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논문검색

Study on the Low Voltage Ride-Through of Doubly-Fed Induction Generator Based on BP Neural Network

초록

영어

In order to ensure that wind turbines could be online under the condition of power grid transient fault, the technology of low voltage ride-through (LVRT) for wind turbine has become a research focus of experts and scholars at home and abroad. In current wind turbine control strategy, the PI parameters of the control system keep unchanged when the wind turbine is in the process of LVRT, which affects the performance of the control system. Therefore, the adaptive PI parameter adjustment system based on BP neural network is proposed, which realize the adaptive adjustment of PI parameters in the process of LVRT. The simulation model of the LVRT process was built, the simulation results show that this control algorithm can effectively restrain the current oscillation caused by the voltage sag, shorten the fault recovery time of the system, and has a good dynamic performance. Besides, the adaptability and robustness of the system has been increased, which has improved the low voltage ride-through capability of the system.

목차

Abstract
 1. Introduction
 2. The Wind Turbine Model for DFIG
  2.1. The Mathematical Model of DFIG
  2.2. The Control Strategies of DFIG
 3. The PI Controller based on BP Neural Network
  3.1. PI Controller
  3.2. BP Neural Network
  3.3. Design of PI Controller based on BP Neural Network
 4. Experiments
 5. Conclusion
 References

저자정보

  • Gu Bo School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450011, China
  • Zhang Lingyun School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450011, China
  • Li Xiaodan School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450011, China
  • Qiu Daoyin School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450011, China

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