Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms

This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches in...

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Published inEnergies (Basel) Vol. 7; no. 6; pp. 3793 - 3809
Main Authors Gonzalez-Gonzalez, Asier, Etxeberria-Agiriano, Ismael, Zulueta, Ekaitz, Oterino-Echavarri, Fernando, Lopez-Guede, Jose Manuel
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2014
Subjects
Adjustment
Aerodynamics
Algorithms
Control algorithms
Engineering schools
Optimization techniques
pitch
Pitch angle
PSO
Reinforcement Learning
Rotor speed
setpoint
Strategy
Swarm intelligence
Turbines
University colleges
Wind turbines
Spain
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Abstract This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches including Reinforcement Learning, the best results were obtained using a Particle Swarm Optimization (PSO)-based wind turbine speed setpoint algorithm. A reward improvement of up to 10.67% has been achieved using PSO compared to a constant approach and 0.48% compared to a conventional approach. We conclude that the pitch angle is the most adequate input variable for the turbine speed setpoint algorithm compared to others such as rotor speed, or rotor angular acceleration.
AbstractList This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to improve a reward function that takes into account the power captured from the wind and the turbine speed error. After different approaches including Reinforcement Learning, the best results were obtained using a Particle Swarm Optimization (PSO)-based wind turbine speed setpoint algorithm. A reward improvement of up to 10.67% has been achieved using PSO compared to a constant approach and 0.48% compared to a conventional approach. We conclude that the pitch angle is the most adequate input variable for the turbine speed setpoint algorithm compared to others such as rotor speed, or rotor angular acceleration.
Author Lopez-Guede, Jose Manuel
Gonzalez-Gonzalez, Asier
Etxeberria-Agiriano, Ismael
Zulueta, Ekaitz
Oterino-Echavarri, Fernando
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10.3390/en5114683
10.3390/en6115717
10.4316/aece.2010.02027
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Snippet This work is aimed at optimizing the wind turbine rotor speed setpoint algorithm. Several intelligent adjustment strategies have been investigated in order to...
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StartPage 3793
SubjectTerms Adjustment
Aerodynamics
Algorithms
Control algorithms
Engineering schools
Optimization techniques
pitch
Pitch angle
PSO
Reinforcement Learning
Rotor speed
setpoint
Strategy
Swarm intelligence
Turbines
University colleges
Wind turbines
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Title Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms
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