Intelligent maximum power extraction control for wind energy conversion systems based on online Q-learning with function approximation

@article{Wei2014IntelligentMP,
  title={Intelligent maximum power extraction control for wind energy conversion systems based on online Q-learning with function approximation},
  author={Chun Wei and Zhe Zhang and Wei Qiao and Liyan Qu},
  journal={2014 IEEE Energy Conversion Congress and Exposition (ECCE)},
  year={2014},
  pages={4911-4916}
}
This paper proposes an intelligent maximum power point tracking (MPPT) algorithm for variable-speed wind energy conversion systems (WECSs) based on an online Q-learning algorithm. Instead of using the conventional Q-learning that uses a lookup table to store the action values for the discretized states, artificial neural networks (ANNs) are used as function approximators to output the action values by using the electrical power and rotor speed of the generator as inputs. This eliminates the… CONTINUE READING