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Fault Diagnosis in Wind Power System Based on Intelligent Techniques

Authors: Kanaan A. Jalal --- Lubna A. Abd alameer
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 11 Part (A) Engineering Pages: 1201-1207
Publisher: University of Technology الجامعة التكنولوجية


Wind energy is one of the most important sources as well as beingenvironmentally friendly and sustainable. In this paper, different types of faults ofDoubly-Fed Induction Generator (DFIG) have been studied based on ArtificialNeural Network (ANN), Particle Swarm Optimization (PSO) and FieldProgrammable Gate Array. To simulate the wind generators modelMATLAB/Simulink program has been used. Artificial Neural Network (ANN) istrained for detection the faults and (PSO) technique is used to get the best weights.After the training process, the network was transformed into a Simulink programand then converted into the Very High Speed Description Language (VHDL) fordownloading on the (FPGA) card, which in turn is used to detect and diagnosis thepresence of faults where it can be re-programmed with high response andaccuracy.

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