Research on the Control of Wind Turbine Output Power

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Abstract:

In order to keep the stable power output of wind turbine,the bp neural network controller is designed for the pitch angle control agencies of the wind energy conversion system, and hardware implementation problem of the controller is discussed based on fpga.The simulation model is built based on the System Generator/Simulink.The results show that the wind turbine output power with the neural network’s controller is stabler than the wind turbine output power with the PID’s,and the hardware implementation of neural network will have a good application prospect in the fields of wind energy conversion system.

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Periodical:

Advanced Materials Research (Volumes 204-210)

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640-643

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Online since:

February 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Ahmet Serdar Yilmaz, Zafer OZer: Pitch Angle Control in Wind Turbines above The Rated Wind Speed by Multi-Layer Perceptron and Radial Basis Function Neural Networks. Expert Systemswith Applications, 9767-9775(2009).

DOI: 10.1016/j.eswa.2009.02.014

Google Scholar

[2] J. Sargolzaei, A. Kianifar: Modeling and Simulation of Wind Turbine Savonius Rotors using Artificial Neural Networks for Estimation of The Power Ratio and Torque. Simulation Modelling Practice and Theory, 1290-1298(2009).

DOI: 10.1016/j.simpat.2009.05.003

Google Scholar

[3] S.S. Kim, S. Jung: Hardware Implementation of a Real Time Neural Network Controller with a DSP and An FPGA. Proceedings. In: International Conference on Robotics and Automation, 4639-4644, Piscataway(2004).

DOI: 10.1109/robot.2004.1302449

Google Scholar

[4] W. Qinruo, Y. Bo and X. Yun: The Hardware Structure Design of Perceptron with FPGA Implementation. In: International Conference on Systems, Man & Cybernetics, 762-767, Piscataway(2003).

DOI: 10.1109/icsmc.2003.1243906

Google Scholar

[5] Zhuo Ruan , Jianguo Han, Yuzhang Han: Bp Neural Network Implementation On Real-time Reconfigurable FPGA System For A Soft-sensing Process. In: International Conference on Neural Networks and Brain, 959-963, Beijing (2003).

DOI: 10.1109/icnnb.2005.1614779

Google Scholar

[6] Inlian Munteanu, Antoneta Iuliana Brarcu and Nicolaos-Antonic Cutululis l: Optimal control of Wind Energy Systems (Springer Publications, London2008).

Google Scholar