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

Ahmet Selim Pehlivan (), Beste Bahceci and Kemalettin Erbatur
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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

Energies, 2022, vol. 15, issue 18, 1-15

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.

Keywords: wind energy; wind turbine; pitch angle controller; genetic algorithm optimization; fuzzy logic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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