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Obulesu Y.P.
K.L. University, Vijayawada, AP
Computer Science & IT Electrical & Electronics Engineering

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A New Hybrid Artificial Neural Network Based Control of Doubly Fed Induction Generator Venu Madhav Gopala; Obulesu Y.P.
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 3: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1147.104 KB) | DOI: 10.11591/ijece.v5i3.pp379-390

Abstract

In this paper, Hybrid Artificial Neural Network (ANN) with Proportional Integral (PI) control technique has been developed for Doubly Fed Induction Generator (DFIG) based wind energy generation system and the performance of the system is compared with NN and PI control techniques. With the increasing use of wind power generation, it is required to instigate the dynamic performance analysis of Doubly Fed Induction Generator under various operating conditions. In this paper, three control techniques have been proposed, the first one is using PI controller, the second one is ANN control, and the third one is based on combination of ANN and PI. The performance of the proposed control techniques is demonstrated through the results, determined by using MATLab/Simulink. From the results it is observed that the dynamic performance of the DFIG is improved with the Hybrid control technique.
Co-Authors Venu Madhav Gopala