Improving Performance of Variable Speed Wind Turbines using Takagi-Sugeno Fuzzy Controller and LQR Method
Keywords:
Fuzzy controller, Pitch control, Variable speed wind turbine
Abstract
The focus of this research is on variable speed wind turbines operation with pitch control. In this paper, an advanced control strategy, based on a linear quadratic regulator and fuzzy controllers, is proposed in order to improve the performance of the variable-speed wind turbine. The proposed controller is designed to reduce the rotor’s speed variation, while optimizing wind turbine power. Wind turbine states are estimated by using fuzzy observer. Moreover, the Takagi-Sugeno fuzzy strategy is used to regulate the rotor speed by controlling the rotation of blades. The proposed method is modeled in MATLAB software by SimWindFarm simulator. Simulation results showed that the fuzzy TS method is an appropriate method for improving the efficiency of wind turbines. Moreover, the proposed method showed better performance compared to the PI controller.
References
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[3] Senjyu, T., Sakamoto, R., Urasaki, N., Higa, H., Uezato, K., & Funabashi, T., ”Output power control of wind turbine generator by pitch angle control using minimum variance control” Electrical Engineering in Japan, 2006, 154, 10–18.
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[10] Bianchi, H. Battista, and R. J. Mantz, “Wind Turbine Control Systems: Principles, Modelling and Gain Scheduling Design”, London: Springer-Verlag ,2007.
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[12] Jelavic, M., Petrovic, V., & Peric, N. “Estimation based individual pitch control of wind turbine.” Automatika, 2010, 51, 181–192.
[13] Soliman, O. P. Malik, and D. Westwick, “Multiple model MIMO predictive control for variable speed variable pitch wind energy conversion systems,” IET Renewable Power Generation, 2010.
[14] A. Bektachea, B. Boukhezzar, "Nonlinear predictive control of a DFIG-based wind turbine for power capture optimization", Electrical Power and Energy Systems, 2018.
[15] Zafer civelek, Murat Lüy, Ertuğrul Çam, Hayati Mamur, "A new fuzzy logic proportional controller approach applied to individual pitch angle for wind turbine load mitigation", Renewable Energy, 2017.
[16] Ahmed Lasheen, Abdel Latif Elshafei, "Wind-turbine collective-pitch control via a fuzzy predictive algorithm", Renewable Energy, 2016.
[17] John Twidell, Tony Weir, "Renewable Energy Resources", Taylor & Francis, 2015.
[18] E. Hau; “Wind Turbines Fundamentals, Technologies, Application, Economics”, 2nd edition, Springer, 2006.
[19] J. M. Jonkman and M. L. Buhl; “FAST user’s guide;" National Renewable Energy Lab., Golden, CO, NREL/EL-500-38230, Aug. 2005.
[2] Eminoglu U, Ayasun S., “Modeling and design optimization of variable-speed wind turbine systems”, Energies, 2014, 7(1):402–19.
[3] Senjyu, T., Sakamoto, R., Urasaki, N., Higa, H., Uezato, K., & Funabashi, T., ”Output power control of wind turbine generator by pitch angle control using minimum variance control” Electrical Engineering in Japan, 2006, 154, 10–18.
[4] Tan Luong Van, Thanh Hai Nguyen, and Dong-Choon Lee, “Advanced Pitch Angle Control Based on Fuzzy Logic for Variable-Speed Wind Turbine Systems”, IEEE TRANSACTIONS ON ENERGY CONVERSION, 2014.
[5] Y. Nam, P. T. Kien, and Y.-H. La, “Alleviating the tower mechanical load of multi-MW wind turbines with LQR control,” J. Power Electron., vol. 13, no. 6, pp. 1024–1031, Nov. 2013.
[6] S. Roy, “Power output by active pitch-regulated wind turbine in presence of short duration wind variations,” IEEE Trans. Energy Convers., vol. 28, no. 4, pp. 1018–1025, Dec. 2013.
[7] T. Senjyu, R. Sakamoto, N. Urasaki, T. Funabashi, H. Fujita, and H. Sekine, “Output power leveling of wind turbine generator for all operating regions by pitch angle control,” IEEE Trans. Energy Convers., vol. 21, no. 2, pp. 467–475, Jun. 2006.
[8] R. M. Kamel, A. Chaouachi, and K. Nagasaka, “Wind power smoothening using fuzzy logic pitch controller and energy capacitor system for improvement micro-grid performance in islanding mode,” Energy, vol. 35, no. 5, pp. 2119–2129, Mar. 2010.
[9] Seyed Mahyar Mehdizadeh Moghadam1, Alireza Khosravi , Seyed Mehdi Rakhtala Rostami, “Design of a Robust Sliding Mode Controller based on Nonlinear Modeling of Variable Speed Wind Turbine,” Majlesi Journal of Electrical Engineering Vol. 11, No. 4, December 2017
[10] Bianchi, H. Battista, and R. J. Mantz, “Wind Turbine Control Systems: Principles, Modelling and Gain Scheduling Design”, London: Springer-Verlag ,2007.
[11] Zafer Civelek, Murat Lüy, Ertuğrul Çam & Necaattin Barışçı, "Control of Pitch Angle of Wind Turbine by Fuzzy Pid Controller", Intelligent Automation & Soft Computing, 2015.
[12] Jelavic, M., Petrovic, V., & Peric, N. “Estimation based individual pitch control of wind turbine.” Automatika, 2010, 51, 181–192.
[13] Soliman, O. P. Malik, and D. Westwick, “Multiple model MIMO predictive control for variable speed variable pitch wind energy conversion systems,” IET Renewable Power Generation, 2010.
[14] A. Bektachea, B. Boukhezzar, "Nonlinear predictive control of a DFIG-based wind turbine for power capture optimization", Electrical Power and Energy Systems, 2018.
[15] Zafer civelek, Murat Lüy, Ertuğrul Çam, Hayati Mamur, "A new fuzzy logic proportional controller approach applied to individual pitch angle for wind turbine load mitigation", Renewable Energy, 2017.
[16] Ahmed Lasheen, Abdel Latif Elshafei, "Wind-turbine collective-pitch control via a fuzzy predictive algorithm", Renewable Energy, 2016.
[17] John Twidell, Tony Weir, "Renewable Energy Resources", Taylor & Francis, 2015.
[18] E. Hau; “Wind Turbines Fundamentals, Technologies, Application, Economics”, 2nd edition, Springer, 2006.
[19] J. M. Jonkman and M. L. Buhl; “FAST user’s guide;" National Renewable Energy Lab., Golden, CO, NREL/EL-500-38230, Aug. 2005.
Published
2020-03-01
How to Cite
Khayat, M., & Nekoui, M. A. (2020). Improving Performance of Variable Speed Wind Turbines using Takagi-Sugeno Fuzzy Controller and LQR Method. Majlesi Journal of Mechatronic Systems, 9(1), 1-10. Retrieved from https://ms.majlesi.info/index.php/ms/article/view/433
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