Min Ding , Zili Tao , Bo Hu , Meng Ye , Yingxiong Ou , Ryuichi Yokoyama
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A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system
When the wind speed changes significantly in a permanent magnet synchronous wind power generation system, the maximum power point cannot be easily determined in a timely manner. This study proposes a maximum power reference signal search method based on fuzzy control, which is an improvement to the climbing search method. A neural network-based parameter regulator is proposed to address external wind speed fluctuations, where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions. Finally, the effectiveness of this method is verified via Simulink simulation
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