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Pitch Angle Controller of Wind Turbine System Using Neural Network

신경망을 이용한 풍력 발전시스템의 피치제어

  • Hong, Min-Ho (Department of Electronic Engineering, Juju National University) ;
  • Ko, Seung-Youn (Department of Electronic Engineering, Juju National University) ;
  • Kim, Ho-Chan (Department of Electrical Engineering, Juju National University) ;
  • Hur, Jong-Chul (Department of Mechanical Engineering, Juju National University) ;
  • Kang, Min-Jae (Department of Electronic Engineering, Juju National University)
  • Received : 2014.01.06
  • Accepted : 2014.02.05
  • Published : 2014.02.28

Abstract

Wind turbine system can obtain the maximum wind energy using torque control under the rated wind speed, and wind turbine power is controlled as the rated power using pitch control over the rated wind speed. In this paper, we present a method for wind turbine pitch controller using neural networks. The purpose of the pitch control is to control generator speed and power in the above rated wind speed. To improve the neural network pitch controller, the difference between a rated and current speed of generator has been used for another input of neural networks as well as wind speed. Error back-propagation algorithm is used for training the neural network pitch controller and simulation and Matlab/Simulink is used for verifying that this system is controlled well.

풍력발전시스템은 정격풍속미만에서는 토크를 제어하여 바람의 에너지를 최대로 하고 정격풍속이상에서는 피치를 제어하여 발전량을 정격으로 유지한다. 본 논문에서는 풍력발전시스템의 피치제어를 신경망을 이용하여 제어하는 방안을 제시한다. 피치제어의 목적은 정격풍속 이상에서 발전기의 회전속도를 일정하게 제어하여, 결과적으로 발전기의 출력을 정격전력으로 유지한다. 이 논문에서는 신경망 피치제어기의 성능을 향상시키기 위하여 발전기의 정격회전속도와 현재 회전속도 차이를 풍속과 함께 신경망의 입력으로 사용하는 방법을 제안하였다. 신경망의 훈련 알고리즘은 오류역전파(error back-propagation) 방법이 사용되었고, Matlab/Simulink를 사용하여 제어가 원활하게 되는 것을 확인하였다.

Keywords

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