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Genetically Optimized Pitch Angle Controller of a Wind Turbine with Fuzzy Logic Design Approach

Author

Listed:
  • Ahmet Selim Pehlivan

    (Mechatronics Engineering, Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey)

  • Beste Bahceci

    (Mechatronics Engineering, Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey)

  • Kemalettin Erbatur

    (Mechatronics Engineering, Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul 34956, Turkey)

Abstract

An important engineering challenge is the design of a wind turbine’s pitch angle controller. The dependability, safety, and power output maximization of a wind turbine are all impacted by this controller. In this study, a 2 MW doubly fed induction generator wind turbine’s blade angle controller design with a novel fuzzy logic controller is tested in a simulated environment. The evolutionary algorithm technique is used to optimize the fuzzy logic controller with three inputs. A genetic algorithm is used to optimize the specified pitch angle controller for a number of coefficients. After the optimization process, the controller’s performance is assessed in terms of power output, overshoot, and steady-state error characteristics.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6705-:d:914153
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    References listed on IDEAS

    as
    1. 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.
    2. Ali, Ehab S., 2015. "Speed control of induction motor supplied by wind turbine via Imperialist Competitive Algorithm," Energy, Elsevier, vol. 89(C), pages 593-600.
    3. Song, Dongran & Li, Ziqun & Wang, Lei & Jin, Fangjun & Huang, Chaoneng & Xia, E. & Rizk-Allah, Rizk M. & Yang, Jian & Su, Mei & Joo, Young Hoon, 2022. "Energy capture efficiency enhancement of wind turbines via stochastic model predictive yaw control based on intelligent scenarios generation," Applied Energy, Elsevier, vol. 312(C).
    4. Lee, Jaejoon & Son, Eunkuk & Hwang, Byungho & Lee, Soogab, 2013. "Blade pitch angle control for aerodynamic performance optimization of a wind farm," Renewable Energy, Elsevier, vol. 54(C), pages 124-130.
    5. 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.
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