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Pitch angle control using hybrid controller for all operating regions of SCIG wind turbine system

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  • Duong, Minh Quan
  • Grimaccia, Francesco
  • Leva, Sonia
  • Mussetta, Marco
  • Ogliari, Emanuele

Abstract

In the past, wind power penetration was extremely limited compared to the total power production. As a result, the interconnection requirements for wind farms were not included in the grid codes. However, in the recent years, the significant amount of energy injected by wind farms has already impacted the power system, both from a technical and a regulatory point of view in the recent years. Large wind plants have a significant influence on power system operation since they are related to unpredictability of the primary source. Thus wind turbines must improve their quality production to ensure the stability and reliability of the power system as conventional power plants. Wind energy is not constant and, since wind turbines output is proportional to the cube of wind speed, this causes the power output of Squirrel-Cage Induction Generator Wind Turbine (SCIG WT) to fluctuate. In order to improve power quality and maintain the stable output generated from SCIG wind farm, this paper presents a hybrid controller based on PI and fuzzy technique for the pitch angle controller which has been one of the most common methods for smoothing output power fluctuations. All models as well as controllers here presented are developed using Matlab-Simulink software.

Suggested Citation

  • Duong, Minh Quan & Grimaccia, Francesco & Leva, Sonia & Mussetta, Marco & Ogliari, Emanuele, 2014. "Pitch angle control using hybrid controller for all operating regions of SCIG wind turbine system," Renewable Energy, Elsevier, vol. 70(C), pages 197-203.
    • Handle: RePEc:eee:renene:v:70:y:2014:i:c:p:197-203
    DOI: 10.1016/j.renene.2014.03.072
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    References listed on IDEAS

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    1. 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.
    2. Kamel, Rashad M. & Chaouachi, Aymen & Nagasaka, Ken, 2010. "Wind power smoothing using fuzzy logic pitch controller and energy capacitor system for improvement Micro-Grid performance in islanding mode," Energy, Elsevier, vol. 35(5), pages 2119-2129.
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    Cited by:

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    3. Mohamed Zribi & Muthana Alrifai & Mohamed Rayan, 2017. "Sliding Mode Control of a Variable- Speed Wind Energy Conversion System Using a Squirrel Cage Induction Generator," Energies, MDPI, vol. 10(5), pages 1-21, May.
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    6. 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.
    7. Ramji Tiwari & Sanjeevikumar Padmanaban & Ramesh Babu Neelakandan, 2017. "Coordinated Control Strategies for a Permanent Magnet Synchronous Generator Based Wind Energy Conversion System," Energies, MDPI, vol. 10(10), pages 1-17, September.
    8. Chan Roh, 2022. "Deep-Learning-Based Pitch Controller for Floating Offshore Wind Turbine Systems with Compensation for Delay of Hydraulic Actuators," Energies, MDPI, vol. 15(9), pages 1-18, April.
    9. Gao, Richie & Gao, Zhiwei, 2016. "Pitch control for wind turbine systems using optimization, estimation and compensation," Renewable Energy, Elsevier, vol. 91(C), pages 501-515.
    10. Shrabani Sahu & Sasmita Behera, 2022. "A review on modern control applications in wind energy conversion system," Energy & Environment, , vol. 33(2), pages 223-262, March.
    11. 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.
    12. Ching-Sung Wang & Mao-Hsiung Chiang, 2016. "A Novel Pitch Control System of a Large Wind Turbine Using Two-Degree-of-Freedom Motion Control with Feedback Linearization Control," Energies, MDPI, vol. 9(10), pages 1-18, September.
    13. Minh Quan Duong & Francesco Grimaccia & Sonia Leva & Marco Mussetta & Kim Hung Le, 2015. "Improving Transient Stability in a Grid-Connected Squirrel-Cage Induction Generator Wind Turbine System Using a Fuzzy Logic Controller," Energies, MDPI, vol. 8(7), pages 1-22, June.
    14. Jun Dong & Shengnan Li & Shuijun Wu & Tingyi He & Bo Yang & Hongchun Shu & Jilai Yu, 2017. "Nonlinear Observer-Based Robust Passive Control of Doubly-Fed Induction Generators for Power System Stability Enhancement via Energy Reshaping," Energies, MDPI, vol. 10(8), pages 1-16, July.
    15. Deyi Fu & Lingxing Kong & Lice Gong & Anqing Wang & Haikun Jia & Na Zhao, 2023. "Wind Turbine Load Optimization Control Strategy Based on LIDAR Feed-Forward Control for Primary Frequency Modulation Process with Pitch Angle Reservation," Energies, MDPI, vol. 16(1), pages 1-14, January.
    16. El-Baklish, Shaimaa K. & El-Badawy, Ayman A. & Frison, Gianluca & Diehl, Moritz, 2020. "Nonlinear model predictive pitch control of aero-elastic wind turbine blades," Renewable Energy, Elsevier, vol. 161(C), pages 777-791.
    17. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    18. 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.

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