the gradient steepest descent method. The whole design process of controller, an accurate model of the system is not required. A two-area fourmachine power system is used to evaluate the performance of the proposed controller in damping the oscillations. The results show that the intra-area oscillations are satisfactorily suppressed by the proposed controller.
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Document Type: Research Article

Publication date: March 1, 2016

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  • JOURNAL OF COMPUTATIONAL INTELLIGENCE AND ELECTRONIC SYSTEMS publishes emerging research in the areas of the computational intelligence and electronic systems. JCIES publishes in all areas of computational intelligence design and applications: applications oriented developments, successful industrial implementations, design tools, technology reviews, computational intelligence education, and applied research, specific emphasis on power electronics, embedded systems, semiconductor devices, analogue circuits, digital electronics, microwave and millimeter-wave techniques, wireless and optical communications, sensors, instrumentation and medical electronics much more.
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