Open Access Open Access  Restricted Access Subscription or Fee Access

Cascading Control Based on Intelligent Algorithms for a Wind Turbine Equipped with a Doubly-Fed Induction Generator

(*) Corresponding author

Authors' affiliations



This paper presents an intelligent cascaded nonlinear control of a Doubly-Fed Induction Generator, based on variable speed wind turbine. The whole system is presented in d-q synchronous reference frame. The main objectives of the controller defined in the partial load region, are optimizing wind energy captured, improving the quality of the power generated and minimizing mechanical stress in the drive train. The energy conversion is based on the proposed dual loop control structure using two introduced algorithms: the extreme learning machine, which is used to improve the system knowledge and the adaptive particle swarm optimization used to search the optimal gains of the conventional proportional integral controller, widely used in control of electrical part. The global controller is first tested for a velocity profile of the high wind turbulence. Secondly, it is compared to the conventional PI for showing its performances in terms of power maximization, sensitivity to perturbations and robustness against changes in parameters of the machine. The proposed control strategy is approved by simulation using software Matlab/Simulink.
Copyright © 2017 Praise Worthy Prize - All rights reserved.


Adaptive Particle Swarm Optimization; Cascaded Control; Doubly Field Induction Generator; Energy Conversion; Extreme Learning Machine; Variable Speed Wind Turbine

Full Text:



R. Zeb, L. Slar, U. Awan, K. Zaman, and M. Shahbaz, Causal Links Between Renewable Energy, Environmental Degradation and Economic Growth in Selected SAARC Countries: Progress Towards Green Economy, Renewable Energy, Vol. 71:123-132, November 2014.

M. Tahir, and N. S. Amin, Advances in Visible Light Responsive Titanium Oxide-Based Photocatalysts for CO2 Conversion to Hydrocarbon Fuels, Energy Convers. Manag, Vol. 76:194-214, December 2013.

Zohoori, A., Vahedi, A., Meo, S., Sorrentino, V., An Improved AHP Method for Multi-Objective Design of FSPM Machine for Wind Farm Applications, (2016) Journal of Intelligent and Fuzzy Systems, 30 (1), pp. 159-169.

Vahedi, A., Meo, S., Zohoori, A., An AHP-based approach for design optimization of flux-switching permanent magnet generator for wind turbine applications, (2016) International Transactions on Electrical Energy Systems, 26 (6), pp. 1318-1338.

Zohoori, A., Vahedi, A., Noroozi, M.A., Meo, S., A new outer-rotor flux switching permanent magnet generator for wind farm applications, (2017) Wind Energy, 20 (1), pp. 3-17.

Y. He, and X. Chen, Wind Turbine Generator Systems. The Supply Chain in China: Status and Problems, Renewable Energy, Vol. 34:2892-2897, April 2009.

M. Koumir, A. E. Bakri, and I. Boumhidi, Optimal control for a variable speed wind turbine based on extreme learning machine and adaptive Particle Swarm Optimization, 5th International Conference on Systems and Control, pp. 151-156, Marrakech, Morocco, 25-27 May 2016.

M. Koumir, A. E. Bakri, and I. Boumhidi, Integral Sliding Mode Control Based on Extreme Learning Machine for a Wind Turbine, Control and Intelligent Systems, Vol. 45(Issue 3), 2017.

Ahmed, I., Zobaa, A., Comparative Power Quality Study of Variable Speed Wind Turbines, (2016) International Journal on Energy Conversion (IRECON), 4 (4), pp. 97-104.

Aouani, N., Bacha, F., Dhifaoui, R., Control Strategy of a Variable Speed Wind Energy Conversion System Based on a Doubly Fed Induction Generator, (2014) International Journal on Energy Conversion (IRECON), 2 (2), pp. 66-73.

K. Johnson, L. Pao, M. Balas, and L. Fingersh, Control of Variable-Speed Wind Turbines, IEEE Control Systems Magazine, Vol. 26:70-81, June 2006.

Reddak, M., Berdai, A., Gourma, A., Boukherouaa, J., Belfiqih, A., Enhanced Sliding Mode MPPT and Power Control for Wind Turbine Systems Driven DFIG (Doubly-Fed Induction Generator), (2016) International Review of Automatic Control (IREACO), 9 (4), pp. 207-215.

Jafari, H., Radan, A., Comparison between Self Tuning PI Voltage Control of DFIG and a Combinational Control for Improved Wind Turbines, (2014) International Journal on Energy Conversion (IRECON), 2 (5), pp. 167-171.

M. Tazil, V. Kumar, R.C. Bansal, S. Kong, Z.Y. Dong, W. Freitas, and H.D. Mathur, Three-Phase Doubly Fed Induction Generators: an Overview, IET Electric Power Applications, Vol. 4(Issue 2):75-89, February 2010.

T. Burton, D. Sharpe, N. Jenkins, and E. Bossanyi, Wind energy handbook (Second Edition. John Wiley & Sons, 2011).

H. J. Asl, and J. Yoon, Power Capture Optimization of Variable-Speed Wind Turbines Using an Output Feedback Controller, Renewable Energy, Vol. 86:517-525, February 2016.

G. Huang, Q. Zhu, and C. Siew, Extreme Learning Machine: Theory and Applications, Neurocomputing, Vol. 70:489-501, May 2006.

E. Cambria, and G.B. Huang, Extreme Learning Machines, IEEE Intelligent Systems, Vol. 28(Issue6):30-59, November-December 2013.

R. J. Cardenas, R.S. Pena, J. Asher, G.M. Asher, and J.C. Clare, Sensorless control of a doubly-fed induction generator for standalone operation, IEEE 35th Annual Power Electronics Specialists Conference, Vol. 5, pp. 3378–3383, July 2004.

Jafari, H., Jafari, H., Comparison of Self Tuning P and PI Voltage Control of DFIG in Wind Power Generation Considering Two Mass Shaft Model, (2014) International Review of Automatic Control (IREACO), 7 (2), pp. 147-155.

R.C. Eberhart, and J. Kennedy, A New Optimizer Using Particle Swarm Theory, Proceedings of the Sixth International Symposium on Micro-Machine and Human Science, pp. 39–43, Nagoya, 4-6 October 1995.

Taeib, A., Chaari, A., PID Controller Based Adaptive PSO, (2014) International Review of Automatic Control (IREACO), 7 (1), pp. 31-37.

Meo, S., Zohoori, A., Vahedi, A., Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach, (2016) Energy Conversion and Management, 110, pp. 230-239.

Del Pizzo, A., Meo, S., Brando, G., Dannier, A., Ciancetta, F., An energy management strategy for fuel-cell hybrid electric vehicles via particle swarm optimization approach, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 543-553.

B. Boukhezzar, and H. Siguerdidjane, Nonlinear Control of A Variable-Speed Wind Turbine Using A Two-Mass Model, IEEE Transactions on Energy Conversion, Vol. 26(Issue 1):149-162, March 2011.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2024 Praise Worthy Prize