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Smoothing wind power fluctuations by fuzzy logic pitch angle controller

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  • Chowdhury, M.A.
  • Hosseinzadeh, N.
  • Shen, W.X.

Abstract

Wind energy has been receiving more acceptance as a reproducible, resourceful and clean energy source since last decade. Wind power is not constant and may fluctuate below the rated wind power when the wind speed is lower than the rated speed. This fact affects the stability of the power system, to which the wind generators are connected. This is becoming more significant with the increasing penetration of wind energy systems. Pitch angle control has been one of the most common methods for smoothing output power fluctuations during below rated wind incidents. A fuzzy logic pitch angle controller is proposed in this paper for smoothing wind power fluctuations during below rated wind incidents beside traditional power regulations during above rated wind incidents. Two smoothing methods have been presented: the determination of the command output power based on the exponential moving average with a proper selection of correction factor by fuzzy reasoning and the dynamic selection of target output power according to the wind incident. Simulation results show the effectiveness of the proposed fuzzy logic pitch angle controller in smoothing output power fluctuations with significantly small drop of output power.

Suggested Citation

  • Chowdhury, M.A. & Hosseinzadeh, N. & Shen, W.X., 2012. "Smoothing wind power fluctuations by fuzzy logic pitch angle controller," Renewable Energy, Elsevier, vol. 38(1), pages 224-233.
    • Handle: RePEc:eee:renene:v:38:y:2012:i:1:p:224-233
    DOI: 10.1016/j.renene.2011.07.034
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    References listed on IDEAS

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    Cited by:

    1. Nikita Tomin, 2023. "Robust Reinforcement Learning-Based Multiple Inputs and Multiple Outputs Controller for Wind Turbines," Mathematics, MDPI, vol. 11(14), pages 1-19, July.
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    3. 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.
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    5. Howlader, Abdul Motin & Urasaki, Naomitsu & Yona, Atsushi & Senjyu, Tomonobu & Saber, Ahmed Yousuf, 2013. "A review of output power smoothing methods for wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 135-146.
    6. Ikegami, Takashi & Urabe, Chiyori T. & Saitou, Tetsuo & Ogimoto, Kazuhiko, 2018. "Numerical definitions of wind power output fluctuations for power system operations," Renewable Energy, Elsevier, vol. 115(C), pages 6-15.
    7. Howlader, Abdul Motin & Izumi, Yuya & Uehara, Akie & Urasaki, Naomitsu & Senjyu, Tomonobu & Yona, Atsushi & Saber, Ahmed Yousuf, 2012. "A minimal order observer based frequency control strategy for an integrated wind-battery-diesel power system," Energy, Elsevier, vol. 46(1), pages 168-178.
    8. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    9. Lamsal, Dipesh & Sreeram, Victor & Mishra, Yateendra & Kumar, Deepak, 2019. "Output power smoothing control approaches for wind and photovoltaic generation systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    10. Wang, Longyan & Cholette, Michael E. & Zhou, Yunkai & Yuan, Jianping & Tan, Andy C.C. & Gu, Yuantong, 2018. "Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization," Renewable Energy, Elsevier, vol. 126(C), pages 819-829.
    11. Muhammad Jabir & Hazlee Azil Illias & Safdar Raza & Hazlie Mokhlis, 2017. "Intermittent Smoothing Approaches for Wind Power Output: A Review," Energies, MDPI, vol. 10(10), pages 1-23, October.
    12. Yin, Xiu-xing & Lin, Yong-gang & Li, Wei & Liu, Hong-wei & Gu, Ya-jing, 2014. "Output power control for hydro-viscous transmission based continuously variable speed wind turbine," Renewable Energy, Elsevier, vol. 72(C), pages 395-405.
    13. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2016. "Comprehensive overview of grid interfaced wind energy generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 260-281.
    14. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    15. 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.
    16. 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.

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