Abstract
Wind turbines exhibit highly non-linear behavior, making it difficult to control their power output using traditional PID control methods. Fuzzy logic control has proven to be an effective solution for addressing this challenge. This work focuses on the application of fuzzy logic control for optimizing the power generated by wind turbines, specifically in high wind speed conditions where limiting the power output is necessary for the protection of the machine. The results of simulation studies comparing fuzzy logic control and conventional PID control are presented and analyzed, demonstrating the superiority of fuzzy logic control in ensuring the desired control performance while maintaining the safety of the wind turbine.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abbas FA, Abdulsada MA, Abusief FR (2011) Speed control of wind turbine by using PID controller. Eng Tech J 29(1)
Lakhal Y, Baghli FZ, El Bakkali L (2013) Modelisation et contrôle d’un aerogenerateur par un controleur pi. In: Proceedings of the 11th Congress of Mechanics, pp 23–26 April 2013, Agadir, Morocco
Mohamed A, Abederrazek L, Lamine M (2019) PID controller design for a wind turbine with the backlash phenomenon. In: Proceedings of the 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA), Tebessa, Algeria, pp 1–6. https://doi.org/10.1109/ICSRESA49121.2019.9182649
Zhang J, Xu S (2015) Application of fuzzy logic control for grid-connected wind energy conversion system. Fuzzy Logic - Tool for Getting Accurate Solutions. In Tech, Sep. 02, 2015. https://doi.org/10.5772/59923
Baburajan S (2017) Pitch control of wind turbine through PID, fuzzy and adaptive fuzzy-PID controllers. Thesis. Rochester Institute of Technology
Bora T, Chatterjee P, Ghosh S (2020) Fuzzy logic based control of variable wind energy system. 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), Jaipur, India, pp 1–5. https://doi.org/10.1109/ICRAIE51050.2020.9358376
Lakhal Y, Baghli FZ, El Bakkali L (2015) Fuzzy logic control strategy for tracking the maximum power point of a horizontal axis wind turbine. Procedia Technol 18:885–892. https://doi.org/10.1016/j.protcy.2015.02.085
Yaakoubi AE, Amhaimar L, Attari K, Harrak MH, Halaoui ME, Asselman A (2019) Non-linear and intelligent maximum power point tracking strategies for small size wind turbines: performance analysis and comparison. Energy Rep 5:545–554. https://doi.org/10.1016/j.egyr.2019.03.001
Civelek Z (2019) Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Eng Sci Technol Int J 21:11–20. https://doi.org/10.1016/j.jestch.2019.04.010
Tahiri M, Djebli A, Mimet A (2017) Drivetrain Flexibility Effect on Control Performance of a Horizontal Axis Wind Turbine. Int J Appl Eng Res 12(16):5511–5519
Lakhal Y, Baghli FZ, El Bakkali L (2017) The efficiency of bond graph approach for a flexible wind turbine modeling. J Eng Sci Technol 12(11):1419–1429
Lakhal Y, Zahra BF, El Bakkali L (2014) Dynamic modeling and simulation of a flexible wind turbine for a multi-objectives control
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Yassine, L., Zahra, B.F., Ait El Kadi, Y., Mohammed, B. (2024). The Efficiency of Fuzzy Logic Control on the Power Stabilization of Wind Turbine. In: Bendaoud, M., El Fathi, A., Bakhsh, F.I., Pierluigi, S. (eds) Advances in Electrical Systems and Innovative Renewable Energy Techniques. ICESA 2023. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-49772-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-031-49772-8_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-49771-1
Online ISBN: 978-3-031-49772-8
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)