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Energies 2014, 7(6), 3793-3809; doi:10.3390/en7063793
Article

Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms

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Received: 20 March 2014 / Revised: 4 June 2014 / Accepted: 12 June 2014 / Published: 18 June 2014
(This article belongs to the Special Issue Wind Turbines 2014)
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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.
Keywords: setpoint; wind turbines; PSO; Reinforcement Learning; pitch setpoint; wind turbines; PSO; Reinforcement Learning; pitch
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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González-González, A.; Etxeberria-Agiriano, I.; Zulueta, E.; Oterino-Echavarri, F.; Lopez-Guede, J.M. Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms. Energies 2014, 7, 3793-3809.

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