Document Type : Research Article

Authors

1 Department of Excellence on Applied Electromagnetic Systems, School of Electrical and Computer, University of Tehran, Tehran, Iran

2 Department of Electrical Engineering, Najafabad branch, Islamic Azad Universi ty, Najafabad, Isfahan, Iran

Abstract

Pitch control is one of t he  major aspects of wind turbine control, particularly over high wi nd s p e e d  a n d  oscillations. General El e c t r i c  (GE) model of  wi n d  t ur bi ne  i s practically compatible with the structure of the wind turbines. I t  h a s  b e e n  p r o v e d t h a t  simulation results using this model are closer to the actual case, compared to other available models. Therefore, in this paper the GE model is used to evaluate the eff ectiveness of  three different controllers including Fuzzy controller, self-organized Fuzzy controller (SOFC) and PI controller i n pitch control of  the wi nd turbine. Afterward, the results of the controller applications as well as the no controller case in t h e  pitch control are compared. The results show a better performance of SOFC in damping the oscillations and overshoot of the wind turbine shaft speed. Finally,
electrical power limit and converter cost, the economic analysis of pitch controller application are carriedout. It is shown that the application of  the SOFC results are around $142,646 saving.

Keywords

1. Boukhezzar, H., and Siguerdid J., “ Nonlinear control of a variable speed wind turbine using a two- mass
model”, IEEE Transactions on Energy Conversion, Vol. 26, No. 1, ( 2 0 1 1 ) ,  149-162.
2. Ruba, M., Szabo, L., and Jurca, F., “Fault tolerant switched reluctance machine for wind turbine blade
pitch control”, in International Conference on Clean Electrical Power, Capri, 721-726, (2009).
3. Zhang, J., Cheng, M., and Chen, Z., “Pitch angle control for variable speed wind turbines”, in 3 International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, Nanjing, China, 2691-2696, (2008).
4. S. Muller, M. Deicke, and R.W De Doncker,. “Adjustable speed generators for wind turbines based on doubly-fed induction machines and 4-quadrant IGBT converters linked to the rotor”, in IEEE Industry Applications Conference, USA, 2249-2254, (2000).
5. Muljadi, E.,  and Butterfield, C. P., “Pitch-controlled variable-speed wind turbine generation”, IEEE Transactions on Industry Applications , Vol. 37, No. 1, (2001), 240-246.
6. Anderson, P. M., and Bose, A., “Stability simulation of wind turbine systems”, IEEE  Transactions on  Power, Apparatus and Systems, Vol. PAS-102, No. 12, (1983), 3791-3795.
7. Owasynczuk, and D.T., Sullivan, J. P., “Dynamic behavior of a class of wind turbine generators during random wind fluctuations”, IEEE Transactions on Power and  Apparatus and Systems, Vol. PAS-100, No. 6, (1981), 2837-2845.
8. Slootweg, J. G., de Haan, S. W. H., Polinder H., and Kling, W. L. “General model for representing variable
speed wind turbines in power system dynamics simulations,” IEEE  Transactions on Power Systems, Vol. 18, No. 1, (2003), 144-151.
9. Conroy, J. F., and Watson, R., “Low-voltage ridethrough of a full converter wind turbine with permanent magnet generator,” IET Renewable Power Generation, Vol. 1, No. 3, (2007), 182-189.
10. Hansen, D., "Evaluation of power control with different electrical and control concept of wind farm", in Part 2–Large systems, Scientific Report, Technical Universit y of Denmark, Denmark, 53-55,  (2010).
11. Miller, N. W., Price, W. W., and Gasca, J. J. S.,  “Dynamic modeling of GE 3.6 wind turbine generators”, in GE-Power Systems Energy Consulting, Ver. 3, USA, (2003).
12. Mamdani, E. H. “Applications of fuzzy algorithms for control of simple dynamic plant”, IEEE Proceedings,
Vol. 121, No. 12, (1974), 1585-1588. 
13. Tipsuwanpom, V., et. el., “Separately excited DC motor drive with fuzzy self-organizing”, in IEEE 
International Conference on Control, Automation, and Systems (ICCAS’07), 1316-1321, Seoul, (2007).
14. Kovacic, Z., and Bogdan, S., “Fuzzy controller design’’, CRC Press, (2005).
15. Kusagur, S. F. Kodad, B. and Ram, V. S., “AI based design of a fuzzy logic scheme for speed control of
induction motors using SVPWM technique’’, Int. Journal of Computer Science and Network Security,
Vol. 9, No. 1, (2009), 72-80.
16. Lee, C. H., and Wang, S. D., “Self-organizing adaptive fuzzy controller”, International Journal of Fuzzy Sets and Systems, Vol. 80, No. 3, (1996),  295-313.
17. Shieh, L., and Peacock, J. E., “Hierarchical rule-based and self-organizing fuzzy logic control for depth of
anaesthesia’’, IEEE Transactions on System, Man, and Cybernetics - Part C: Applications   and Reviews,
Vol. 29, No. 1, (1999), 98-109.
18. Nie, J., and Lee, T. H., “Self-organizing rule-base  control of multivariable nonlinear servomechanisms’’,
International Journal of Fuzzy Sets and Systems, Vol. 81, No. 3, (1997), 285-304.
19. Kumar, V., and Rana, K. P. S., “Real time comparative study of the performance of FPGA based PID and fuzzy controllers for a rectilinear plant”, in IEEE India International Conference on Power Electronics (IICPE), New Delhi, 1-7, (2011). 
20. Acromag Incorporated team, “FPGAs go green in wind turbine control”, in Acromag Incorporated Report,
USA, 1-3, (2009).
21. S. Bico, “Simulator for wind turbine control system software testing”, in EE publishers/Energize, Application, 66-68, (2010). 
22. Beckhof Company, “PC-based control for wind turbines”, http://download.beckhoff.com, 1-28, (2012).
23. Wang, L., and Liu, K. H., “Implementation of a webbased real-time monitoring and control system for a
hybrid wind-PV-battery renewable energy system”, in IEEE Symposium on Antennas and Propagation (ISAP), Toki Messe, 1-6, (2007).
24. GE Energy Tech. Group, “GE’s 1.5-77 (class I) wind turbine”, http://www.ge-energy.com/wind, GE Comp.
Trans., 1-8, (2012).
25. Kung, Y. S., Tsai, M. H., a n d  Chen, C. S.,  “FPGAbased servo control IC for PMLSM drives with adaptive fuzzy control”, i n IEEE Conference on Industrial Electronics and Applications, Singapore, 16, (2006).
26. 27. M. Bolinger, a n d  R. Wiser, "Understanding trends in wind turbine prices over the past decade",
Lawrence Berkeley National Laboratory, USA,1-46, Oct. 2011.