Control of DFIG for improvement of voltage regulation in a power system using recurrent neural networks

This article focuses on the voltage control of Doubly Fed Induction Generator (DFIG) wind turbines using Recurrent Neural Network (RNN). The paper also compares the performance of Static Synchronous Compensator (STATCOM) and DFIG systems, subject to the line to ground fault. The RNN is used in two main parts which are RNN Identifier (RNNI) and RNN Controller (RNNC). Performance of the DFIG is simulated and analyzed with and without the RNN controller. In this study, voltage regulation on Recurrent Neural Network is designed to control for a standard multi-machine power system. The results demonstrated significant improvement in the voltage regulation using the RNN controller for DFIG in the power system. [Ali Asghar Shojaei, Mohd Fauzi Othman, Rasoul Rahmani, Masoud Samadi. Control of DFIG for improvement of voltage regulation in a power system using recurrent neural networks. Life Sci J 2013;10(12s):761-769]. (ISSN:1097-8135). http://www.lifesciencesite.com. 122 Keyword: Recurrent neural network, control, DFIG, voltage regulation, STATCOM

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