Abstract
Wind turbine generators are highly desirable to operate autonomously throughout the wind speed range below hurricane conditions. A key requirement to achieve this goal is to be able to control the wind turbine speed using a full-scope feedback control scheme. Currently, wind turbine speed is controlled by modulating the angular position of the rotor blades to catch the required amount of kinetic energy of the wind to produce the desired rotational speed. Typically, conventional PI controllers modulate the blades angular position only for wind speeds in the range from 12 m/s through 25 m/s. This paper introduces a fuzzy speed controller to control autonomously the turbine rotational speed in the whole wind speed range from 0 m/s throughout 30 m/s. After presenting several key concepts about small-scale wind turbines, the design of the fuzzy speed controller based on a TSK fuzzy system is introduced. In this regard, the proposed fuzzy speed controller intelligently extends the scope of control below nominal speed and above trip conditions.
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References
Uehara, A., et al.: A coordinated control method to smooth wind power fluctuations of a PMSG-based WECS. IEEE Trans. Energy Convers. 26(2), 550–558 (2016)
Civelek, Z., Lüy, M., Cam, E., Barisci, N.: Control of pitch angle of wind turbine by fuzzy PID controller. Intell. Autom. Soft Comput. 22(3), 463–471 (2015)
Qi, Y., Meng, Q.: The application of fuzzy PID control in pitch wind turbine. Energy Procedia 16(C), 1635–1641 (2012)
Van, T.L., Nguyen, T.H., Lee, D.C.: Advanced pitch angle control based on fuzzy logic for variable-speed wind turbine systems. IEEE Trans. Energy Convers. 30(2), 1–10 (2015)
Tong, W.: Fundamentals of wind energy. In: Tong, W. (ed.) Wind Power Generation and Wind Turbine Design. WIT Transactions on State of Art in Science and Engineering, vol. 44, pp. 3–48. WIT Press, Southampton (2010)
Tumo-Int: TumoInt 1000 W 3Blades Small Wind Turbine User Manual. Tumo-Int Corporation Limited, Guangzhou (2016)
Esparza, U.B.: Diseño y optimización de un sistema de generación aislada de energía eólica orientado a las necesidades de poblaciones sin acceso a la red eléctrica. Universidad Pública de Navarra, Plampona (2011)
Ashgar, A.B., Liu, X.: Online estimation of wind turbine tip speed ratio by adaptive neuro-fuzzy algorithm. Int. J. Adv. Comput. Sci. Appl. 9(3), 28–33 (2018)
Heir, S.: Grid Integration of Wind Energy: Onshore and Offshore Conversion Systems. Wiley, Chichester (2014)
Garcia, R., Garduno, R.: Modeling a wind turbine synchronous generator. Int. J. Energy Power (IJEP) 2(3), 64–70 (2013)
IEC. Wind energy generation systems - Part 12-1: Power performance measurements of electricity producing wind turbines. Standard: IEC 61400-12-1:2017. Edition 2.0. International Electrotechnical Commission, Switzerland (2017)
Qi, J., Liu, Y.: PID control in adjustable-pitch wind turbine system based on fuzzy control. In: 2nd International Conference on Industrial Mechatronics and Automation. IEEE, Wuhan (2010)
Yager, R.R., Filev, D.P.: Essentials of Fuzzy Modeling and Control. Wiley, Hoboken (1994)
Acknowledgements
Mónica Borunda thanks Consejo Nacional de Ciencia y Tecnología (CONACYT) support for her Catedra Research Position with ID 71557, and to Instituto Nacional de Electricidad y Energías Limpias (INEEL) for its hospitality. Gorka Zubeldia thanks Fundación Novia Salcedo and (INEEL) for funding and hosting his stay.
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Garduno, R., Borunda, M., Hernandez, M.A., Zubeldia, G. (2019). Speed Control of a Wind Turbine Using Fuzzy Logic. In: Martínez-Villaseñor, L., Batyrshin, I., Marín-Hernández, A. (eds) Advances in Soft Computing. MICAI 2019. Lecture Notes in Computer Science(), vol 11835. Springer, Cham. https://doi.org/10.1007/978-3-030-33749-0_42
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DOI: https://doi.org/10.1007/978-3-030-33749-0_42
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