Advertisement

Design Fuzzy Logic Controller by Particle Swarm Optimization for Wind Turbine

  • Nasseer K. Bachache
  • Jinyu Wen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7928)

Abstract

In this work the Particle Swarm Optimization (PSO) is utilized to framing the optimal parameters of Fuzzy Logic Controller FLC, this parameter is (centers and width) of triangle membership functions, the proposed method can design a robust controller to govern the speed of wind turbine WT, adjusting pitch angle of blade can regulate the output power of WT at a wide range of wind speed, the mean objective of this work is to make the operation of WT works as like as traditional motivator used in power system. By SIMULINK-MATLAB we implement the complete mathematical model of the system. The simulation results demonstrate that the Optimized Fuzzy Logic Control (OFLC) gets a better parameters of fuzzy sets using PSO, and realizes a good dynamic behavior compared with conventional FLC.

Keywords

Particle Swarm Optimization PSO Fuzzy Logic Control FLC Pitch Angle of Wind Turbine PAWT 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Wu, B., Lang, Y., Navid, Z., Samir, K.: Power Conversion and Control of Wind Energy System. A John Wiley & Sons, Inc., Canada (2011)Google Scholar
  2. 2.
    Jiao, B., Wang, L.: RBF Neural Network Sliding Mode Control for Variable Speed Adjustable Pitch System of Wind Turbine. In: International Conference on Electrical and Control Engineering, China (2010)Google Scholar
  3. 3.
    Yau, X., Liu, Y., Guo, C.: Adaptive Fuzzy Sliding-mode Control in Variable Speed Adjustable Pitch Wind Turbine. In: IEEE International Conference on Automation and Logistics, China (2007)Google Scholar
  4. 4.
    Guo, H., Guo, Q.: H∞ Control of Adjustable-Pitch Wind Turbine Adjustable-Pitch System. In: IEEE 5th International Conference Power Electronics and Motion Control, Slovenia (2006)Google Scholar
  5. 5.
    Dou, Z.L., Cheng, M.Z., Ling, Z.B., Cai, X.: An Adjustable Pitch Control System in a Large Wind Turbine Based on a Fuzzy-PID Controller. In: International Symposium on Power Electronics, Electrical Drives, Automation and Motion, Italy (2010)Google Scholar
  6. 6.
    Lin, W., Hong, C.: A New Elman Neural Network Based Control Algorithm for Adjustable-Pitch Variable-Speed Wind-Energy Conversion Systems. IEEE Trans. on Power Electronics 26(2) (2011)Google Scholar
  7. 7.
    Isaac, I.A., Cabrera, D., Pizarro, H., Giraldo, D., Gonzalez, J.W., Biechl, H.: Fuzzy Logic Based Parameter Estimator for Variable Speed Wind Generators PI Pitch Control. In: International Conference on Fuzzy Systems, Spain, pp. 18–23. IEEE Press (2010)Google Scholar
  8. 8.
    Lawrence, K.L., Josiah, L.M., Alex, H.: Particle Swarm Optimized T-S Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System. In: 35th Photovoltaic Specialists Conference, pp. 89–94. IEEE Press, Hawai’i (2010)Google Scholar
  9. 9.
    Olimpo, A.L., Janaka, E., Phill, C., Mike, H.: Wind Energy Generation Modelling and Control, pp. 4–6. A John Wiley and Sons, Ltd. (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nasseer K. Bachache
    • 1
  • Jinyu Wen
    • 1
  1. 1.College of Electrical and Electronic EngineeringHuazhong University of Science and Technology (HUST)WuhanChina

Personalised recommendations