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A new fuzzy logic proportional controller approach applied to individual pitch angle for wind turbine load mitigation

Author

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  • Civelek, Zafer
  • Lüy, Murat
  • Çam, Ertuğrul
  • Mamur, Hayati

Abstract

In the world, efforts to increase the resource diversity in electric generation have accelerated lately. So, the great improvements have been achieved in wind turbines (WTs). The dimensions of WTs have grown for more electric generation and their energy productions have increased. Depending on these developments, it has become more important to reduce the WT load mitigation. Thus, a tendency to pass an individual pitch angle system control rather than a collective pitch angle system control employed to stable the output power of WTs over nominal wind speeds has whetted in recent studies. However, in literature, a controller proposal relating to how to incorporate the blade moments used for providing the individual pitch angle system into the output power control system has not yet been offered. Therefore, in this study, a new fuzzy logic proportional control (FL-P-C) approach has been recommended to mitigate the moment load on blades and tower to a minimum possible value while keeping the output power of WTs at a constant value. The offered FL-P-C has also been verified by MATLAB/Simulink. Through the first application of the FL-P-C on a WT, a significant improvement of 33–83% has been managed for the blade and tower moment loads. Furthermore, the grid fluctuations have been reduced because of the stabilisation of the output power of the WT. Ultimately, by the offered FL-P-C, not only the WT load mitigations and maintenance costs of WTs could be reduced, but also electric costs could be decreased owing to increasing lifetimes of WTs.

Suggested Citation

  • Civelek, Zafer & Lüy, Murat & Çam, Ertuğrul & Mamur, Hayati, 2017. "A new fuzzy logic proportional controller approach applied to individual pitch angle for wind turbine load mitigation," Renewable Energy, Elsevier, vol. 111(C), pages 708-717.
    • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:708-717
    DOI: 10.1016/j.renene.2017.04.064
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    Citations

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    Cited by:

    1. Sales-Setién, Ester & Peñarrocha-Alós, Ignacio, 2020. "Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm level," Renewable Energy, Elsevier, vol. 146(C), pages 1746-1765.
    2. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    3. Noyes, Carlos & Loth, Eric & Martin, Dana & Johnson, Kathryn & Ananda, Gavin & Selig, Michael, 2020. "Extreme-scale load-aligning rotor: To hinge or not to hinge?," Applied Energy, Elsevier, vol. 257(C).
    4. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.
    5. Li, Juan & Wang, Yinan & Zhao, Xiaowei & Qi, Pengyuan, 2021. "Model free adaptive control of large and flexible wind turbine rotors with controllable flaps," Renewable Energy, Elsevier, vol. 180(C), pages 68-82.
    6. Hosseini, Ehsan & Aghadavoodi, Ehsan & Fernández Ramírez, Luis M., 2020. "Improving response of wind turbines by pitch angle controller based on gain-scheduled recurrent ANFIS type 2 with passive reinforcement learning," Renewable Energy, Elsevier, vol. 157(C), pages 897-910.
    7. Bofeng Xu & Yue Yuan & Haoming Liu & Peng Jiang & Ziqi Gao & Xiang Shen & Xin Cai, 2020. "A Pitch Angle Controller Based on Novel Fuzzy-PI Control for Wind Turbine Load Reduction," Energies, MDPI, vol. 13(22), pages 1-16, November.
    8. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
    9. Ahmet Selim Pehlivan & Beste Bahceci & Kemalettin Erbatur, 2022. "Genetically Optimized Pitch Angle Controller of a Wind Turbine with Fuzzy Logic Design Approach," Energies, MDPI, vol. 15(18), pages 1-15, September.
    10. Yuri Merizalde & Luis Hernández-Callejo & Oscar Duque-Perez & Víctor Alonso-Gómez, 2019. "Maintenance Models Applied to Wind Turbines. A Comprehensive Overview," Energies, MDPI, vol. 12(2), pages 1-41, January.
    11. Yolanda Vidal & Leonardo Acho & Ignasi Cifre & Àlex Garcia & Francesc Pozo & José Rodellar, 2017. "Wind Turbine Synchronous Reset Pitch Control," Energies, MDPI, vol. 10(6), pages 1-16, June.
    12. Xilin Zhao & Zhenyu Lin & Bo Fu & Li He & Na Fang, 2018. "Research on Automatic Generation Control with Wind Power Participation Based on Predictive Optimal 2-Degree-of-Freedom PID Strategy for Multi-area Interconnected Power System," Energies, MDPI, vol. 11(12), pages 1-17, November.
    13. Golnary, Farshad & Moradi, Hamed, 2018. "Design and comparison of quasi continuous sliding mode control with feedback linearization for a large scale wind turbine with wind speed estimation," Renewable Energy, Elsevier, vol. 127(C), pages 495-508.

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