Intelligent Maximum Power Tracking Control For a Wind Energy System Based on Magnetic Gear Generator

  • K. S. Belkhir Department of Electrical Engineering, University Ferhat Abbas Setif 1, Algeria
Keywords: artificial neural network, magnetic gear generator, wind power


This paper studies maximum wind power extraction from magnetic gear generator using an artificial neural network for the wind energy system. High speed can be reached with this representation either with magnetic gear generator, under low wind conditions often found inland, or without mechanical gear. In order to track maximum power, the artificial neural network controller adjusts the outer rotor speed, and thus, inner rotor speed. The proposed system is supported by simulation results.


Download data is not yet available.


V. Markovitz, “Sizing Up Wind Energy: Bigger Means Greener Study Says”, National Geographic News, available at: https://news., 2012

J. Helsen, F. Vanhollebeke, D. Vandepitte, W. Desmet, “Some trends and challenges in wind turbine upscaling”, in: Proceedings of ISMA International Conference on Noise and Vibration, Leuven, pp. 4345-4359, Katholieke Universiteit Leuven, 2012

P. Dvorak, “Britannia breaks the 9 MW barrier”, Windpower Engineering and Development, available at: https://www., 2010

L. R. Martin, “Wind energy-the facts: A guide to the technology, economics, and future of wind power”, Journal of Cleaner Production, Vol. 18, No. 10, pp. 1122-1123, 2010

J. Beurskens, “Achieving the 20 MW wind turbine”, available at: https://, 2011

K. Atallah, D. Howe, “A novel high-performance magnetic gear”, IEEE Transactions On Magnetics, Vol. 37, No. 4, pp. 2844-2846, 2001

K. Atallah, S. D. Calverley, D. Howe, “Design, analysis and realisation of a high-performance magnetic gear”, IEE Proceedings-Electric Power Applications, Vol. 151, No. 2, pp.135-143, 2004

K. Atallah, J. Rens, S. Mezani, D. Howe, “A novel “Pseudo” direct-drive Brushless permanent magnet machine”, IEEE Transactions on Magnetics, Vol. 44, No. 11, pp.4349-4352, 2008

H. Camblong, I. M. de Alegria, M. Rodriguez, G. Abad, “Experimental evaluation of wind turbines maximum power point tracking controllers”, Energy Conversion and Management, Vol. 47, No. 18-19, pp. 2846-2858, 2006

C. Y. Lee, Y. X. Shen, J. C. Cheng, Y. Y. Li, C. W. Chang, “Neural networks and particle swarm optimization based MPPT for small wind power generator”, World Academy of Science, Engineering and Technology, Vol. 3, No. 12, pp. 2222-2228, 2009

C. Y. Lee, P. H. Chen, Y. X. Shen, “Maximum power point tracking (MPPT) system of small wind power generator using RBFNN approach”, Expert Systems with Applications, Vol. 38, No. 10, pp. 12058-12065, 2011

I. Munteanu, A. I. Bratcu, E. Ceanga, “Wind turbulence used as searching signal for MPPT in variable-speed wind energy conversion systems”, Renewable Energy, Vol. 34, No. 1, pp. 322-327, 2009

W. M. Lin, C. M. Hong, “Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system”, Energy, Vol. 35, No. 6, pp. 2440-2447, 2010

R. Kot, M. Rolak, M. Malinowski, “Comparison of maximum peak power tracking algorithms for a small wind turbine”, Mathematics and Computers in Simulation, Vol. 91, pp. 29-40, 2013

Y. Y. Hong, S. D. Lu, C. S. Chiou, “MPPT for PM wind generator using gradient approximation”, Energy Conversion and Management, Vol. 50, No. 1, pp. 82-89, 2009

S. M. Muyeen, A. A. Durra, J. Tamura, “Variable speed wind turbine generator system with current controlled voltage source inverter”, Energy Conversion and Management, Vol. 52, pp. 2688-2694, 2011

Z. Qi, E. Lin, “Integrated power control for small wind power system”, Journal of Power Sources, Vol. 217, pp. 322-328, 2012


Abstract Views: 209
PDF Downloads: 158

Metrics Information
Bookmark and Share